diff --git a/getting_started/getting_started_api.ipynb b/getting_started/getting_started_api.ipynb index 455d124..85b7dc4 100644 --- a/getting_started/getting_started_api.ipynb +++ b/getting_started/getting_started_api.ipynb @@ -30,9 +30,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "import os\n", @@ -330,9 +328,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "\n", @@ -428,9 +424,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "# Launch solar and wind generation\n", @@ -501,9 +495,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "%run ../chronix2grid/kpi/Generator_parameter_checker.py\n", @@ -657,9 +649,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "#for scenario_name in os.listdir(generation_output_folder):\n", @@ -823,9 +813,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "Ramps=delta_dispatch_no_monthly_rupture\n", diff --git a/getting_started/getting_started_cli.ipynb b/getting_started/getting_started_cli.ipynb index 0965663..c862822 100644 --- a/getting_started/getting_started_cli.ipynb +++ b/getting_started/getting_started_cli.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -31,54 +31,16 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Usage: chronix2grid [OPTIONS]\n", - "\n", - "Options:\n", - " --case TEXT case folder to base generation on\n", - " --start-date TEXT Start date to generate chronics\n", - " --weeks INTEGER Number of weeks to generate\n", - " --by-n-weeks INTEGER Size of the output chunks in weeks\n", - " --n_scenarios INTEGER Number of scenarios to generate\n", - " --mode TEXT Steps to execute : L for loads only (and KPI);\n", - " R(K) for renewables (and KPI) only; LRTK for all\n", - " generation\n", - "\n", - " --input-folder TEXT Directory to read input files from.\n", - " --output-folder TEXT Directory to store output files.\n", - " --seed-for-loads TEXT Input seed to ensure reproducibility of loads\n", - " generation\n", - "\n", - " --seed-for-res TEXT Input seed to ensure reproducibility of renewables\n", - " generation\n", - "\n", - " --seed-for-dispatch TEXT Input seed to ensure reproducibility of dispatch\n", - " --ignore-warnings Ignore the warnings related to the existence of\n", - " data files in the chosen output directory.\n", - "\n", - " --scenario_name TEXT subname to add to the generated scenario output\n", - " folder, as Scenario_subname_i\n", - "\n", - " --nb_core INTEGER number of cores to parallelize the number of\n", - " scenarios\n", - "\n", - " --help Show this message and exit.\n" - ] - } - ], + "outputs": [], "source": [ "!chronix2grid --help" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -105,20 +67,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'chronix2grid --mode RLTK --output-folder /home/vrenault/Projects/ChroniX2Grid/getting_started/example/output --input-folder /home/vrenault/Projects/ChroniX2Grid/getting_started/example/input --ignore-warnings --weeks 8 --case case118_l2rpn_wcci --n_scenarios 1 --start-date 2012-01-01 --by-n-weeks 4'" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "cli_chronix2grid=\"chronix2grid \\\n", " --mode {} --output-folder {} --input-folder {} --ignore-warnings \\\n", @@ -129,76 +80,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "case118_l2rpn_wcci\n", - "initial_seeds\n", - "{'loads': 1046744458, 'renewables': 1046744458, 'dispatch': 1046744458}\n", - "seeds for scenario: Scenario_0\n", - "{'loads': 1046744458, 'renewables': 1046744458, 'dispatch': 1046744458}\n", - "scenarion_path: /home/vrenault/Projects/ChroniX2Grid/getting_started/example/output/generation/case118_l2rpn_wcci/2012-01-01/Scenario_0\n", - "=====================================================================================================================================\n", - "============================================== CHRONICS GENERATION ==================================================================\n", - "=====================================================================================================================================\n", - "/home/vrenault/Projects/ChroniX2Grid/venv_test/lib/python3.6/site-packages/grid2op/MakeEnv/Make.py:248: UserWarning:\n", - "\n", - "You are using a development environment. This environment is not intended for training agents.\n", - "\n", - "================ Generating Scenario_0 ================\n", - "Computing global auto-correlated spatio-temporal noise for thermosensible demand...\n", - "Computing loads ...\n", - "Saving files in zipped csv in \"/home/vrenault/Projects/ChroniX2Grid/getting_started/example/output/generation/case118_l2rpn_wcci/2012-01-01/Scenario_0\"\n", - "Computing global auto-correlated spatio-temporal noise for sun and wind...\n", - "Generating solar and wind production chronics\n", - "Saving files in zipped csv\n", - "mode_opf is not None\n", - "Preprocessing input data..\n", - "Filter generators ramps up/down\n", - "Adapting PyPSA grid with parameters..\n", - "mode_opf is not None\n", - "\n", - "--> OPF formulation by => month - Analyzing month # 1\n", - "INFO:pypsa.linopf:Prepare linear problem\n", - "INFO:pypsa.linopf:Total preparation time: 7.42s\n", - "INFO:pypsa.linopf:Solve linear problem using Cbc solver\n", - "INFO:pypsa.linopf:Optimization successful. Objective value: 1.07e+09\n", - "-- opf succeeded >Objective value (should be greater than zero!\n", - "\n", - "--> OPF formulation by => month - Analyzing month # 2\n", - "INFO:pypsa.linopf:Prepare linear problem\n", - "INFO:pypsa.linopf:Total preparation time: 5.79s\n", - "INFO:pypsa.linopf:Solve linear problem using Cbc solver\n", - "INFO:pypsa.linopf:Optimization successful. Objective value: 8.48e+08\n", - "-- opf succeeded >Objective value (should be greater than zero!\n", - "Total time 2.07 min\n", - "OPF Done......\n", - "Saving results for the grids with individual generators...\n", - "applying noise to forecast of 0.01 %\n", - "\n", - "\n", - "=====================================================================================================================================\n", - "================================================= KPI GENERATION ===================================================================\n", - "=====================================================================================================================================\n", - "Scenario_0...\n", - "Warning: KPI are incomplete. Computation has been made on 8 weeks, but are meant to be computed on 52 weeks\n", - "Importing and formatting data downloaded from regional eco2mix data\n", - "Importing and formatting synthetic chronics\n", - "(1) Computing KPI's...\n", - "Warning: prices data have not been given for both synthetic and reference dispatch. Quantiles will be computed on demand instead. Next time, you can provide .../France/eco2mix/prices_2012.csv.bz2 \n", - "\n", - "(2) Generating json output file...\n", - "-Done-\n", - "\n", - "multiprocessing done\n", - "Time taken = 327.52284812927246 seconds\n" - ] - } - ], + "outputs": [], "source": [ "!$cli_chronix2grid" ] diff --git a/getting_started/running_chronics_grid2op.ipynb b/getting_started/running_chronics_grid2op.ipynb index d7360de..bad7f02 100644 --- a/getting_started/running_chronics_grid2op.ipynb +++ b/getting_started/running_chronics_grid2op.ipynb @@ -23,9 +23,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "import os\n", @@ -109,9 +107,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "from grid2op.Chronics import Multifolder, GridStateFromFileWithForecasts\n", @@ -215,9 +211,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "!ls $path_data_saved" @@ -297,9 +291,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "\n", @@ -362,9 +354,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "scrolled": true - }, + "metadata": {}, "outputs": [], "source": [ "prods_p_perType[['nuclear','hydro','thermal']].iplot(kind='scatter', filename='cufflinks/cf-simple-line')" diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/config.py b/input_data/generation/l2rpn_case14_sandbox_1x/config.py new file mode 100644 index 0000000..920d8d1 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/config.py @@ -0,0 +1,40 @@ +from grid2op.Action import TopologyAndDispatchAction +from grid2op.Reward import RedispReward +from grid2op.Rules import DefaultRules +from grid2op.Chronics import Multifolder +from grid2op.Chronics import GridStateFromFileWithForecasts +from grid2op.Backend import PandaPowerBackend + +config = { + "backend": PandaPowerBackend, + "action_class": TopologyAndDispatchAction, + "observation_class": None, + "reward_class": RedispReward, + "gamerules_class": DefaultRules, + "chronics_class": Multifolder, + "grid_value_class": GridStateFromFileWithForecasts, + "volagecontroler_class": None, + "thermal_limits": [ + 541., + 450., + 375., + 636., + 175., + 285., + 335., + 657., + 496., + 827., + 442., + 641., + 840., + 156., + 664., + 235., + 119., + 179., + 1986., + 1572. + ], + "names_chronics_to_grid": None +} diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/grid.json b/input_data/generation/l2rpn_case14_sandbox_1x/grid.json new file mode 100644 index 0000000..c118ea3 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/grid.json @@ -0,0 +1,1363 @@ +{ + "_module": "pandapower.auxiliary", + "_class": "pandapowerNet", + "_object": { + "bus": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"vn_kv\",\"type\",\"zone\",\"in_service\",\"min_vm_pu\",\"max_vm_pu\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[1,138.0,\"b\",1.0,true,0.94,1.06],[2,138.0,\"b\",1.0,true,0.94,1.06],[3,138.0,\"b\",1.0,true,0.94,1.06],[4,138.0,\"b\",1.0,true,0.94,1.06],[5,138.0,\"b\",1.0,true,0.94,1.06],[6,20.0,\"b\",1.0,true,0.94,1.06],[7,14.0,\"b\",1.0,true,0.94,1.06],[8,12.0,\"b\",1.0,true,0.94,1.06],[9,20.0,\"b\",1.0,true,0.94,1.06],[10,20.0,\"b\",1.0,true,0.94,1.06],[11,20.0,\"b\",1.0,true,0.94,1.06],[12,20.0,\"b\",1.0,true,0.94,1.06],[13,20.0,\"b\",1.0,true,0.94,1.06],[14,20.0,\"b\",1.0,true,0.94,1.06]]}", + "orient": "split", + "dtype": { + "name": "object", + "vn_kv": "float64", + "type": "object", + "zone": "object", + "in_service": "bool", + "min_vm_pu": "float64", + "max_vm_pu": "float64" + } + }, + "load": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"const_z_percent\",\"const_i_percent\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"controllable\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10],\"data\":[[null,1,21.699999999999999,12.699999999999999,0.0,0.0,null,1.0,true,null,false],[null,2,94.200000000000003,19.0,0.0,0.0,null,1.0,true,null,false],[null,3,47.799999999999997,-3.9,0.0,0.0,null,1.0,true,null,false],[null,4,7.6,1.6,0.0,0.0,null,1.0,true,null,false],[null,5,11.199999999999999,7.5,0.0,0.0,null,1.0,true,null,false],[null,8,29.5,16.600000000000001,0.0,0.0,null,1.0,true,null,false],[null,9,9.0,5.8,0.0,0.0,null,1.0,true,null,false],[null,10,3.5,1.8,0.0,0.0,null,1.0,true,null,false],[null,11,6.1,1.6,0.0,0.0,null,1.0,true,null,false],[null,12,13.5,5.8,0.0,0.0,null,1.0,true,null,false],[null,13,14.9,5.0,0.0,0.0,null,1.0,true,null,false]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "p_mw": "float64", + "q_mvar": "float64", + "const_z_percent": "float64", + "const_i_percent": "float64", + "sn_mva": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object", + "controllable": "object" + } + }, + "sgen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"current_source\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "int64", + "p_mw": "float64", + "q_mvar": "float64", + "sn_mva": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object", + "current_source": "bool" + } + }, + "storage": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"sn_mva\",\"soc_percent\",\"min_e_mwh\",\"max_e_mwh\",\"scaling\",\"in_service\",\"type\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "int64", + "p_mw": "float64", + "q_mvar": "float64", + "sn_mva": "float64", + "soc_percent": "float64", + "min_e_mwh": "float64", + "max_e_mwh": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object" + } + }, + "gen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"vm_pu\",\"sn_mva\",\"min_q_mvar\",\"max_q_mvar\",\"scaling\",\"slack\",\"in_service\",\"type\",\"controllable\",\"min_p_mw\",\"max_p_mw\"],\"index\":[0,1,2,3,4],\"data\":[[null,1,40.0,1.045,null,-40.0,50.0,1.0,false,true,null,true,0.0,140.0],[null,2,0.0,1.01,null,0.0,40.0,1.0,false,true,null,true,0.0,100.0],[null,5,0.0,1.07,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0],[null,5,0.0,1.07,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0],[null,7,0.0,1.09,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "p_mw": "float64", + "vm_pu": "float64", + "sn_mva": "float64", + "min_q_mvar": "float64", + "max_q_mvar": "float64", + "scaling": "float64", + "slack": "bool", + "in_service": "bool", + "type": "object", + "controllable": "bool", + "min_p_mw": "float64", + "max_p_mw": "float64" + } + }, + "switch": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"bus\",\"element\",\"et\",\"type\",\"closed\",\"name\",\"z_ohm\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "bus": "int64", + "element": "int64", + "et": "object", + "type": "object", + "closed": "bool", + "name": "object", + "z_ohm": "float64" + } + }, + "shunt": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"bus\",\"name\",\"q_mvar\",\"p_mw\",\"vn_kv\",\"step\",\"max_step\",\"in_service\"],\"index\":[0],\"data\":[[8,null,-19.0,0.0,20.0,1,1,true]]}", + "orient": "split", + "dtype": { + "bus": "uint32", + "name": "object", + "q_mvar": "float64", + "p_mw": "float64", + "vn_kv": "float64", + "step": "uint32", + "max_step": "uint32", + "in_service": "bool" + } + }, + "ext_grid": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"vm_pu\",\"va_degree\",\"in_service\",\"min_p_mw\",\"max_p_mw\",\"min_q_mvar\",\"max_q_mvar\"],\"index\":[0],\"data\":[[null,0,1.06,0.0,true,0.0,332.399999999999977,0.0,10.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "vm_pu": "float64", + "va_degree": "float64", + "in_service": "bool", + "min_p_mw": "float64", + "max_p_mw": "float64", + "min_q_mvar": "float64", + "max_q_mvar": "float64" + } + }, + "line": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"from_bus\",\"to_bus\",\"length_km\",\"r_ohm_per_km\",\"x_ohm_per_km\",\"c_nf_per_km\",\"g_us_per_km\",\"max_i_ka\",\"df\",\"parallel\",\"type\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14],\"data\":[[null,null,0,1,1.0,3.6907272,11.2683348,882.522683811391971,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,0,4,1.0,10.2894732,42.475737599999995,822.350682642433412,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,2,1.0,8.948775599999999,37.701406800000001,732.092680888995574,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,3,1.0,11.0664684,33.578380799999998,568.29112215127509,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,4,1.0,10.845558,33.1137072,578.319789012768069,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,2,3,1.0,12.761384400000001,32.570953199999998,213.94489304518595,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,3,4,1.0,2.542374,8.019428400000001,0.0,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,5,10,1.0,0.37992,0.7956,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,5,11,1.0,0.49164,1.02324,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,5,12,1.0,0.2646,0.52108,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,8,9,1.0,0.12724,0.338,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,8,13,1.0,0.50844,1.08152,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,9,10,1.0,0.3282,0.76828,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,11,12,1.0,0.88368,0.79952,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,12,13,1.0,0.68372,1.39208,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "length_km": "float64", + "r_ohm_per_km": "float64", + "x_ohm_per_km": "float64", + "c_nf_per_km": "float64", + "g_us_per_km": "float64", + "max_i_ka": "float64", + "df": "float64", + "parallel": "uint32", + "type": "object", + "in_service": "bool", + "max_loading_percent": "float64" + } + }, + "trafo": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,138.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.200000000000002,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,138.0,20.0,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.100000000000003,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,138.0,20.0,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.799999999999995,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,8,6,9900.0,20.0,14.0,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "hv_bus": "uint32", + "lv_bus": "uint32", + "sn_mva": "float64", + "vn_hv_kv": "float64", + "vn_lv_kv": "float64", + "vk_percent": "float64", + "vkr_percent": "float64", + "pfe_kw": "float64", + "i0_percent": "float64", + "shift_degree": "float64", + "tap_side": "object", + "tap_neutral": "float64", + "tap_min": "float64", + "tap_max": "float64", + "tap_step_percent": "float64", + "tap_step_degree": "float64", + "tap_pos": "float64", + "tap_phase_shifter": "bool", + "parallel": "uint32", + "df": "float64", + "in_service": "bool", + "max_loading_percent": "float64" + } + }, + "trafo3w": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "hv_bus": "uint32", + "mv_bus": "uint32", + "lv_bus": "uint32", + "sn_hv_mva": "float64", + "sn_mv_mva": "float64", + "sn_lv_mva": "float64", + "vn_hv_kv": "float64", + "vn_mv_kv": "float64", + "vn_lv_kv": "float64", + "vk_hv_percent": "float64", + "vk_mv_percent": "float64", + "vk_lv_percent": "float64", + "vkr_hv_percent": "float64", + "vkr_mv_percent": "float64", + "vkr_lv_percent": "float64", + "pfe_kw": "float64", + "i0_percent": "float64", + "shift_mv_degree": "float64", + "shift_lv_degree": "float64", + "tap_side": "object", + "tap_neutral": "int32", + "tap_min": "int32", + "tap_max": "int32", + "tap_step_percent": "float64", + "tap_step_degree": "float64", + "tap_pos": "int32", + "tap_at_star_point": "bool", + "in_service": "bool" + } + }, + "impedance": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"from_bus\",\"to_bus\",\"rft_pu\",\"xft_pu\",\"rtf_pu\",\"xtf_pu\",\"sn_mva\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "rft_pu": "float64", + "xft_pu": "float64", + "rtf_pu": "float64", + "xtf_pu": "float64", + "sn_mva": "float64", + "in_service": "bool" + } + }, + "dcline": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"from_bus\",\"to_bus\",\"p_mw\",\"loss_percent\",\"loss_mw\",\"vm_from_pu\",\"vm_to_pu\",\"max_p_mw\",\"min_q_from_mvar\",\"min_q_to_mvar\",\"max_q_from_mvar\",\"max_q_to_mvar\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "p_mw": "float64", + "loss_percent": "float64", + "loss_mw": "float64", + "vm_from_pu": "float64", + "vm_to_pu": "float64", + "max_p_mw": "float64", + "min_q_from_mvar": "float64", + "min_q_to_mvar": "float64", + "max_q_from_mvar": "float64", + "max_q_to_mvar": "float64", + "in_service": "bool" + } + }, + "ward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"ps_mw\",\"qs_mvar\",\"qz_mvar\",\"pz_mw\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "ps_mw": "float64", + "qs_mvar": "float64", + "qz_mvar": "float64", + "pz_mw": "float64", + "in_service": "bool" + } + }, + "xward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"ps_mw\",\"qs_mvar\",\"qz_mvar\",\"pz_mw\",\"r_ohm\",\"x_ohm\",\"vm_pu\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "ps_mw": "float64", + "qs_mvar": "float64", + "qz_mvar": "float64", + "pz_mw": "float64", + "r_ohm": "float64", + "x_ohm": "float64", + "vm_pu": "float64", + "in_service": "bool" + } + }, + "measurement": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"measurement_type\",\"element_type\",\"element\",\"value\",\"std_dev\",\"side\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "measurement_type": "object", + "element_type": "object", + "element": "uint32", + "value": "float64", + "std_dev": "float64", + "side": "object" + } + }, + "pwl_cost": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"power_type\",\"element\",\"et\",\"points\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "power_type": "object", + "element": "uint32", + "et": "object", + "points": "object" + } + }, + "poly_cost": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"element\",\"et\",\"cp0_eur\",\"cp1_eur_per_mw\",\"cp2_eur_per_mw2\",\"cq0_eur\",\"cq1_eur_per_mvar\",\"cq2_eur_per_mvar2\"],\"index\":[0,1,2,3,4],\"data\":[[0,\"ext_grid\",0.0,20.0,0.0430293,0.0,0.0,0.0],[0,\"gen\",0.0,20.0,0.25,0.0,0.0,0.0],[1,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0],[2,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0],[3,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0]]}", + "orient": "split", + "dtype": { + "element": "uint32", + "et": "object", + "cp0_eur": "float64", + "cp1_eur_per_mw": "float64", + "cp2_eur_per_mw2": "float64", + "cq0_eur": "float64", + "cq1_eur_per_mvar": "float64", + "cq2_eur_per_mvar2": "float64" + } + }, + "controller": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\",\"in_service\",\"order\",\"level\",\"recycle\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object", + "in_service": "bool", + "order": "float64", + "level": "object", + "recycle": "bool" + } + }, + "line_geodata": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"coords\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "coords": "object" + } + }, + "bus_geodata": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"x\",\"y\",\"coords\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "x": "float64", + "y": "float64", + "coords": "object" + } + }, + "version": "2.2.1", + "converged": false, + "name": "", + "f_hz": 50, + "sn_mva": 100.0, + "std_types": { + "line": { + "NAYY 4x50 SE": { + "c_nf_per_km": 210, + "r_ohm_per_km": 0.642, + "x_ohm_per_km": 0.083, + "max_i_ka": 0.142, + "type": "cs", + "q_mm2": 50, + "alpha": 0.00403 + }, + "NAYY 4x120 SE": { + "c_nf_per_km": 264, + "r_ohm_per_km": 0.225, + "x_ohm_per_km": 0.08, + "max_i_ka": 0.242, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NAYY 4x150 SE": { + "c_nf_per_km": 261, + "r_ohm_per_km": 0.208, + "x_ohm_per_km": 0.08, + "max_i_ka": 0.27, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x95 RM/25 12/20 kV": { + "c_nf_per_km": 216, + "r_ohm_per_km": 0.313, + "x_ohm_per_km": 0.132, + "max_i_ka": 0.252, + "type": "cs", + "q_mm2": 95, + "alpha": 0.00403 + }, + "NA2XS2Y 1x185 RM/25 12/20 kV": { + "c_nf_per_km": 273, + "r_ohm_per_km": 0.161, + "x_ohm_per_km": 0.117, + "max_i_ka": 0.362, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00403 + }, + "NA2XS2Y 1x240 RM/25 12/20 kV": { + "c_nf_per_km": 304, + "r_ohm_per_km": 0.122, + "x_ohm_per_km": 0.112, + "max_i_ka": 0.421, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00403 + }, + "NA2XS2Y 1x95 RM/25 6/10 kV": { + "c_nf_per_km": 315, + "r_ohm_per_km": 0.313, + "x_ohm_per_km": 0.123, + "max_i_ka": 0.249, + "type": "cs", + "q_mm2": 95, + "alpha": 0.00403 + }, + "NA2XS2Y 1x185 RM/25 6/10 kV": { + "c_nf_per_km": 406, + "r_ohm_per_km": 0.161, + "x_ohm_per_km": 0.11, + "max_i_ka": 0.358, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00403 + }, + "NA2XS2Y 1x240 RM/25 6/10 kV": { + "c_nf_per_km": 456, + "r_ohm_per_km": 0.122, + "x_ohm_per_km": 0.105, + "max_i_ka": 0.416, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00403 + }, + "NA2XS2Y 1x150 RM/25 12/20 kV": { + "c_nf_per_km": 250, + "r_ohm_per_km": 0.206, + "x_ohm_per_km": 0.116, + "max_i_ka": 0.319, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x120 RM/25 12/20 kV": { + "c_nf_per_km": 230, + "r_ohm_per_km": 0.253, + "x_ohm_per_km": 0.119, + "max_i_ka": 0.283, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NA2XS2Y 1x70 RM/25 12/20 kV": { + "c_nf_per_km": 190, + "r_ohm_per_km": 0.443, + "x_ohm_per_km": 0.132, + "max_i_ka": 0.22, + "type": "cs", + "q_mm2": 70, + "alpha": 0.00403 + }, + "NA2XS2Y 1x150 RM/25 6/10 kV": { + "c_nf_per_km": 360, + "r_ohm_per_km": 0.206, + "x_ohm_per_km": 0.11, + "max_i_ka": 0.315, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x120 RM/25 6/10 kV": { + "c_nf_per_km": 340, + "r_ohm_per_km": 0.253, + "x_ohm_per_km": 0.113, + "max_i_ka": 0.28, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NA2XS2Y 1x70 RM/25 6/10 kV": { + "c_nf_per_km": 280, + "r_ohm_per_km": 0.443, + "x_ohm_per_km": 0.123, + "max_i_ka": 0.217, + "type": "cs", + "q_mm2": 70, + "alpha": 0.00403 + }, + "N2XS(FL)2Y 1x120 RM/35 64/110 kV": { + "c_nf_per_km": 112, + "r_ohm_per_km": 0.153, + "x_ohm_per_km": 0.166, + "max_i_ka": 0.366, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x185 RM/35 64/110 kV": { + "c_nf_per_km": 125, + "r_ohm_per_km": 0.099, + "x_ohm_per_km": 0.156, + "max_i_ka": 0.457, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x240 RM/35 64/110 kV": { + "c_nf_per_km": 135, + "r_ohm_per_km": 0.075, + "x_ohm_per_km": 0.149, + "max_i_ka": 0.526, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x300 RM/35 64/110 kV": { + "c_nf_per_km": 144, + "r_ohm_per_km": 0.06, + "x_ohm_per_km": 0.144, + "max_i_ka": 0.588, + "type": "cs", + "q_mm2": 300, + "alpha": 0.00393 + }, + "15-AL1/3-ST1A 0.4": { + "c_nf_per_km": 11, + "r_ohm_per_km": 1.8769, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.105, + "type": "ol", + "q_mm2": 16, + "alpha": 0.00403 + }, + "24-AL1/4-ST1A 0.4": { + "c_nf_per_km": 11.25, + "r_ohm_per_km": 1.2012, + "x_ohm_per_km": 0.335, + "max_i_ka": 0.14, + "type": "ol", + "q_mm2": 24, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 0.4": { + "c_nf_per_km": 12.2, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.3, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 0.4": { + "c_nf_per_km": 13.2, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.29, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "34-AL1/6-ST1A 10.0": { + "c_nf_per_km": 9.7, + "r_ohm_per_km": 0.8342, + "x_ohm_per_km": 0.36, + "max_i_ka": 0.17, + "type": "ol", + "q_mm2": 34, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 10.0": { + "c_nf_per_km": 10.1, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 10.0": { + "c_nf_per_km": 10.4, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.339, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 10.0": { + "c_nf_per_km": 10.75, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.33, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 10.0": { + "c_nf_per_km": 11.1, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.323, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 10.0": { + "c_nf_per_km": 11.25, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.315, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "34-AL1/6-ST1A 20.0": { + "c_nf_per_km": 9.15, + "r_ohm_per_km": 0.8342, + "x_ohm_per_km": 0.382, + "max_i_ka": 0.17, + "type": "ol", + "q_mm2": 34, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 20.0": { + "c_nf_per_km": 9.5, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.372, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 20.0": { + "c_nf_per_km": 9.7, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.36, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 20.0": { + "c_nf_per_km": 10, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 20.0": { + "c_nf_per_km": 10.3, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.344, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 20.0": { + "c_nf_per_km": 10.5, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.337, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "184-AL1/30-ST1A 20.0": { + "c_nf_per_km": 10.75, + "r_ohm_per_km": 0.1571, + "x_ohm_per_km": 0.33, + "max_i_ka": 0.535, + "type": "ol", + "q_mm2": 184, + "alpha": 0.00403 + }, + "243-AL1/39-ST1A 20.0": { + "c_nf_per_km": 11, + "r_ohm_per_km": 0.1188, + "x_ohm_per_km": 0.32, + "max_i_ka": 0.645, + "type": "ol", + "q_mm2": 243, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 110.0": { + "c_nf_per_km": 8, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.46, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 110.0": { + "c_nf_per_km": 8.4, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.45, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 110.0": { + "c_nf_per_km": 8.65, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.44, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 110.0": { + "c_nf_per_km": 8.5, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.43, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 110.0": { + "c_nf_per_km": 8.75, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.41, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "184-AL1/30-ST1A 110.0": { + "c_nf_per_km": 8.8, + "r_ohm_per_km": 0.1571, + "x_ohm_per_km": 0.4, + "max_i_ka": 0.535, + "type": "ol", + "q_mm2": 184, + "alpha": 0.00403 + }, + "243-AL1/39-ST1A 110.0": { + "c_nf_per_km": 9, + "r_ohm_per_km": 0.1188, + "x_ohm_per_km": 0.39, + "max_i_ka": 0.645, + "type": "ol", + "q_mm2": 243, + "alpha": 0.00403 + }, + "305-AL1/39-ST1A 110.0": { + "c_nf_per_km": 9.2, + "r_ohm_per_km": 0.0949, + "x_ohm_per_km": 0.38, + "max_i_ka": 0.74, + "type": "ol", + "q_mm2": 305, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 110.0": { + "c_nf_per_km": 9.75, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.37, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 110.0": { + "c_nf_per_km": 9.95, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.36, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 220.0": { + "c_nf_per_km": 10, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.285, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 220.0": { + "c_nf_per_km": 11.7, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.275, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 380.0": { + "c_nf_per_km": 11, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.253, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 380.0": { + "c_nf_per_km": 14.6, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.25, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + } + }, + "trafo": { + "160 MVA 380/110 kV": { + "i0_percent": 0.06, + "pfe_kw": 60, + "vkr_percent": 0.25, + "sn_mva": 160, + "vn_lv_kv": 110.0, + "vn_hv_kv": 380.0, + "vk_percent": 12.2, + "shift_degree": 0, + "vector_group": "Yy0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "100 MVA 220/110 kV": { + "i0_percent": 0.06, + "pfe_kw": 55, + "vkr_percent": 0.26, + "sn_mva": 100, + "vn_lv_kv": 110.0, + "vn_hv_kv": 220.0, + "vk_percent": 12.0, + "shift_degree": 0, + "vector_group": "Yy0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "63 MVA 110/20 kV": { + "i0_percent": 0.04, + "pfe_kw": 22, + "vkr_percent": 0.32, + "sn_mva": 63, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 18, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "40 MVA 110/20 kV": { + "i0_percent": 0.05, + "pfe_kw": 18, + "vkr_percent": 0.34, + "sn_mva": 40, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 16.2, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "25 MVA 110/20 kV": { + "i0_percent": 0.07, + "pfe_kw": 14, + "vkr_percent": 0.41, + "sn_mva": 25, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 12, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "63 MVA 110/10 kV": { + "sn_mva": 63, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 18, + "vkr_percent": 0.32, + "pfe_kw": 22, + "i0_percent": 0.04, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "40 MVA 110/10 kV": { + "sn_mva": 40, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 16.2, + "vkr_percent": 0.34, + "pfe_kw": 18, + "i0_percent": 0.05, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "25 MVA 110/10 kV": { + "sn_mva": 25, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 12, + "vkr_percent": 0.41, + "pfe_kw": 14, + "i0_percent": 0.07, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "0.25 MVA 20/0.4 kV": { + "sn_mva": 0.25, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.44, + "pfe_kw": 0.8, + "i0_percent": 0.32, + "shift_degree": 150, + "vector_group": "Yzn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.4 MVA 20/0.4 kV": { + "sn_mva": 0.4, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.425, + "pfe_kw": 1.35, + "i0_percent": 0.3375, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.63 MVA 20/0.4 kV": { + "sn_mva": 0.63, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.206, + "pfe_kw": 1.65, + "i0_percent": 0.2619, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.25 MVA 10/0.4 kV": { + "sn_mva": 0.25, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.2, + "pfe_kw": 0.6, + "i0_percent": 0.24, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.4 MVA 10/0.4 kV": { + "sn_mva": 0.4, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.325, + "pfe_kw": 0.95, + "i0_percent": 0.2375, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.63 MVA 10/0.4 kV": { + "sn_mva": 0.63, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.0794, + "pfe_kw": 1.18, + "i0_percent": 0.1873, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + } + }, + "trafo3w": { + "63/25/38 MVA 110/20/10 kV": { + "sn_hv_mva": 63, + "sn_mv_mva": 25, + "sn_lv_mva": 38, + "vn_hv_kv": 110, + "vn_mv_kv": 20, + "vn_lv_kv": 10, + "vk_hv_percent": 10.4, + "vk_mv_percent": 10.4, + "vk_lv_percent": 10.4, + "vkr_hv_percent": 0.28, + "vkr_mv_percent": 0.32, + "vkr_lv_percent": 0.35, + "pfe_kw": 35, + "i0_percent": 0.89, + "shift_mv_degree": 0, + "shift_lv_degree": 0, + "vector_group": "YN0yn0yn0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -10, + "tap_max": 10, + "tap_step_percent": 1.2 + }, + "63/25/38 MVA 110/10/10 kV": { + "sn_hv_mva": 63, + "sn_mv_mva": 25, + "sn_lv_mva": 38, + "vn_hv_kv": 110, + "vn_mv_kv": 10, + "vn_lv_kv": 10, + "vk_hv_percent": 10.4, + "vk_mv_percent": 10.4, + "vk_lv_percent": 10.4, + "vkr_hv_percent": 0.28, + "vkr_mv_percent": 0.32, + "vkr_lv_percent": 0.35, + "pfe_kw": 35, + "i0_percent": 0.89, + "shift_mv_degree": 0, + "shift_lv_degree": 0, + "vector_group": "YN0yn0yn0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -10, + "tap_max": 10, + "tap_step_percent": 1.2 + } + } + }, + "res_bus": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"vm_pu\",\"va_degree\",\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "vm_pu": "float64", + "va_degree": "float64", + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_line": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"ql_mvar\",\"i_from_ka\",\"i_to_ka\",\"i_ka\",\"vm_from_pu\",\"va_from_degree\",\"vm_to_pu\",\"va_to_degree\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_from_ka": "float64", + "i_to_ka": "float64", + "i_ka": "float64", + "vm_from_pu": "float64", + "va_from_degree": "float64", + "vm_to_pu": "float64", + "va_to_degree": "float64", + "loading_percent": "float64" + } + }, + "res_trafo": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_hv_mw\",\"q_hv_mvar\",\"p_lv_mw\",\"q_lv_mvar\",\"pl_mw\",\"ql_mvar\",\"i_hv_ka\",\"i_lv_ka\",\"vm_hv_pu\",\"va_hv_degree\",\"vm_lv_pu\",\"va_lv_degree\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_hv_mw": "float64", + "q_hv_mvar": "float64", + "p_lv_mw": "float64", + "q_lv_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_hv_ka": "float64", + "i_lv_ka": "float64", + "vm_hv_pu": "float64", + "va_hv_degree": "float64", + "vm_lv_pu": "float64", + "va_lv_degree": "float64", + "loading_percent": "float64" + } + }, + "res_trafo3w": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_hv_mw\",\"q_hv_mvar\",\"p_mv_mw\",\"q_mv_mvar\",\"p_lv_mw\",\"q_lv_mvar\",\"pl_mw\",\"ql_mvar\",\"i_hv_ka\",\"i_mv_ka\",\"i_lv_ka\",\"vm_hv_pu\",\"va_hv_degree\",\"vm_mv_pu\",\"va_mv_degree\",\"vm_lv_pu\",\"va_lv_degree\",\"va_internal_degree\",\"vm_internal_pu\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_hv_mw": "float64", + "q_hv_mvar": "float64", + "p_mv_mw": "float64", + "q_mv_mvar": "float64", + "p_lv_mw": "float64", + "q_lv_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_hv_ka": "float64", + "i_mv_ka": "float64", + "i_lv_ka": "float64", + "vm_hv_pu": "float64", + "va_hv_degree": "float64", + "vm_mv_pu": "float64", + "va_mv_degree": "float64", + "vm_lv_pu": "float64", + "va_lv_degree": "float64", + "va_internal_degree": "float64", + "vm_internal_pu": "float64", + "loading_percent": "float64" + } + }, + "res_impedance": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"ql_mvar\",\"i_from_ka\",\"i_to_ka\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_from_ka": "float64", + "i_to_ka": "float64" + } + }, + "res_ext_grid": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_load": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_sgen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_storage": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_shunt": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64" + } + }, + "res_gen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"va_degree\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "va_degree": "float64", + "vm_pu": "float64" + } + }, + "res_ward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64" + } + }, + "res_xward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\",\"va_internal_degree\",\"vm_internal_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64", + "va_internal_degree": "float64", + "vm_internal_pu": "float64" + } + }, + "res_dcline": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"vm_from_pu\",\"va_from_degree\",\"vm_to_pu\",\"va_to_degree\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "vm_from_pu": "float64", + "va_from_degree": "float64", + "vm_to_pu": "float64", + "va_to_degree": "float64" + } + }, + "user_pf_options": {} + } +} diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/grid_layout.json b/input_data/generation/l2rpn_case14_sandbox_1x/grid_layout.json new file mode 100644 index 0000000..e153464 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/grid_layout.json @@ -0,0 +1,58 @@ +{ + "sub_0": [ + -280.0, + -81.0 + ], + "sub_1": [ + -100.0, + -270.0 + ], + "sub_2": [ + 366.0, + -270.0 + ], + "sub_3": [ + 366.0, + -54.0 + ], + "sub_4": [ + -64.0, + -54.0 + ], + "sub_5": [ + -64.0, + 54.0 + ], + "sub_6": [ + 450.0, + 0.0 + ], + "sub_7": [ + 550.0, + 0.0 + ], + "sub_8": [ + 326.0, + 54.0 + ], + "sub_9": [ + 222.0, + 108.0 + ], + "sub_10": [ + 79.0, + 162.0 + ], + "sub_11": [ + -170.0, + 270.0 + ], + "sub_12": [ + -64.0, + 270.0 + ], + "sub_13": [ + 222.0, + 216.0 + ] +} diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/loads_charac.csv b/input_data/generation/l2rpn_case14_sandbox_1x/loads_charac.csv new file mode 100644 index 0000000..cafe653 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/loads_charac.csv @@ -0,0 +1,13 @@ +Pmax,name,type,x,y +21.7,load_1_0,residential,180,10 +94.2,load_2_1,residential,646,10 +14.9,load_13_10,residential,646,226 +47.8,load_3_2,residential,216,226 +7.6,load_4_3,residential,216,334 +11.2,load_5_4,residential,606,334 +29.5,load_8_5,residential,502,388 +9.0,load_9_6,residential,359,442 +3.5,load_10_7,residential,128,550 +6.1,load_11_8,residential,216,550 +13.5,load_12_9,residential,502,496 + diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/params.json b/input_data/generation/l2rpn_case14_sandbox_1x/params.json new file mode 100644 index 0000000..183a084 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/params.json @@ -0,0 +1,4 @@ +{ + "dt": 5, + "planned_std": "0.01" +} diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/params_load.json b/input_data/generation/l2rpn_case14_sandbox_1x/params_load.json new file mode 100644 index 0000000..f40abf3 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/params_load.json @@ -0,0 +1,8 @@ +{ + "Lx": 1000, + "Ly": 1000, + "dx_corr": 250, + "dy_corr": 250, + "temperature_corr": 400, + "std_temperature_noise": 0.06 +} diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/params_loss.json b/input_data/generation/l2rpn_case14_sandbox_1x/params_loss.json new file mode 100644 index 0000000..717b866 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/params_loss.json @@ -0,0 +1 @@ +{"loss_pattern": "loss_pattern.csv"} \ No newline at end of file diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/params_opf.json b/input_data/generation/l2rpn_case14_sandbox_1x/params_opf.json new file mode 100644 index 0000000..94c2e38 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/params_opf.json @@ -0,0 +1 @@ +{"step_opf_min": 5, "mode_opf": "month", "reactive_comp": 1, "losses_pct": 0.4, "dispatch_by_carrier": false, "ramp_mode": "hard", "pyomo": false, "solver_name": "cbc", "idxSlack": 5, "nameSlack": "gen_0_5", "hydro_ramp_reduction_factor": 1, "slack_p_max_reduction": 30, "slack_ramp_max_reduction": 6, "loss_grid2op_simulation": true, "agent_type": "reco", "early_stopping_mode": false} diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/params_res.json b/input_data/generation/l2rpn_case14_sandbox_1x/params_res.json new file mode 100644 index 0000000..3542d3c --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/params_res.json @@ -0,0 +1,16 @@ +{ + "Lx": 1000, + "Ly": 1000, + "dx_corr": 250, + "dy_corr": 250, + "long_wind_corr": 5000, + "medium_wind_corr": 720, + "short_wind_corr": 120, + "solar_corr": 20, + "smoothdist": 0.001, + "std_solar_noise": 0.4, + "std_short_wind_noise": 0.1, + "std_medium_wind_noise": 0.15, + "std_long_wind_noise": 0.2, + "year_solar_pattern": 2007 +} diff --git a/input_data/generation/l2rpn_case14_sandbox_1x/prods_charac.csv b/input_data/generation/l2rpn_case14_sandbox_1x/prods_charac.csv new file mode 100644 index 0000000..95008df --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_1x/prods_charac.csv @@ -0,0 +1,7 @@ +Pmax,Pmin,name,type,bus,max_ramp_up,max_ramp_down,min_up_time,min_down_time,marginal_cost,shut_down_cost,start_cost,x,y,V +140,0.0,gen_1_0,nuclear,1,5,5,96,96,40,10,20,180,10,142.1 +120,0.0,gen_2_1,thermal,2,10,10,4,4,70,1,2,646,10,142.1 +20,0.0,gen_5_2,wind,5,0,0,0,0,0,0,0,216,334,22.0 +20,0.0,gen_5_3,solar,5,0,0,0,0,0,0,0,216,334,22.0 +10,0.0,gen_7_4,solar,7,0,0,0,0,0,0,0,718,280,13.2 +100,0.0,gen_0_5,hydro,0,15,15,4,4,70,1,2,0,199,142.1 diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/config.py b/input_data/generation/l2rpn_case14_sandbox_2x/config.py new file mode 100644 index 0000000..920d8d1 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/config.py @@ -0,0 +1,40 @@ +from grid2op.Action import TopologyAndDispatchAction +from grid2op.Reward import RedispReward +from grid2op.Rules import DefaultRules +from grid2op.Chronics import Multifolder +from grid2op.Chronics import GridStateFromFileWithForecasts +from grid2op.Backend import PandaPowerBackend + +config = { + "backend": PandaPowerBackend, + "action_class": TopologyAndDispatchAction, + "observation_class": None, + "reward_class": RedispReward, + "gamerules_class": DefaultRules, + "chronics_class": Multifolder, + "grid_value_class": GridStateFromFileWithForecasts, + "volagecontroler_class": None, + "thermal_limits": [ + 541., + 450., + 375., + 636., + 175., + 285., + 335., + 657., + 496., + 827., + 442., + 641., + 840., + 156., + 664., + 235., + 119., + 179., + 1986., + 1572. + ], + "names_chronics_to_grid": None +} diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/grid.json b/input_data/generation/l2rpn_case14_sandbox_2x/grid.json new file mode 100644 index 0000000..c118ea3 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/grid.json @@ -0,0 +1,1363 @@ +{ + "_module": "pandapower.auxiliary", + "_class": "pandapowerNet", + "_object": { + "bus": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"vn_kv\",\"type\",\"zone\",\"in_service\",\"min_vm_pu\",\"max_vm_pu\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[1,138.0,\"b\",1.0,true,0.94,1.06],[2,138.0,\"b\",1.0,true,0.94,1.06],[3,138.0,\"b\",1.0,true,0.94,1.06],[4,138.0,\"b\",1.0,true,0.94,1.06],[5,138.0,\"b\",1.0,true,0.94,1.06],[6,20.0,\"b\",1.0,true,0.94,1.06],[7,14.0,\"b\",1.0,true,0.94,1.06],[8,12.0,\"b\",1.0,true,0.94,1.06],[9,20.0,\"b\",1.0,true,0.94,1.06],[10,20.0,\"b\",1.0,true,0.94,1.06],[11,20.0,\"b\",1.0,true,0.94,1.06],[12,20.0,\"b\",1.0,true,0.94,1.06],[13,20.0,\"b\",1.0,true,0.94,1.06],[14,20.0,\"b\",1.0,true,0.94,1.06]]}", + "orient": "split", + "dtype": { + "name": "object", + "vn_kv": "float64", + "type": "object", + "zone": "object", + "in_service": "bool", + "min_vm_pu": "float64", + "max_vm_pu": "float64" + } + }, + "load": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"const_z_percent\",\"const_i_percent\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"controllable\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10],\"data\":[[null,1,21.699999999999999,12.699999999999999,0.0,0.0,null,1.0,true,null,false],[null,2,94.200000000000003,19.0,0.0,0.0,null,1.0,true,null,false],[null,3,47.799999999999997,-3.9,0.0,0.0,null,1.0,true,null,false],[null,4,7.6,1.6,0.0,0.0,null,1.0,true,null,false],[null,5,11.199999999999999,7.5,0.0,0.0,null,1.0,true,null,false],[null,8,29.5,16.600000000000001,0.0,0.0,null,1.0,true,null,false],[null,9,9.0,5.8,0.0,0.0,null,1.0,true,null,false],[null,10,3.5,1.8,0.0,0.0,null,1.0,true,null,false],[null,11,6.1,1.6,0.0,0.0,null,1.0,true,null,false],[null,12,13.5,5.8,0.0,0.0,null,1.0,true,null,false],[null,13,14.9,5.0,0.0,0.0,null,1.0,true,null,false]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "p_mw": "float64", + "q_mvar": "float64", + "const_z_percent": "float64", + "const_i_percent": "float64", + "sn_mva": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object", + "controllable": "object" + } + }, + "sgen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"current_source\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "int64", + "p_mw": "float64", + "q_mvar": "float64", + "sn_mva": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object", + "current_source": "bool" + } + }, + "storage": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"sn_mva\",\"soc_percent\",\"min_e_mwh\",\"max_e_mwh\",\"scaling\",\"in_service\",\"type\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "int64", + "p_mw": "float64", + "q_mvar": "float64", + "sn_mva": "float64", + "soc_percent": "float64", + "min_e_mwh": "float64", + "max_e_mwh": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object" + } + }, + "gen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"vm_pu\",\"sn_mva\",\"min_q_mvar\",\"max_q_mvar\",\"scaling\",\"slack\",\"in_service\",\"type\",\"controllable\",\"min_p_mw\",\"max_p_mw\"],\"index\":[0,1,2,3,4],\"data\":[[null,1,40.0,1.045,null,-40.0,50.0,1.0,false,true,null,true,0.0,140.0],[null,2,0.0,1.01,null,0.0,40.0,1.0,false,true,null,true,0.0,100.0],[null,5,0.0,1.07,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0],[null,5,0.0,1.07,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0],[null,7,0.0,1.09,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "p_mw": "float64", + "vm_pu": "float64", + "sn_mva": "float64", + "min_q_mvar": "float64", + "max_q_mvar": "float64", + "scaling": "float64", + "slack": "bool", + "in_service": "bool", + "type": "object", + "controllable": "bool", + "min_p_mw": "float64", + "max_p_mw": "float64" + } + }, + "switch": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"bus\",\"element\",\"et\",\"type\",\"closed\",\"name\",\"z_ohm\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "bus": "int64", + "element": "int64", + "et": "object", + "type": "object", + "closed": "bool", + "name": "object", + "z_ohm": "float64" + } + }, + "shunt": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"bus\",\"name\",\"q_mvar\",\"p_mw\",\"vn_kv\",\"step\",\"max_step\",\"in_service\"],\"index\":[0],\"data\":[[8,null,-19.0,0.0,20.0,1,1,true]]}", + "orient": "split", + "dtype": { + "bus": "uint32", + "name": "object", + "q_mvar": "float64", + "p_mw": "float64", + "vn_kv": "float64", + "step": "uint32", + "max_step": "uint32", + "in_service": "bool" + } + }, + "ext_grid": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"vm_pu\",\"va_degree\",\"in_service\",\"min_p_mw\",\"max_p_mw\",\"min_q_mvar\",\"max_q_mvar\"],\"index\":[0],\"data\":[[null,0,1.06,0.0,true,0.0,332.399999999999977,0.0,10.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "vm_pu": "float64", + "va_degree": "float64", + "in_service": "bool", + "min_p_mw": "float64", + "max_p_mw": "float64", + "min_q_mvar": "float64", + "max_q_mvar": "float64" + } + }, + "line": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"from_bus\",\"to_bus\",\"length_km\",\"r_ohm_per_km\",\"x_ohm_per_km\",\"c_nf_per_km\",\"g_us_per_km\",\"max_i_ka\",\"df\",\"parallel\",\"type\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14],\"data\":[[null,null,0,1,1.0,3.6907272,11.2683348,882.522683811391971,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,0,4,1.0,10.2894732,42.475737599999995,822.350682642433412,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,2,1.0,8.948775599999999,37.701406800000001,732.092680888995574,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,3,1.0,11.0664684,33.578380799999998,568.29112215127509,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,4,1.0,10.845558,33.1137072,578.319789012768069,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,2,3,1.0,12.761384400000001,32.570953199999998,213.94489304518595,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,3,4,1.0,2.542374,8.019428400000001,0.0,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,5,10,1.0,0.37992,0.7956,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,5,11,1.0,0.49164,1.02324,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,5,12,1.0,0.2646,0.52108,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,8,9,1.0,0.12724,0.338,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,8,13,1.0,0.50844,1.08152,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,9,10,1.0,0.3282,0.76828,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,11,12,1.0,0.88368,0.79952,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,12,13,1.0,0.68372,1.39208,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "length_km": "float64", + "r_ohm_per_km": "float64", + "x_ohm_per_km": "float64", + "c_nf_per_km": "float64", + "g_us_per_km": "float64", + "max_i_ka": "float64", + "df": "float64", + "parallel": "uint32", + "type": "object", + "in_service": "bool", + "max_loading_percent": "float64" + } + }, + "trafo": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,138.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.200000000000002,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,138.0,20.0,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.100000000000003,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,138.0,20.0,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.799999999999995,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,8,6,9900.0,20.0,14.0,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "hv_bus": "uint32", + "lv_bus": "uint32", + "sn_mva": "float64", + "vn_hv_kv": "float64", + "vn_lv_kv": "float64", + "vk_percent": "float64", + "vkr_percent": "float64", + "pfe_kw": "float64", + "i0_percent": "float64", + "shift_degree": "float64", + "tap_side": "object", + "tap_neutral": "float64", + "tap_min": "float64", + "tap_max": "float64", + "tap_step_percent": "float64", + "tap_step_degree": "float64", + "tap_pos": "float64", + "tap_phase_shifter": "bool", + "parallel": "uint32", + "df": "float64", + "in_service": "bool", + "max_loading_percent": "float64" + } + }, + "trafo3w": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "hv_bus": "uint32", + "mv_bus": "uint32", + "lv_bus": "uint32", + "sn_hv_mva": "float64", + "sn_mv_mva": "float64", + "sn_lv_mva": "float64", + "vn_hv_kv": "float64", + "vn_mv_kv": "float64", + "vn_lv_kv": "float64", + "vk_hv_percent": "float64", + "vk_mv_percent": "float64", + "vk_lv_percent": "float64", + "vkr_hv_percent": "float64", + "vkr_mv_percent": "float64", + "vkr_lv_percent": "float64", + "pfe_kw": "float64", + "i0_percent": "float64", + "shift_mv_degree": "float64", + "shift_lv_degree": "float64", + "tap_side": "object", + "tap_neutral": "int32", + "tap_min": "int32", + "tap_max": "int32", + "tap_step_percent": "float64", + "tap_step_degree": "float64", + "tap_pos": "int32", + "tap_at_star_point": "bool", + "in_service": "bool" + } + }, + "impedance": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"from_bus\",\"to_bus\",\"rft_pu\",\"xft_pu\",\"rtf_pu\",\"xtf_pu\",\"sn_mva\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "rft_pu": "float64", + "xft_pu": "float64", + "rtf_pu": "float64", + "xtf_pu": "float64", + "sn_mva": "float64", + "in_service": "bool" + } + }, + "dcline": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"from_bus\",\"to_bus\",\"p_mw\",\"loss_percent\",\"loss_mw\",\"vm_from_pu\",\"vm_to_pu\",\"max_p_mw\",\"min_q_from_mvar\",\"min_q_to_mvar\",\"max_q_from_mvar\",\"max_q_to_mvar\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "p_mw": "float64", + "loss_percent": "float64", + "loss_mw": "float64", + "vm_from_pu": "float64", + "vm_to_pu": "float64", + "max_p_mw": "float64", + "min_q_from_mvar": "float64", + "min_q_to_mvar": "float64", + "max_q_from_mvar": "float64", + "max_q_to_mvar": "float64", + "in_service": "bool" + } + }, + "ward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"ps_mw\",\"qs_mvar\",\"qz_mvar\",\"pz_mw\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "ps_mw": "float64", + "qs_mvar": "float64", + "qz_mvar": "float64", + "pz_mw": "float64", + "in_service": "bool" + } + }, + "xward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"ps_mw\",\"qs_mvar\",\"qz_mvar\",\"pz_mw\",\"r_ohm\",\"x_ohm\",\"vm_pu\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "ps_mw": "float64", + "qs_mvar": "float64", + "qz_mvar": "float64", + "pz_mw": "float64", + "r_ohm": "float64", + "x_ohm": "float64", + "vm_pu": "float64", + "in_service": "bool" + } + }, + "measurement": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"measurement_type\",\"element_type\",\"element\",\"value\",\"std_dev\",\"side\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "measurement_type": "object", + "element_type": "object", + "element": "uint32", + "value": "float64", + "std_dev": "float64", + "side": "object" + } + }, + "pwl_cost": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"power_type\",\"element\",\"et\",\"points\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "power_type": "object", + "element": "uint32", + "et": "object", + "points": "object" + } + }, + "poly_cost": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"element\",\"et\",\"cp0_eur\",\"cp1_eur_per_mw\",\"cp2_eur_per_mw2\",\"cq0_eur\",\"cq1_eur_per_mvar\",\"cq2_eur_per_mvar2\"],\"index\":[0,1,2,3,4],\"data\":[[0,\"ext_grid\",0.0,20.0,0.0430293,0.0,0.0,0.0],[0,\"gen\",0.0,20.0,0.25,0.0,0.0,0.0],[1,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0],[2,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0],[3,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0]]}", + "orient": "split", + "dtype": { + "element": "uint32", + "et": "object", + "cp0_eur": "float64", + "cp1_eur_per_mw": "float64", + "cp2_eur_per_mw2": "float64", + "cq0_eur": "float64", + "cq1_eur_per_mvar": "float64", + "cq2_eur_per_mvar2": "float64" + } + }, + "controller": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\",\"in_service\",\"order\",\"level\",\"recycle\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object", + "in_service": "bool", + "order": "float64", + "level": "object", + "recycle": "bool" + } + }, + "line_geodata": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"coords\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "coords": "object" + } + }, + "bus_geodata": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"x\",\"y\",\"coords\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "x": "float64", + "y": "float64", + "coords": "object" + } + }, + "version": "2.2.1", + "converged": false, + "name": "", + "f_hz": 50, + "sn_mva": 100.0, + "std_types": { + "line": { + "NAYY 4x50 SE": { + "c_nf_per_km": 210, + "r_ohm_per_km": 0.642, + "x_ohm_per_km": 0.083, + "max_i_ka": 0.142, + "type": "cs", + "q_mm2": 50, + "alpha": 0.00403 + }, + "NAYY 4x120 SE": { + "c_nf_per_km": 264, + "r_ohm_per_km": 0.225, + "x_ohm_per_km": 0.08, + "max_i_ka": 0.242, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NAYY 4x150 SE": { + "c_nf_per_km": 261, + "r_ohm_per_km": 0.208, + "x_ohm_per_km": 0.08, + "max_i_ka": 0.27, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x95 RM/25 12/20 kV": { + "c_nf_per_km": 216, + "r_ohm_per_km": 0.313, + "x_ohm_per_km": 0.132, + "max_i_ka": 0.252, + "type": "cs", + "q_mm2": 95, + "alpha": 0.00403 + }, + "NA2XS2Y 1x185 RM/25 12/20 kV": { + "c_nf_per_km": 273, + "r_ohm_per_km": 0.161, + "x_ohm_per_km": 0.117, + "max_i_ka": 0.362, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00403 + }, + "NA2XS2Y 1x240 RM/25 12/20 kV": { + "c_nf_per_km": 304, + "r_ohm_per_km": 0.122, + "x_ohm_per_km": 0.112, + "max_i_ka": 0.421, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00403 + }, + "NA2XS2Y 1x95 RM/25 6/10 kV": { + "c_nf_per_km": 315, + "r_ohm_per_km": 0.313, + "x_ohm_per_km": 0.123, + "max_i_ka": 0.249, + "type": "cs", + "q_mm2": 95, + "alpha": 0.00403 + }, + "NA2XS2Y 1x185 RM/25 6/10 kV": { + "c_nf_per_km": 406, + "r_ohm_per_km": 0.161, + "x_ohm_per_km": 0.11, + "max_i_ka": 0.358, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00403 + }, + "NA2XS2Y 1x240 RM/25 6/10 kV": { + "c_nf_per_km": 456, + "r_ohm_per_km": 0.122, + "x_ohm_per_km": 0.105, + "max_i_ka": 0.416, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00403 + }, + "NA2XS2Y 1x150 RM/25 12/20 kV": { + "c_nf_per_km": 250, + "r_ohm_per_km": 0.206, + "x_ohm_per_km": 0.116, + "max_i_ka": 0.319, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x120 RM/25 12/20 kV": { + "c_nf_per_km": 230, + "r_ohm_per_km": 0.253, + "x_ohm_per_km": 0.119, + "max_i_ka": 0.283, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NA2XS2Y 1x70 RM/25 12/20 kV": { + "c_nf_per_km": 190, + "r_ohm_per_km": 0.443, + "x_ohm_per_km": 0.132, + "max_i_ka": 0.22, + "type": "cs", + "q_mm2": 70, + "alpha": 0.00403 + }, + "NA2XS2Y 1x150 RM/25 6/10 kV": { + "c_nf_per_km": 360, + "r_ohm_per_km": 0.206, + "x_ohm_per_km": 0.11, + "max_i_ka": 0.315, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x120 RM/25 6/10 kV": { + "c_nf_per_km": 340, + "r_ohm_per_km": 0.253, + "x_ohm_per_km": 0.113, + "max_i_ka": 0.28, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NA2XS2Y 1x70 RM/25 6/10 kV": { + "c_nf_per_km": 280, + "r_ohm_per_km": 0.443, + "x_ohm_per_km": 0.123, + "max_i_ka": 0.217, + "type": "cs", + "q_mm2": 70, + "alpha": 0.00403 + }, + "N2XS(FL)2Y 1x120 RM/35 64/110 kV": { + "c_nf_per_km": 112, + "r_ohm_per_km": 0.153, + "x_ohm_per_km": 0.166, + "max_i_ka": 0.366, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x185 RM/35 64/110 kV": { + "c_nf_per_km": 125, + "r_ohm_per_km": 0.099, + "x_ohm_per_km": 0.156, + "max_i_ka": 0.457, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x240 RM/35 64/110 kV": { + "c_nf_per_km": 135, + "r_ohm_per_km": 0.075, + "x_ohm_per_km": 0.149, + "max_i_ka": 0.526, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x300 RM/35 64/110 kV": { + "c_nf_per_km": 144, + "r_ohm_per_km": 0.06, + "x_ohm_per_km": 0.144, + "max_i_ka": 0.588, + "type": "cs", + "q_mm2": 300, + "alpha": 0.00393 + }, + "15-AL1/3-ST1A 0.4": { + "c_nf_per_km": 11, + "r_ohm_per_km": 1.8769, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.105, + "type": "ol", + "q_mm2": 16, + "alpha": 0.00403 + }, + "24-AL1/4-ST1A 0.4": { + "c_nf_per_km": 11.25, + "r_ohm_per_km": 1.2012, + "x_ohm_per_km": 0.335, + "max_i_ka": 0.14, + "type": "ol", + "q_mm2": 24, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 0.4": { + "c_nf_per_km": 12.2, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.3, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 0.4": { + "c_nf_per_km": 13.2, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.29, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "34-AL1/6-ST1A 10.0": { + "c_nf_per_km": 9.7, + "r_ohm_per_km": 0.8342, + "x_ohm_per_km": 0.36, + "max_i_ka": 0.17, + "type": "ol", + "q_mm2": 34, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 10.0": { + "c_nf_per_km": 10.1, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 10.0": { + "c_nf_per_km": 10.4, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.339, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 10.0": { + "c_nf_per_km": 10.75, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.33, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 10.0": { + "c_nf_per_km": 11.1, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.323, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 10.0": { + "c_nf_per_km": 11.25, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.315, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "34-AL1/6-ST1A 20.0": { + "c_nf_per_km": 9.15, + "r_ohm_per_km": 0.8342, + "x_ohm_per_km": 0.382, + "max_i_ka": 0.17, + "type": "ol", + "q_mm2": 34, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 20.0": { + "c_nf_per_km": 9.5, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.372, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 20.0": { + "c_nf_per_km": 9.7, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.36, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 20.0": { + "c_nf_per_km": 10, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 20.0": { + "c_nf_per_km": 10.3, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.344, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 20.0": { + "c_nf_per_km": 10.5, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.337, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "184-AL1/30-ST1A 20.0": { + "c_nf_per_km": 10.75, + "r_ohm_per_km": 0.1571, + "x_ohm_per_km": 0.33, + "max_i_ka": 0.535, + "type": "ol", + "q_mm2": 184, + "alpha": 0.00403 + }, + "243-AL1/39-ST1A 20.0": { + "c_nf_per_km": 11, + "r_ohm_per_km": 0.1188, + "x_ohm_per_km": 0.32, + "max_i_ka": 0.645, + "type": "ol", + "q_mm2": 243, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 110.0": { + "c_nf_per_km": 8, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.46, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 110.0": { + "c_nf_per_km": 8.4, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.45, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 110.0": { + "c_nf_per_km": 8.65, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.44, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 110.0": { + "c_nf_per_km": 8.5, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.43, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 110.0": { + "c_nf_per_km": 8.75, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.41, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "184-AL1/30-ST1A 110.0": { + "c_nf_per_km": 8.8, + "r_ohm_per_km": 0.1571, + "x_ohm_per_km": 0.4, + "max_i_ka": 0.535, + "type": "ol", + "q_mm2": 184, + "alpha": 0.00403 + }, + "243-AL1/39-ST1A 110.0": { + "c_nf_per_km": 9, + "r_ohm_per_km": 0.1188, + "x_ohm_per_km": 0.39, + "max_i_ka": 0.645, + "type": "ol", + "q_mm2": 243, + "alpha": 0.00403 + }, + "305-AL1/39-ST1A 110.0": { + "c_nf_per_km": 9.2, + "r_ohm_per_km": 0.0949, + "x_ohm_per_km": 0.38, + "max_i_ka": 0.74, + "type": "ol", + "q_mm2": 305, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 110.0": { + "c_nf_per_km": 9.75, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.37, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 110.0": { + "c_nf_per_km": 9.95, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.36, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 220.0": { + "c_nf_per_km": 10, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.285, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 220.0": { + "c_nf_per_km": 11.7, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.275, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 380.0": { + "c_nf_per_km": 11, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.253, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 380.0": { + "c_nf_per_km": 14.6, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.25, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + } + }, + "trafo": { + "160 MVA 380/110 kV": { + "i0_percent": 0.06, + "pfe_kw": 60, + "vkr_percent": 0.25, + "sn_mva": 160, + "vn_lv_kv": 110.0, + "vn_hv_kv": 380.0, + "vk_percent": 12.2, + "shift_degree": 0, + "vector_group": "Yy0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "100 MVA 220/110 kV": { + "i0_percent": 0.06, + "pfe_kw": 55, + "vkr_percent": 0.26, + "sn_mva": 100, + "vn_lv_kv": 110.0, + "vn_hv_kv": 220.0, + "vk_percent": 12.0, + "shift_degree": 0, + "vector_group": "Yy0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "63 MVA 110/20 kV": { + "i0_percent": 0.04, + "pfe_kw": 22, + "vkr_percent": 0.32, + "sn_mva": 63, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 18, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "40 MVA 110/20 kV": { + "i0_percent": 0.05, + "pfe_kw": 18, + "vkr_percent": 0.34, + "sn_mva": 40, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 16.2, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "25 MVA 110/20 kV": { + "i0_percent": 0.07, + "pfe_kw": 14, + "vkr_percent": 0.41, + "sn_mva": 25, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 12, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "63 MVA 110/10 kV": { + "sn_mva": 63, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 18, + "vkr_percent": 0.32, + "pfe_kw": 22, + "i0_percent": 0.04, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "40 MVA 110/10 kV": { + "sn_mva": 40, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 16.2, + "vkr_percent": 0.34, + "pfe_kw": 18, + "i0_percent": 0.05, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "25 MVA 110/10 kV": { + "sn_mva": 25, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 12, + "vkr_percent": 0.41, + "pfe_kw": 14, + "i0_percent": 0.07, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "0.25 MVA 20/0.4 kV": { + "sn_mva": 0.25, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.44, + "pfe_kw": 0.8, + "i0_percent": 0.32, + "shift_degree": 150, + "vector_group": "Yzn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.4 MVA 20/0.4 kV": { + "sn_mva": 0.4, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.425, + "pfe_kw": 1.35, + "i0_percent": 0.3375, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.63 MVA 20/0.4 kV": { + "sn_mva": 0.63, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.206, + "pfe_kw": 1.65, + "i0_percent": 0.2619, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.25 MVA 10/0.4 kV": { + "sn_mva": 0.25, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.2, + "pfe_kw": 0.6, + "i0_percent": 0.24, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.4 MVA 10/0.4 kV": { + "sn_mva": 0.4, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.325, + "pfe_kw": 0.95, + "i0_percent": 0.2375, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.63 MVA 10/0.4 kV": { + "sn_mva": 0.63, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.0794, + "pfe_kw": 1.18, + "i0_percent": 0.1873, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + } + }, + "trafo3w": { + "63/25/38 MVA 110/20/10 kV": { + "sn_hv_mva": 63, + "sn_mv_mva": 25, + "sn_lv_mva": 38, + "vn_hv_kv": 110, + "vn_mv_kv": 20, + "vn_lv_kv": 10, + "vk_hv_percent": 10.4, + "vk_mv_percent": 10.4, + "vk_lv_percent": 10.4, + "vkr_hv_percent": 0.28, + "vkr_mv_percent": 0.32, + "vkr_lv_percent": 0.35, + "pfe_kw": 35, + "i0_percent": 0.89, + "shift_mv_degree": 0, + "shift_lv_degree": 0, + "vector_group": "YN0yn0yn0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -10, + "tap_max": 10, + "tap_step_percent": 1.2 + }, + "63/25/38 MVA 110/10/10 kV": { + "sn_hv_mva": 63, + "sn_mv_mva": 25, + "sn_lv_mva": 38, + "vn_hv_kv": 110, + "vn_mv_kv": 10, + "vn_lv_kv": 10, + "vk_hv_percent": 10.4, + "vk_mv_percent": 10.4, + "vk_lv_percent": 10.4, + "vkr_hv_percent": 0.28, + "vkr_mv_percent": 0.32, + "vkr_lv_percent": 0.35, + "pfe_kw": 35, + "i0_percent": 0.89, + "shift_mv_degree": 0, + "shift_lv_degree": 0, + "vector_group": "YN0yn0yn0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -10, + "tap_max": 10, + "tap_step_percent": 1.2 + } + } + }, + "res_bus": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"vm_pu\",\"va_degree\",\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "vm_pu": "float64", + "va_degree": "float64", + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_line": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"ql_mvar\",\"i_from_ka\",\"i_to_ka\",\"i_ka\",\"vm_from_pu\",\"va_from_degree\",\"vm_to_pu\",\"va_to_degree\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_from_ka": "float64", + "i_to_ka": "float64", + "i_ka": "float64", + "vm_from_pu": "float64", + "va_from_degree": "float64", + "vm_to_pu": "float64", + "va_to_degree": "float64", + "loading_percent": "float64" + } + }, + "res_trafo": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_hv_mw\",\"q_hv_mvar\",\"p_lv_mw\",\"q_lv_mvar\",\"pl_mw\",\"ql_mvar\",\"i_hv_ka\",\"i_lv_ka\",\"vm_hv_pu\",\"va_hv_degree\",\"vm_lv_pu\",\"va_lv_degree\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_hv_mw": "float64", + "q_hv_mvar": "float64", + "p_lv_mw": "float64", + "q_lv_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_hv_ka": "float64", + "i_lv_ka": "float64", + "vm_hv_pu": "float64", + "va_hv_degree": "float64", + "vm_lv_pu": "float64", + "va_lv_degree": "float64", + "loading_percent": "float64" + } + }, + "res_trafo3w": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_hv_mw\",\"q_hv_mvar\",\"p_mv_mw\",\"q_mv_mvar\",\"p_lv_mw\",\"q_lv_mvar\",\"pl_mw\",\"ql_mvar\",\"i_hv_ka\",\"i_mv_ka\",\"i_lv_ka\",\"vm_hv_pu\",\"va_hv_degree\",\"vm_mv_pu\",\"va_mv_degree\",\"vm_lv_pu\",\"va_lv_degree\",\"va_internal_degree\",\"vm_internal_pu\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_hv_mw": "float64", + "q_hv_mvar": "float64", + "p_mv_mw": "float64", + "q_mv_mvar": "float64", + "p_lv_mw": "float64", + "q_lv_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_hv_ka": "float64", + "i_mv_ka": "float64", + "i_lv_ka": "float64", + "vm_hv_pu": "float64", + "va_hv_degree": "float64", + "vm_mv_pu": "float64", + "va_mv_degree": "float64", + "vm_lv_pu": "float64", + "va_lv_degree": "float64", + "va_internal_degree": "float64", + "vm_internal_pu": "float64", + "loading_percent": "float64" + } + }, + "res_impedance": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"ql_mvar\",\"i_from_ka\",\"i_to_ka\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_from_ka": "float64", + "i_to_ka": "float64" + } + }, + "res_ext_grid": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_load": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_sgen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_storage": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_shunt": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64" + } + }, + "res_gen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"va_degree\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "va_degree": "float64", + "vm_pu": "float64" + } + }, + "res_ward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64" + } + }, + "res_xward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\",\"va_internal_degree\",\"vm_internal_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64", + "va_internal_degree": "float64", + "vm_internal_pu": "float64" + } + }, + "res_dcline": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"vm_from_pu\",\"va_from_degree\",\"vm_to_pu\",\"va_to_degree\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "vm_from_pu": "float64", + "va_from_degree": "float64", + "vm_to_pu": "float64", + "va_to_degree": "float64" + } + }, + "user_pf_options": {} + } +} diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/grid_layout.json b/input_data/generation/l2rpn_case14_sandbox_2x/grid_layout.json new file mode 100644 index 0000000..e153464 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/grid_layout.json @@ -0,0 +1,58 @@ +{ + "sub_0": [ + -280.0, + -81.0 + ], + "sub_1": [ + -100.0, + -270.0 + ], + "sub_2": [ + 366.0, + -270.0 + ], + "sub_3": [ + 366.0, + -54.0 + ], + "sub_4": [ + -64.0, + -54.0 + ], + "sub_5": [ + -64.0, + 54.0 + ], + "sub_6": [ + 450.0, + 0.0 + ], + "sub_7": [ + 550.0, + 0.0 + ], + "sub_8": [ + 326.0, + 54.0 + ], + "sub_9": [ + 222.0, + 108.0 + ], + "sub_10": [ + 79.0, + 162.0 + ], + "sub_11": [ + -170.0, + 270.0 + ], + "sub_12": [ + -64.0, + 270.0 + ], + "sub_13": [ + 222.0, + 216.0 + ] +} diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/loads_charac.csv b/input_data/generation/l2rpn_case14_sandbox_2x/loads_charac.csv new file mode 100644 index 0000000..cafe653 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/loads_charac.csv @@ -0,0 +1,13 @@ +Pmax,name,type,x,y +21.7,load_1_0,residential,180,10 +94.2,load_2_1,residential,646,10 +14.9,load_13_10,residential,646,226 +47.8,load_3_2,residential,216,226 +7.6,load_4_3,residential,216,334 +11.2,load_5_4,residential,606,334 +29.5,load_8_5,residential,502,388 +9.0,load_9_6,residential,359,442 +3.5,load_10_7,residential,128,550 +6.1,load_11_8,residential,216,550 +13.5,load_12_9,residential,502,496 + diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/params.json b/input_data/generation/l2rpn_case14_sandbox_2x/params.json new file mode 100644 index 0000000..183a084 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/params.json @@ -0,0 +1,4 @@ +{ + "dt": 5, + "planned_std": "0.01" +} diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/params_load.json b/input_data/generation/l2rpn_case14_sandbox_2x/params_load.json new file mode 100644 index 0000000..f40abf3 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/params_load.json @@ -0,0 +1,8 @@ +{ + "Lx": 1000, + "Ly": 1000, + "dx_corr": 250, + "dy_corr": 250, + "temperature_corr": 400, + "std_temperature_noise": 0.06 +} diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/params_loss.json b/input_data/generation/l2rpn_case14_sandbox_2x/params_loss.json new file mode 100644 index 0000000..717b866 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/params_loss.json @@ -0,0 +1 @@ +{"loss_pattern": "loss_pattern.csv"} \ No newline at end of file diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/params_opf.json b/input_data/generation/l2rpn_case14_sandbox_2x/params_opf.json new file mode 100644 index 0000000..94c2e38 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/params_opf.json @@ -0,0 +1 @@ +{"step_opf_min": 5, "mode_opf": "month", "reactive_comp": 1, "losses_pct": 0.4, "dispatch_by_carrier": false, "ramp_mode": "hard", "pyomo": false, "solver_name": "cbc", "idxSlack": 5, "nameSlack": "gen_0_5", "hydro_ramp_reduction_factor": 1, "slack_p_max_reduction": 30, "slack_ramp_max_reduction": 6, "loss_grid2op_simulation": true, "agent_type": "reco", "early_stopping_mode": false} diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/params_res.json b/input_data/generation/l2rpn_case14_sandbox_2x/params_res.json new file mode 100644 index 0000000..3542d3c --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/params_res.json @@ -0,0 +1,16 @@ +{ + "Lx": 1000, + "Ly": 1000, + "dx_corr": 250, + "dy_corr": 250, + "long_wind_corr": 5000, + "medium_wind_corr": 720, + "short_wind_corr": 120, + "solar_corr": 20, + "smoothdist": 0.001, + "std_solar_noise": 0.4, + "std_short_wind_noise": 0.1, + "std_medium_wind_noise": 0.15, + "std_long_wind_noise": 0.2, + "year_solar_pattern": 2007 +} diff --git a/input_data/generation/l2rpn_case14_sandbox_2x/prods_charac.csv b/input_data/generation/l2rpn_case14_sandbox_2x/prods_charac.csv new file mode 100644 index 0000000..84201c4 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_2x/prods_charac.csv @@ -0,0 +1,7 @@ +Pmax,Pmin,name,type,bus,max_ramp_up,max_ramp_down,min_up_time,min_down_time,marginal_cost,shut_down_cost,start_cost,x,y,V +140,0.0,gen_1_0,nuclear,1,5,5,96,96,40,10,20,180,10,142.1 +120,0.0,gen_2_1,thermal,2,10,10,4,4,70,1,2,646,10,142.1 +40,0.0,gen_5_2,wind,5,0,0,0,0,0,0,0,216,334,22.0 +40,0.0,gen_5_3,solar,5,0,0,0,0,0,0,0,216,334,22.0 +30,0.0,gen_7_4,solar,7,0,0,0,0,0,0,0,718,280,13.2 +100,0.0,gen_0_5,hydro,0,15,15,4,4,70,1,2,0,199,142.1 diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/config.py b/input_data/generation/l2rpn_case14_sandbox_3x/config.py new file mode 100644 index 0000000..920d8d1 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/config.py @@ -0,0 +1,40 @@ +from grid2op.Action import TopologyAndDispatchAction +from grid2op.Reward import RedispReward +from grid2op.Rules import DefaultRules +from grid2op.Chronics import Multifolder +from grid2op.Chronics import GridStateFromFileWithForecasts +from grid2op.Backend import PandaPowerBackend + +config = { + "backend": PandaPowerBackend, + "action_class": TopologyAndDispatchAction, + "observation_class": None, + "reward_class": RedispReward, + "gamerules_class": DefaultRules, + "chronics_class": Multifolder, + "grid_value_class": GridStateFromFileWithForecasts, + "volagecontroler_class": None, + "thermal_limits": [ + 541., + 450., + 375., + 636., + 175., + 285., + 335., + 657., + 496., + 827., + 442., + 641., + 840., + 156., + 664., + 235., + 119., + 179., + 1986., + 1572. + ], + "names_chronics_to_grid": None +} diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/grid.json b/input_data/generation/l2rpn_case14_sandbox_3x/grid.json new file mode 100644 index 0000000..c118ea3 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/grid.json @@ -0,0 +1,1363 @@ +{ + "_module": "pandapower.auxiliary", + "_class": "pandapowerNet", + "_object": { + "bus": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"vn_kv\",\"type\",\"zone\",\"in_service\",\"min_vm_pu\",\"max_vm_pu\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[1,138.0,\"b\",1.0,true,0.94,1.06],[2,138.0,\"b\",1.0,true,0.94,1.06],[3,138.0,\"b\",1.0,true,0.94,1.06],[4,138.0,\"b\",1.0,true,0.94,1.06],[5,138.0,\"b\",1.0,true,0.94,1.06],[6,20.0,\"b\",1.0,true,0.94,1.06],[7,14.0,\"b\",1.0,true,0.94,1.06],[8,12.0,\"b\",1.0,true,0.94,1.06],[9,20.0,\"b\",1.0,true,0.94,1.06],[10,20.0,\"b\",1.0,true,0.94,1.06],[11,20.0,\"b\",1.0,true,0.94,1.06],[12,20.0,\"b\",1.0,true,0.94,1.06],[13,20.0,\"b\",1.0,true,0.94,1.06],[14,20.0,\"b\",1.0,true,0.94,1.06]]}", + "orient": "split", + "dtype": { + "name": "object", + "vn_kv": "float64", + "type": "object", + "zone": "object", + "in_service": "bool", + "min_vm_pu": "float64", + "max_vm_pu": "float64" + } + }, + "load": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"const_z_percent\",\"const_i_percent\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"controllable\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10],\"data\":[[null,1,21.699999999999999,12.699999999999999,0.0,0.0,null,1.0,true,null,false],[null,2,94.200000000000003,19.0,0.0,0.0,null,1.0,true,null,false],[null,3,47.799999999999997,-3.9,0.0,0.0,null,1.0,true,null,false],[null,4,7.6,1.6,0.0,0.0,null,1.0,true,null,false],[null,5,11.199999999999999,7.5,0.0,0.0,null,1.0,true,null,false],[null,8,29.5,16.600000000000001,0.0,0.0,null,1.0,true,null,false],[null,9,9.0,5.8,0.0,0.0,null,1.0,true,null,false],[null,10,3.5,1.8,0.0,0.0,null,1.0,true,null,false],[null,11,6.1,1.6,0.0,0.0,null,1.0,true,null,false],[null,12,13.5,5.8,0.0,0.0,null,1.0,true,null,false],[null,13,14.9,5.0,0.0,0.0,null,1.0,true,null,false]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "p_mw": "float64", + "q_mvar": "float64", + "const_z_percent": "float64", + "const_i_percent": "float64", + "sn_mva": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object", + "controllable": "object" + } + }, + "sgen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"sn_mva\",\"scaling\",\"in_service\",\"type\",\"current_source\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "int64", + "p_mw": "float64", + "q_mvar": "float64", + "sn_mva": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object", + "current_source": "bool" + } + }, + "storage": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"q_mvar\",\"sn_mva\",\"soc_percent\",\"min_e_mwh\",\"max_e_mwh\",\"scaling\",\"in_service\",\"type\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "int64", + "p_mw": "float64", + "q_mvar": "float64", + "sn_mva": "float64", + "soc_percent": "float64", + "min_e_mwh": "float64", + "max_e_mwh": "float64", + "scaling": "float64", + "in_service": "bool", + "type": "object" + } + }, + "gen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"p_mw\",\"vm_pu\",\"sn_mva\",\"min_q_mvar\",\"max_q_mvar\",\"scaling\",\"slack\",\"in_service\",\"type\",\"controllable\",\"min_p_mw\",\"max_p_mw\"],\"index\":[0,1,2,3,4],\"data\":[[null,1,40.0,1.045,null,-40.0,50.0,1.0,false,true,null,true,0.0,140.0],[null,2,0.0,1.01,null,0.0,40.0,1.0,false,true,null,true,0.0,100.0],[null,5,0.0,1.07,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0],[null,5,0.0,1.07,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0],[null,7,0.0,1.09,null,-6.0,24.0,1.0,false,true,null,true,0.0,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "p_mw": "float64", + "vm_pu": "float64", + "sn_mva": "float64", + "min_q_mvar": "float64", + "max_q_mvar": "float64", + "scaling": "float64", + "slack": "bool", + "in_service": "bool", + "type": "object", + "controllable": "bool", + "min_p_mw": "float64", + "max_p_mw": "float64" + } + }, + "switch": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"bus\",\"element\",\"et\",\"type\",\"closed\",\"name\",\"z_ohm\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "bus": "int64", + "element": "int64", + "et": "object", + "type": "object", + "closed": "bool", + "name": "object", + "z_ohm": "float64" + } + }, + "shunt": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"bus\",\"name\",\"q_mvar\",\"p_mw\",\"vn_kv\",\"step\",\"max_step\",\"in_service\"],\"index\":[0],\"data\":[[8,null,-19.0,0.0,20.0,1,1,true]]}", + "orient": "split", + "dtype": { + "bus": "uint32", + "name": "object", + "q_mvar": "float64", + "p_mw": "float64", + "vn_kv": "float64", + "step": "uint32", + "max_step": "uint32", + "in_service": "bool" + } + }, + "ext_grid": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"vm_pu\",\"va_degree\",\"in_service\",\"min_p_mw\",\"max_p_mw\",\"min_q_mvar\",\"max_q_mvar\"],\"index\":[0],\"data\":[[null,0,1.06,0.0,true,0.0,332.399999999999977,0.0,10.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "vm_pu": "float64", + "va_degree": "float64", + "in_service": "bool", + "min_p_mw": "float64", + "max_p_mw": "float64", + "min_q_mvar": "float64", + "max_q_mvar": "float64" + } + }, + "line": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"from_bus\",\"to_bus\",\"length_km\",\"r_ohm_per_km\",\"x_ohm_per_km\",\"c_nf_per_km\",\"g_us_per_km\",\"max_i_ka\",\"df\",\"parallel\",\"type\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14],\"data\":[[null,null,0,1,1.0,3.6907272,11.2683348,882.522683811391971,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,0,4,1.0,10.2894732,42.475737599999995,822.350682642433412,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,2,1.0,8.948775599999999,37.701406800000001,732.092680888995574,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,3,1.0,11.0664684,33.578380799999998,568.29112215127509,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,1,4,1.0,10.845558,33.1137072,578.319789012768069,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,2,3,1.0,12.761384400000001,32.570953199999998,213.94489304518595,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,3,4,1.0,2.542374,8.019428400000001,0.0,0.0,41.418606267951418,1.0,1,\"ol\",true,100.0],[null,null,5,10,1.0,0.37992,0.7956,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,5,11,1.0,0.49164,1.02324,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,5,12,1.0,0.2646,0.52108,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,8,9,1.0,0.12724,0.338,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,8,13,1.0,0.50844,1.08152,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,9,10,1.0,0.3282,0.76828,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,11,12,1.0,0.88368,0.79952,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0],[null,null,12,13,1.0,0.68372,1.39208,0.0,0.0,285.788383248864761,1.0,1,\"ol\",true,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "length_km": "float64", + "r_ohm_per_km": "float64", + "x_ohm_per_km": "float64", + "c_nf_per_km": "float64", + "g_us_per_km": "float64", + "max_i_ka": "float64", + "df": "float64", + "parallel": "uint32", + "type": "object", + "in_service": "bool", + "max_loading_percent": "float64" + } + }, + "trafo": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"lv_bus\",\"sn_mva\",\"vn_hv_kv\",\"vn_lv_kv\",\"vk_percent\",\"vkr_percent\",\"pfe_kw\",\"i0_percent\",\"shift_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_phase_shifter\",\"parallel\",\"df\",\"in_service\",\"max_loading_percent\"],\"index\":[0,1,2,3,4],\"data\":[[null,null,3,6,9900.0,138.0,14.0,2070.288000000000011,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,2.200000000000002,null,-1.0,false,1,1.0,true,100.0],[null,null,3,8,9900.0,138.0,20.0,5506.181999999999789,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,3.100000000000003,null,-1.0,false,1,1.0,true,100.0],[null,null,4,5,9900.0,138.0,20.0,2494.998000000000047,0.0,0.0,0.0,0.0,\"hv\",0.0,null,null,6.799999999999995,null,-1.0,false,1,1.0,true,100.0],[null,null,6,7,9900.0,14.0,12.0,1743.884999999999991,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0],[null,null,8,6,9900.0,20.0,14.0,1089.098999999999933,0.0,0.0,0.0,0.0,null,null,null,null,null,null,null,false,1,1.0,true,100.0]]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "hv_bus": "uint32", + "lv_bus": "uint32", + "sn_mva": "float64", + "vn_hv_kv": "float64", + "vn_lv_kv": "float64", + "vk_percent": "float64", + "vkr_percent": "float64", + "pfe_kw": "float64", + "i0_percent": "float64", + "shift_degree": "float64", + "tap_side": "object", + "tap_neutral": "float64", + "tap_min": "float64", + "tap_max": "float64", + "tap_step_percent": "float64", + "tap_step_degree": "float64", + "tap_pos": "float64", + "tap_phase_shifter": "bool", + "parallel": "uint32", + "df": "float64", + "in_service": "bool", + "max_loading_percent": "float64" + } + }, + "trafo3w": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"std_type\",\"hv_bus\",\"mv_bus\",\"lv_bus\",\"sn_hv_mva\",\"sn_mv_mva\",\"sn_lv_mva\",\"vn_hv_kv\",\"vn_mv_kv\",\"vn_lv_kv\",\"vk_hv_percent\",\"vk_mv_percent\",\"vk_lv_percent\",\"vkr_hv_percent\",\"vkr_mv_percent\",\"vkr_lv_percent\",\"pfe_kw\",\"i0_percent\",\"shift_mv_degree\",\"shift_lv_degree\",\"tap_side\",\"tap_neutral\",\"tap_min\",\"tap_max\",\"tap_step_percent\",\"tap_step_degree\",\"tap_pos\",\"tap_at_star_point\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "std_type": "object", + "hv_bus": "uint32", + "mv_bus": "uint32", + "lv_bus": "uint32", + "sn_hv_mva": "float64", + "sn_mv_mva": "float64", + "sn_lv_mva": "float64", + "vn_hv_kv": "float64", + "vn_mv_kv": "float64", + "vn_lv_kv": "float64", + "vk_hv_percent": "float64", + "vk_mv_percent": "float64", + "vk_lv_percent": "float64", + "vkr_hv_percent": "float64", + "vkr_mv_percent": "float64", + "vkr_lv_percent": "float64", + "pfe_kw": "float64", + "i0_percent": "float64", + "shift_mv_degree": "float64", + "shift_lv_degree": "float64", + "tap_side": "object", + "tap_neutral": "int32", + "tap_min": "int32", + "tap_max": "int32", + "tap_step_percent": "float64", + "tap_step_degree": "float64", + "tap_pos": "int32", + "tap_at_star_point": "bool", + "in_service": "bool" + } + }, + "impedance": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"from_bus\",\"to_bus\",\"rft_pu\",\"xft_pu\",\"rtf_pu\",\"xtf_pu\",\"sn_mva\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "rft_pu": "float64", + "xft_pu": "float64", + "rtf_pu": "float64", + "xtf_pu": "float64", + "sn_mva": "float64", + "in_service": "bool" + } + }, + "dcline": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"from_bus\",\"to_bus\",\"p_mw\",\"loss_percent\",\"loss_mw\",\"vm_from_pu\",\"vm_to_pu\",\"max_p_mw\",\"min_q_from_mvar\",\"min_q_to_mvar\",\"max_q_from_mvar\",\"max_q_to_mvar\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "from_bus": "uint32", + "to_bus": "uint32", + "p_mw": "float64", + "loss_percent": "float64", + "loss_mw": "float64", + "vm_from_pu": "float64", + "vm_to_pu": "float64", + "max_p_mw": "float64", + "min_q_from_mvar": "float64", + "min_q_to_mvar": "float64", + "max_q_from_mvar": "float64", + "max_q_to_mvar": "float64", + "in_service": "bool" + } + }, + "ward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"ps_mw\",\"qs_mvar\",\"qz_mvar\",\"pz_mw\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "ps_mw": "float64", + "qs_mvar": "float64", + "qz_mvar": "float64", + "pz_mw": "float64", + "in_service": "bool" + } + }, + "xward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"bus\",\"ps_mw\",\"qs_mvar\",\"qz_mvar\",\"pz_mw\",\"r_ohm\",\"x_ohm\",\"vm_pu\",\"in_service\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "bus": "uint32", + "ps_mw": "float64", + "qs_mvar": "float64", + "qz_mvar": "float64", + "pz_mw": "float64", + "r_ohm": "float64", + "x_ohm": "float64", + "vm_pu": "float64", + "in_service": "bool" + } + }, + "measurement": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"name\",\"measurement_type\",\"element_type\",\"element\",\"value\",\"std_dev\",\"side\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "name": "object", + "measurement_type": "object", + "element_type": "object", + "element": "uint32", + "value": "float64", + "std_dev": "float64", + "side": "object" + } + }, + "pwl_cost": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"power_type\",\"element\",\"et\",\"points\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "power_type": "object", + "element": "uint32", + "et": "object", + "points": "object" + } + }, + "poly_cost": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"element\",\"et\",\"cp0_eur\",\"cp1_eur_per_mw\",\"cp2_eur_per_mw2\",\"cq0_eur\",\"cq1_eur_per_mvar\",\"cq2_eur_per_mvar2\"],\"index\":[0,1,2,3,4],\"data\":[[0,\"ext_grid\",0.0,20.0,0.0430293,0.0,0.0,0.0],[0,\"gen\",0.0,20.0,0.25,0.0,0.0,0.0],[1,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0],[2,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0],[3,\"gen\",0.0,40.0,0.01,0.0,0.0,0.0]]}", + "orient": "split", + "dtype": { + "element": "uint32", + "et": "object", + "cp0_eur": "float64", + "cp1_eur_per_mw": "float64", + "cp2_eur_per_mw2": "float64", + "cq0_eur": "float64", + "cq1_eur_per_mvar": "float64", + "cq2_eur_per_mvar2": "float64" + } + }, + "controller": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"object\",\"in_service\",\"order\",\"level\",\"recycle\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "object": "object", + "in_service": "bool", + "order": "float64", + "level": "object", + "recycle": "bool" + } + }, + "line_geodata": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"coords\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "coords": "object" + } + }, + "bus_geodata": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"x\",\"y\",\"coords\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "x": "float64", + "y": "float64", + "coords": "object" + } + }, + "version": "2.2.1", + "converged": false, + "name": "", + "f_hz": 50, + "sn_mva": 100.0, + "std_types": { + "line": { + "NAYY 4x50 SE": { + "c_nf_per_km": 210, + "r_ohm_per_km": 0.642, + "x_ohm_per_km": 0.083, + "max_i_ka": 0.142, + "type": "cs", + "q_mm2": 50, + "alpha": 0.00403 + }, + "NAYY 4x120 SE": { + "c_nf_per_km": 264, + "r_ohm_per_km": 0.225, + "x_ohm_per_km": 0.08, + "max_i_ka": 0.242, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NAYY 4x150 SE": { + "c_nf_per_km": 261, + "r_ohm_per_km": 0.208, + "x_ohm_per_km": 0.08, + "max_i_ka": 0.27, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x95 RM/25 12/20 kV": { + "c_nf_per_km": 216, + "r_ohm_per_km": 0.313, + "x_ohm_per_km": 0.132, + "max_i_ka": 0.252, + "type": "cs", + "q_mm2": 95, + "alpha": 0.00403 + }, + "NA2XS2Y 1x185 RM/25 12/20 kV": { + "c_nf_per_km": 273, + "r_ohm_per_km": 0.161, + "x_ohm_per_km": 0.117, + "max_i_ka": 0.362, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00403 + }, + "NA2XS2Y 1x240 RM/25 12/20 kV": { + "c_nf_per_km": 304, + "r_ohm_per_km": 0.122, + "x_ohm_per_km": 0.112, + "max_i_ka": 0.421, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00403 + }, + "NA2XS2Y 1x95 RM/25 6/10 kV": { + "c_nf_per_km": 315, + "r_ohm_per_km": 0.313, + "x_ohm_per_km": 0.123, + "max_i_ka": 0.249, + "type": "cs", + "q_mm2": 95, + "alpha": 0.00403 + }, + "NA2XS2Y 1x185 RM/25 6/10 kV": { + "c_nf_per_km": 406, + "r_ohm_per_km": 0.161, + "x_ohm_per_km": 0.11, + "max_i_ka": 0.358, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00403 + }, + "NA2XS2Y 1x240 RM/25 6/10 kV": { + "c_nf_per_km": 456, + "r_ohm_per_km": 0.122, + "x_ohm_per_km": 0.105, + "max_i_ka": 0.416, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00403 + }, + "NA2XS2Y 1x150 RM/25 12/20 kV": { + "c_nf_per_km": 250, + "r_ohm_per_km": 0.206, + "x_ohm_per_km": 0.116, + "max_i_ka": 0.319, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x120 RM/25 12/20 kV": { + "c_nf_per_km": 230, + "r_ohm_per_km": 0.253, + "x_ohm_per_km": 0.119, + "max_i_ka": 0.283, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NA2XS2Y 1x70 RM/25 12/20 kV": { + "c_nf_per_km": 190, + "r_ohm_per_km": 0.443, + "x_ohm_per_km": 0.132, + "max_i_ka": 0.22, + "type": "cs", + "q_mm2": 70, + "alpha": 0.00403 + }, + "NA2XS2Y 1x150 RM/25 6/10 kV": { + "c_nf_per_km": 360, + "r_ohm_per_km": 0.206, + "x_ohm_per_km": 0.11, + "max_i_ka": 0.315, + "type": "cs", + "q_mm2": 150, + "alpha": 0.00403 + }, + "NA2XS2Y 1x120 RM/25 6/10 kV": { + "c_nf_per_km": 340, + "r_ohm_per_km": 0.253, + "x_ohm_per_km": 0.113, + "max_i_ka": 0.28, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00403 + }, + "NA2XS2Y 1x70 RM/25 6/10 kV": { + "c_nf_per_km": 280, + "r_ohm_per_km": 0.443, + "x_ohm_per_km": 0.123, + "max_i_ka": 0.217, + "type": "cs", + "q_mm2": 70, + "alpha": 0.00403 + }, + "N2XS(FL)2Y 1x120 RM/35 64/110 kV": { + "c_nf_per_km": 112, + "r_ohm_per_km": 0.153, + "x_ohm_per_km": 0.166, + "max_i_ka": 0.366, + "type": "cs", + "q_mm2": 120, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x185 RM/35 64/110 kV": { + "c_nf_per_km": 125, + "r_ohm_per_km": 0.099, + "x_ohm_per_km": 0.156, + "max_i_ka": 0.457, + "type": "cs", + "q_mm2": 185, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x240 RM/35 64/110 kV": { + "c_nf_per_km": 135, + "r_ohm_per_km": 0.075, + "x_ohm_per_km": 0.149, + "max_i_ka": 0.526, + "type": "cs", + "q_mm2": 240, + "alpha": 0.00393 + }, + "N2XS(FL)2Y 1x300 RM/35 64/110 kV": { + "c_nf_per_km": 144, + "r_ohm_per_km": 0.06, + "x_ohm_per_km": 0.144, + "max_i_ka": 0.588, + "type": "cs", + "q_mm2": 300, + "alpha": 0.00393 + }, + "15-AL1/3-ST1A 0.4": { + "c_nf_per_km": 11, + "r_ohm_per_km": 1.8769, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.105, + "type": "ol", + "q_mm2": 16, + "alpha": 0.00403 + }, + "24-AL1/4-ST1A 0.4": { + "c_nf_per_km": 11.25, + "r_ohm_per_km": 1.2012, + "x_ohm_per_km": 0.335, + "max_i_ka": 0.14, + "type": "ol", + "q_mm2": 24, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 0.4": { + "c_nf_per_km": 12.2, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.3, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 0.4": { + "c_nf_per_km": 13.2, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.29, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "34-AL1/6-ST1A 10.0": { + "c_nf_per_km": 9.7, + "r_ohm_per_km": 0.8342, + "x_ohm_per_km": 0.36, + "max_i_ka": 0.17, + "type": "ol", + "q_mm2": 34, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 10.0": { + "c_nf_per_km": 10.1, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 10.0": { + "c_nf_per_km": 10.4, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.339, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 10.0": { + "c_nf_per_km": 10.75, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.33, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 10.0": { + "c_nf_per_km": 11.1, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.323, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 10.0": { + "c_nf_per_km": 11.25, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.315, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "34-AL1/6-ST1A 20.0": { + "c_nf_per_km": 9.15, + "r_ohm_per_km": 0.8342, + "x_ohm_per_km": 0.382, + "max_i_ka": 0.17, + "type": "ol", + "q_mm2": 34, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 20.0": { + "c_nf_per_km": 9.5, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.372, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 20.0": { + "c_nf_per_km": 9.7, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.36, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 20.0": { + "c_nf_per_km": 10, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.35, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 20.0": { + "c_nf_per_km": 10.3, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.344, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 20.0": { + "c_nf_per_km": 10.5, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.337, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "184-AL1/30-ST1A 20.0": { + "c_nf_per_km": 10.75, + "r_ohm_per_km": 0.1571, + "x_ohm_per_km": 0.33, + "max_i_ka": 0.535, + "type": "ol", + "q_mm2": 184, + "alpha": 0.00403 + }, + "243-AL1/39-ST1A 20.0": { + "c_nf_per_km": 11, + "r_ohm_per_km": 0.1188, + "x_ohm_per_km": 0.32, + "max_i_ka": 0.645, + "type": "ol", + "q_mm2": 243, + "alpha": 0.00403 + }, + "48-AL1/8-ST1A 110.0": { + "c_nf_per_km": 8, + "r_ohm_per_km": 0.5939, + "x_ohm_per_km": 0.46, + "max_i_ka": 0.21, + "type": "ol", + "q_mm2": 48, + "alpha": 0.00403 + }, + "70-AL1/11-ST1A 110.0": { + "c_nf_per_km": 8.4, + "r_ohm_per_km": 0.4132, + "x_ohm_per_km": 0.45, + "max_i_ka": 0.29, + "type": "ol", + "q_mm2": 70, + "alpha": 0.00403 + }, + "94-AL1/15-ST1A 110.0": { + "c_nf_per_km": 8.65, + "r_ohm_per_km": 0.306, + "x_ohm_per_km": 0.44, + "max_i_ka": 0.35, + "type": "ol", + "q_mm2": 94, + "alpha": 0.00403 + }, + "122-AL1/20-ST1A 110.0": { + "c_nf_per_km": 8.5, + "r_ohm_per_km": 0.2376, + "x_ohm_per_km": 0.43, + "max_i_ka": 0.41, + "type": "ol", + "q_mm2": 122, + "alpha": 0.00403 + }, + "149-AL1/24-ST1A 110.0": { + "c_nf_per_km": 8.75, + "r_ohm_per_km": 0.194, + "x_ohm_per_km": 0.41, + "max_i_ka": 0.47, + "type": "ol", + "q_mm2": 149, + "alpha": 0.00403 + }, + "184-AL1/30-ST1A 110.0": { + "c_nf_per_km": 8.8, + "r_ohm_per_km": 0.1571, + "x_ohm_per_km": 0.4, + "max_i_ka": 0.535, + "type": "ol", + "q_mm2": 184, + "alpha": 0.00403 + }, + "243-AL1/39-ST1A 110.0": { + "c_nf_per_km": 9, + "r_ohm_per_km": 0.1188, + "x_ohm_per_km": 0.39, + "max_i_ka": 0.645, + "type": "ol", + "q_mm2": 243, + "alpha": 0.00403 + }, + "305-AL1/39-ST1A 110.0": { + "c_nf_per_km": 9.2, + "r_ohm_per_km": 0.0949, + "x_ohm_per_km": 0.38, + "max_i_ka": 0.74, + "type": "ol", + "q_mm2": 305, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 110.0": { + "c_nf_per_km": 9.75, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.37, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 110.0": { + "c_nf_per_km": 9.95, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.36, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 220.0": { + "c_nf_per_km": 10, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.285, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 220.0": { + "c_nf_per_km": 11.7, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.275, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + }, + "490-AL1/64-ST1A 380.0": { + "c_nf_per_km": 11, + "r_ohm_per_km": 0.059, + "x_ohm_per_km": 0.253, + "max_i_ka": 0.96, + "type": "ol", + "q_mm2": 490, + "alpha": 0.00403 + }, + "679-AL1/86-ST1A 380.0": { + "c_nf_per_km": 14.6, + "r_ohm_per_km": 0.042, + "x_ohm_per_km": 0.25, + "max_i_ka": 1.15, + "type": "ol", + "q_mm2": 679, + "alpha": 0.00403 + } + }, + "trafo": { + "160 MVA 380/110 kV": { + "i0_percent": 0.06, + "pfe_kw": 60, + "vkr_percent": 0.25, + "sn_mva": 160, + "vn_lv_kv": 110.0, + "vn_hv_kv": 380.0, + "vk_percent": 12.2, + "shift_degree": 0, + "vector_group": "Yy0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "100 MVA 220/110 kV": { + "i0_percent": 0.06, + "pfe_kw": 55, + "vkr_percent": 0.26, + "sn_mva": 100, + "vn_lv_kv": 110.0, + "vn_hv_kv": 220.0, + "vk_percent": 12.0, + "shift_degree": 0, + "vector_group": "Yy0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "63 MVA 110/20 kV": { + "i0_percent": 0.04, + "pfe_kw": 22, + "vkr_percent": 0.32, + "sn_mva": 63, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 18, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "40 MVA 110/20 kV": { + "i0_percent": 0.05, + "pfe_kw": 18, + "vkr_percent": 0.34, + "sn_mva": 40, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 16.2, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "25 MVA 110/20 kV": { + "i0_percent": 0.07, + "pfe_kw": 14, + "vkr_percent": 0.41, + "sn_mva": 25, + "vn_lv_kv": 20.0, + "vn_hv_kv": 110.0, + "vk_percent": 12, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "63 MVA 110/10 kV": { + "sn_mva": 63, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 18, + "vkr_percent": 0.32, + "pfe_kw": 22, + "i0_percent": 0.04, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "40 MVA 110/10 kV": { + "sn_mva": 40, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 16.2, + "vkr_percent": 0.34, + "pfe_kw": 18, + "i0_percent": 0.05, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "25 MVA 110/10 kV": { + "sn_mva": 25, + "vn_hv_kv": 110, + "vn_lv_kv": 10, + "vk_percent": 12, + "vkr_percent": 0.41, + "pfe_kw": 14, + "i0_percent": 0.07, + "shift_degree": 150, + "vector_group": "YNd5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -9, + "tap_max": 9, + "tap_step_degree": 0, + "tap_step_percent": 1.5, + "tap_phase_shifter": false + }, + "0.25 MVA 20/0.4 kV": { + "sn_mva": 0.25, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.44, + "pfe_kw": 0.8, + "i0_percent": 0.32, + "shift_degree": 150, + "vector_group": "Yzn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.4 MVA 20/0.4 kV": { + "sn_mva": 0.4, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.425, + "pfe_kw": 1.35, + "i0_percent": 0.3375, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.63 MVA 20/0.4 kV": { + "sn_mva": 0.63, + "vn_hv_kv": 20, + "vn_lv_kv": 0.4, + "vk_percent": 6, + "vkr_percent": 1.206, + "pfe_kw": 1.65, + "i0_percent": 0.2619, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.25 MVA 10/0.4 kV": { + "sn_mva": 0.25, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.2, + "pfe_kw": 0.6, + "i0_percent": 0.24, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.4 MVA 10/0.4 kV": { + "sn_mva": 0.4, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.325, + "pfe_kw": 0.95, + "i0_percent": 0.2375, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + }, + "0.63 MVA 10/0.4 kV": { + "sn_mva": 0.63, + "vn_hv_kv": 10, + "vn_lv_kv": 0.4, + "vk_percent": 4, + "vkr_percent": 1.0794, + "pfe_kw": 1.18, + "i0_percent": 0.1873, + "shift_degree": 150, + "vector_group": "Dyn5", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -2, + "tap_max": 2, + "tap_step_degree": 0, + "tap_step_percent": 2.5, + "tap_phase_shifter": false + } + }, + "trafo3w": { + "63/25/38 MVA 110/20/10 kV": { + "sn_hv_mva": 63, + "sn_mv_mva": 25, + "sn_lv_mva": 38, + "vn_hv_kv": 110, + "vn_mv_kv": 20, + "vn_lv_kv": 10, + "vk_hv_percent": 10.4, + "vk_mv_percent": 10.4, + "vk_lv_percent": 10.4, + "vkr_hv_percent": 0.28, + "vkr_mv_percent": 0.32, + "vkr_lv_percent": 0.35, + "pfe_kw": 35, + "i0_percent": 0.89, + "shift_mv_degree": 0, + "shift_lv_degree": 0, + "vector_group": "YN0yn0yn0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -10, + "tap_max": 10, + "tap_step_percent": 1.2 + }, + "63/25/38 MVA 110/10/10 kV": { + "sn_hv_mva": 63, + "sn_mv_mva": 25, + "sn_lv_mva": 38, + "vn_hv_kv": 110, + "vn_mv_kv": 10, + "vn_lv_kv": 10, + "vk_hv_percent": 10.4, + "vk_mv_percent": 10.4, + "vk_lv_percent": 10.4, + "vkr_hv_percent": 0.28, + "vkr_mv_percent": 0.32, + "vkr_lv_percent": 0.35, + "pfe_kw": 35, + "i0_percent": 0.89, + "shift_mv_degree": 0, + "shift_lv_degree": 0, + "vector_group": "YN0yn0yn0", + "tap_side": "hv", + "tap_neutral": 0, + "tap_min": -10, + "tap_max": 10, + "tap_step_percent": 1.2 + } + } + }, + "res_bus": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"vm_pu\",\"va_degree\",\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "vm_pu": "float64", + "va_degree": "float64", + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_line": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"ql_mvar\",\"i_from_ka\",\"i_to_ka\",\"i_ka\",\"vm_from_pu\",\"va_from_degree\",\"vm_to_pu\",\"va_to_degree\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_from_ka": "float64", + "i_to_ka": "float64", + "i_ka": "float64", + "vm_from_pu": "float64", + "va_from_degree": "float64", + "vm_to_pu": "float64", + "va_to_degree": "float64", + "loading_percent": "float64" + } + }, + "res_trafo": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_hv_mw\",\"q_hv_mvar\",\"p_lv_mw\",\"q_lv_mvar\",\"pl_mw\",\"ql_mvar\",\"i_hv_ka\",\"i_lv_ka\",\"vm_hv_pu\",\"va_hv_degree\",\"vm_lv_pu\",\"va_lv_degree\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_hv_mw": "float64", + "q_hv_mvar": "float64", + "p_lv_mw": "float64", + "q_lv_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_hv_ka": "float64", + "i_lv_ka": "float64", + "vm_hv_pu": "float64", + "va_hv_degree": "float64", + "vm_lv_pu": "float64", + "va_lv_degree": "float64", + "loading_percent": "float64" + } + }, + "res_trafo3w": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_hv_mw\",\"q_hv_mvar\",\"p_mv_mw\",\"q_mv_mvar\",\"p_lv_mw\",\"q_lv_mvar\",\"pl_mw\",\"ql_mvar\",\"i_hv_ka\",\"i_mv_ka\",\"i_lv_ka\",\"vm_hv_pu\",\"va_hv_degree\",\"vm_mv_pu\",\"va_mv_degree\",\"vm_lv_pu\",\"va_lv_degree\",\"va_internal_degree\",\"vm_internal_pu\",\"loading_percent\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_hv_mw": "float64", + "q_hv_mvar": "float64", + "p_mv_mw": "float64", + "q_mv_mvar": "float64", + "p_lv_mw": "float64", + "q_lv_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_hv_ka": "float64", + "i_mv_ka": "float64", + "i_lv_ka": "float64", + "vm_hv_pu": "float64", + "va_hv_degree": "float64", + "vm_mv_pu": "float64", + "va_mv_degree": "float64", + "vm_lv_pu": "float64", + "va_lv_degree": "float64", + "va_internal_degree": "float64", + "vm_internal_pu": "float64", + "loading_percent": "float64" + } + }, + "res_impedance": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"ql_mvar\",\"i_from_ka\",\"i_to_ka\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "ql_mvar": "float64", + "i_from_ka": "float64", + "i_to_ka": "float64" + } + }, + "res_ext_grid": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_load": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_sgen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_storage": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64" + } + }, + "res_shunt": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64" + } + }, + "res_gen": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"va_degree\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "va_degree": "float64", + "vm_pu": "float64" + } + }, + "res_ward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64" + } + }, + "res_xward": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_mw\",\"q_mvar\",\"vm_pu\",\"va_internal_degree\",\"vm_internal_pu\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_mw": "float64", + "q_mvar": "float64", + "vm_pu": "float64", + "va_internal_degree": "float64", + "vm_internal_pu": "float64" + } + }, + "res_dcline": { + "_module": "pandas.core.frame", + "_class": "DataFrame", + "_object": "{\"columns\":[\"p_from_mw\",\"q_from_mvar\",\"p_to_mw\",\"q_to_mvar\",\"pl_mw\",\"vm_from_pu\",\"va_from_degree\",\"vm_to_pu\",\"va_to_degree\"],\"index\":[],\"data\":[]}", + "orient": "split", + "dtype": { + "p_from_mw": "float64", + "q_from_mvar": "float64", + "p_to_mw": "float64", + "q_to_mvar": "float64", + "pl_mw": "float64", + "vm_from_pu": "float64", + "va_from_degree": "float64", + "vm_to_pu": "float64", + "va_to_degree": "float64" + } + }, + "user_pf_options": {} + } +} diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/grid_layout.json b/input_data/generation/l2rpn_case14_sandbox_3x/grid_layout.json new file mode 100644 index 0000000..e153464 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/grid_layout.json @@ -0,0 +1,58 @@ +{ + "sub_0": [ + -280.0, + -81.0 + ], + "sub_1": [ + -100.0, + -270.0 + ], + "sub_2": [ + 366.0, + -270.0 + ], + "sub_3": [ + 366.0, + -54.0 + ], + "sub_4": [ + -64.0, + -54.0 + ], + "sub_5": [ + -64.0, + 54.0 + ], + "sub_6": [ + 450.0, + 0.0 + ], + "sub_7": [ + 550.0, + 0.0 + ], + "sub_8": [ + 326.0, + 54.0 + ], + "sub_9": [ + 222.0, + 108.0 + ], + "sub_10": [ + 79.0, + 162.0 + ], + "sub_11": [ + -170.0, + 270.0 + ], + "sub_12": [ + -64.0, + 270.0 + ], + "sub_13": [ + 222.0, + 216.0 + ] +} diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/loads_charac.csv b/input_data/generation/l2rpn_case14_sandbox_3x/loads_charac.csv new file mode 100644 index 0000000..cafe653 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/loads_charac.csv @@ -0,0 +1,13 @@ +Pmax,name,type,x,y +21.7,load_1_0,residential,180,10 +94.2,load_2_1,residential,646,10 +14.9,load_13_10,residential,646,226 +47.8,load_3_2,residential,216,226 +7.6,load_4_3,residential,216,334 +11.2,load_5_4,residential,606,334 +29.5,load_8_5,residential,502,388 +9.0,load_9_6,residential,359,442 +3.5,load_10_7,residential,128,550 +6.1,load_11_8,residential,216,550 +13.5,load_12_9,residential,502,496 + diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/params.json b/input_data/generation/l2rpn_case14_sandbox_3x/params.json new file mode 100644 index 0000000..183a084 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/params.json @@ -0,0 +1,4 @@ +{ + "dt": 5, + "planned_std": "0.01" +} diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/params_load.json b/input_data/generation/l2rpn_case14_sandbox_3x/params_load.json new file mode 100644 index 0000000..f40abf3 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/params_load.json @@ -0,0 +1,8 @@ +{ + "Lx": 1000, + "Ly": 1000, + "dx_corr": 250, + "dy_corr": 250, + "temperature_corr": 400, + "std_temperature_noise": 0.06 +} diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/params_loss.json b/input_data/generation/l2rpn_case14_sandbox_3x/params_loss.json new file mode 100644 index 0000000..717b866 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/params_loss.json @@ -0,0 +1 @@ +{"loss_pattern": "loss_pattern.csv"} \ No newline at end of file diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/params_opf.json b/input_data/generation/l2rpn_case14_sandbox_3x/params_opf.json new file mode 100644 index 0000000..94c2e38 --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/params_opf.json @@ -0,0 +1 @@ +{"step_opf_min": 5, "mode_opf": "month", "reactive_comp": 1, "losses_pct": 0.4, "dispatch_by_carrier": false, "ramp_mode": "hard", "pyomo": false, "solver_name": "cbc", "idxSlack": 5, "nameSlack": "gen_0_5", "hydro_ramp_reduction_factor": 1, "slack_p_max_reduction": 30, "slack_ramp_max_reduction": 6, "loss_grid2op_simulation": true, "agent_type": "reco", "early_stopping_mode": false} diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/params_res.json b/input_data/generation/l2rpn_case14_sandbox_3x/params_res.json new file mode 100644 index 0000000..3542d3c --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/params_res.json @@ -0,0 +1,16 @@ +{ + "Lx": 1000, + "Ly": 1000, + "dx_corr": 250, + "dy_corr": 250, + "long_wind_corr": 5000, + "medium_wind_corr": 720, + "short_wind_corr": 120, + "solar_corr": 20, + "smoothdist": 0.001, + "std_solar_noise": 0.4, + "std_short_wind_noise": 0.1, + "std_medium_wind_noise": 0.15, + "std_long_wind_noise": 0.2, + "year_solar_pattern": 2007 +} diff --git a/input_data/generation/l2rpn_case14_sandbox_3x/prods_charac.csv b/input_data/generation/l2rpn_case14_sandbox_3x/prods_charac.csv new file mode 100644 index 0000000..0c1159a --- /dev/null +++ b/input_data/generation/l2rpn_case14_sandbox_3x/prods_charac.csv @@ -0,0 +1,7 @@ +Pmax,Pmin,name,type,bus,max_ramp_up,max_ramp_down,min_up_time,min_down_time,marginal_cost,shut_down_cost,start_cost,x,y,V +140,0.0,gen_1_0,nuclear,1,5,5,96,96,40,10,20,180,10,142.1 +120,0.0,gen_2_1,thermal,2,10,10,4,4,70,1,2,646,10,142.1 +70,0.0,gen_5_2,wind,5,0,0,0,0,0,0,0,216,334,22.0 +70,0.0,gen_5_3,solar,5,0,0,0,0,0,0,0,216,334,22.0 +40,0.0,gen_7_4,solar,7,0,0,0,0,0,0,0,718,280,13.2 +100,0.0,gen_0_5,hydro,0,15,15,4,4,70,1,2,0,199,142.1 diff --git a/scripts/generate_l2rpn_case_14.sh b/scripts/generate_l2rpn_case_14.sh new file mode 100755 index 0000000..ed29ce9 --- /dev/null +++ b/scripts/generate_l2rpn_case_14.sh @@ -0,0 +1,23 @@ +#!/bin/bash + +WEEKS=52 +CASES=("l2rpn_case14_sandbox_1x" "l2rpn_case14_sandbox_2x" "l2rpn_case14_sandbox_3x") +START=2019-01-05 +N_SCENARIOS=1 + +for case in ${CASES[*]}; +do + echo "Generating data for case " $case + chronix2grid --mode LRT \ + --output-folder `pwd`/../output_data \ + --input-folder `pwd`/../input_data \ + --ignore-warnings \ + --weeks $WEEKS \ + --case $case \ + --n_scenarios $N_SCENARIOS \ + --start-date $START \ + --by-n-weeks 4 \ + --seed-for-loads 936327420 --seed-for-res 936327420 --seed-for-dispatch 936327420 + +done +