Merge branch 'wind_layout_mod' of https://github.com/NREL/HOPP into w…

…ind_layout_mod

.github/workflows/ci.yml

@@ -1,6 +1,6 @@
 name: Testing
 
-on: [ push ]
+on: [ push, pull_request ]
 
 jobs:
   build:
@@ -20,6 +20,7 @@ jobs:
         env:
           SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL: True
         run: |
+          pip install scikit-learn
           sudo apt-get update && sudo apt-get install -y libglpk-dev glpk-utils coinor-cbc
           python -m pip install --upgrade pip
           pip install -r requirements.txt

.gitignore

@@ -10,7 +10,6 @@ examples/HOPP_examples/
 HOPP_examples/
 HOPP-demos/
 # needed for h2 test inputs: tests/analysis/results/
-WB_case_study/
 examples/H2 Analysis/results/reopt_precomputes/
 
 tests/hybrid/REoptResultsNoExportAboveLoad.json
@@ -20,10 +19,6 @@ examples/analysis/results/*.csv
 resource_files/wind
 resource_files/solar
 
-resource_files/grid/tunisia_est_grid_prices.csv
-resource_files/solar/Hazoua
-resource_files/solar/Beni_Miha
-
 # clean up after merge
 examples/Powerflow Analysis
 examples/analysis/Engie

LICENSE

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2019, Alliance for Sustainable Energy, LLC
+Copyright (c) 2020, Alliance for Sustainable Energy, LLC
 All rights reserved.
 
 Redistribution and use in source and binary forms, with or without

README.md

@@ -1,5 +1,7 @@
 # Hybrid Optimization and Performance Platform
 
+![CI Tests](https://github.com/NREL/HOPP/actions/workflows/ci.yml/badge.svg)
+
 As part of NREL's [Hybrid Energy Systems Research](https://www.nrel.gov/wind/hybrid-energy-systems-research.html), this
 software assesses optimal designs for the deployment of utility-scale hybrid energy plants, particularly considering wind,
 solar and storage.
@@ -23,10 +25,12 @@ solar and storage.
 
 4. Install requirements:
     ```
-    conda install -c conda-forge glpk -y
+    conda install -c conda-forge coin-or-cbc -y
     conda install -c conda-forge shapely==1.7.1 -y
     pip install -r requirements.txt
     ```
+
+    Note if you are on Windows, you will have to manually install Cbc: https://github.com/coin-or/Cbc
 
 5. Run install script:
     ```

RELEASE.md

@@ -1,5 +1,14 @@
 # Release Notes
 
+## Version 1.0.0, Upcoming
+* Add Wind + PV + Battery + PEM Electrolyzer analysis to examples in `H2_Analysis`
+* Add default scenario inputs for hydrogen as end product with result files
+* Add files for simulating, optimizing and plotting Wind + PV + Battery + PEM Electrolyzer hybrids
+* Add a PEM electrolyzer model to hybrid (not integrated into HybridSimulation)
+* Separate power and financial simulations for PowerSoures and HybridSimulation
+* Fix multiprocessing issues
+* Updates to integrate FLORIS v3
+
 ## Version 0.1.0.dev3, Mar. 11, 2022
 * Include CBC package data for Windows
 

alt_dev/optimization_driver_alt.py

@@ -1,4 +1,3 @@
-import functools
 import inspect
 import time
 import os
@@ -152,7 +151,44 @@ def run(self):
 
 class OptimizationDriver():
     """
-    Object to interface the HOPP optimization problem with humpday optimizers
+    Object to interface the HOPP design analysis methods (i.e., sampling and optimization)
+
+    .. TODO: We might want to rename this to ProblemDriver? As it is required for non-optimization runs.
+
+    Parameters
+    ----------
+    time_limit : initializer(float), optional
+        Total time limit in seconds
+
+    eval_limit : initializer(float), optional
+        Objective evaluation limit (counts new evaluations only)
+    
+    obj_limit : initializer(float), optional
+        Lower bound of objective, exit if best objective is less than this
+
+    n_proc : initializer(int), optional
+        Maximum number of objective process workers
+
+    cach_dir : initializer(str), optional
+        Filename for the driver cache file
+
+    reconnect_cache : initializer(bool), optional
+        ``True`` if the driver should reconnect to a previous result cache
+
+    write_csv : initializer(bool), optional
+        ``True`` if the cached results should be written to csv format files
+
+    dataframe_file : initializer(str), optional
+        Filename for the driver cache dataframe file
+
+    csv_file : initializer(str), optional
+        filename for the driver cache csv file (if ``write_csv`` is ``True``)
+
+    scaled : initializer(bool), optional
+        ``True`` if the sample/optimizer candidates need to be scaled to problem units
+    
+    retry : initializer(bool), optional
+        ``True`` if any evaluations ending in an exception should be retried on restart
     """
     DEFAULT_KWARGS = dict(time_limit=np.inf,  # total time limit in seconds
                           eval_limit=np.inf,  # objective evaluation limit (counts new evaluations only)
@@ -348,9 +384,9 @@ def write_cache(self, pd_filename=None, csv_filename=None) -> None:
         :param filename: Optional path of file to write out the cache to
         :return:  None
         """
-        if self.start_len == len(self.cache) - 1:
-            print(f"no new entries in cache ({len(self.cache) - 1} results), skipping write...")
-            return
+        # if self.start_len == len(self.cache) - 1:
+            # print(f"no new entries in cache ({len(self.cache) - 1} results), skipping write...")
+            # return
 
         dt_string = datetime.now().strftime('%Y-%m-%d_%H.%M.%S')
 

alt_dev/post_dev.py

@@ -140,16 +140,20 @@ def plot(x, y, color, type, symbol, log_x, log_y, scale_x, scale_y):
         plot_data = pd.concat(data_list, axis=1, keys=keys)
 
         if type == "box":
-            return px.box(plot_data, x=x, y=y, color=color, points=points, log_x=log_x, log_y=log_y, **kwargs)
+            return px.box(plot_data, x=x, y=y, color=color, points=points, log_x=log_x, log_y=log_y, 
+             color_continuous_scale=px.colors.sequential.Turbo, **kwargs)
 
         elif type == "bar":
-            return px.bar(plot_data, x=x, y=y, color=color, barmode=barmode, log_x=log_x, log_y=log_y, **kwargs)
+            return px.bar(plot_data, x=x, y=y, color=color, barmode=barmode, log_x=log_x, log_y=log_y, 
+             color_continuous_scale=px.colors.sequential.Turbo, **kwargs)
 
         elif type == "scatter":
-            return px.scatter(plot_data, x=x, y=y, color=color, symbol=symbol, log_x=log_x, log_y=log_y, **kwargs)
+            return px.scatter(plot_data, x=x, y=y, color=color, symbol=symbol, log_x=log_x, log_y=log_y, 
+             color_continuous_scale=px.colors.sequential.Turbo, **kwargs)
 
         elif type == "line":    
-            return px.line(plot_data, x=x, y=y, color=color, symbol=symbol, log_x=log_x, log_y=log_y, **kwargs)
+            return px.line(plot_data, x=x, y=y, color=color, symbol=symbol, log_x=log_x, log_y=log_y, 
+             color_continuous_scale=px.colors.sequential.Turbo, **kwargs)
 
     return interact_row_wrap(plot, **switches).widget         
 

alt_dev/run_alt.py

@@ -28,6 +28,7 @@
 import pyDOE2 as pyDOE
 # import idaes.surrogate.pysmo.sampling as sampling
 import numpy as np
+import pandas as pd
 
 # NREL dev API key, for weather and data files and site information
 from pathlib import Path
@@ -78,7 +79,7 @@ def init_simulation_pv():
                            'dc_ac_ratio': 1.1},
                     'battery': {'system_capacity_kwh': battery_capacity_mwh * 1000,
                                 'system_capacity_kw': battery_capacity_mw * 1000},
-                    'grid': interconnection_size_mw * 1000}
+                    'grid': {'interconnect_kw': interconnection_size_mw * 1000}}
 
     # Create the hybrid plant simulation
     # TODO: turn these off to run full year simulation
@@ -91,7 +92,6 @@ def init_simulation_pv():
     # TODO: turn-on receiver and field optimization before... initial simulation
     hybrid_plant = HybridSimulation(technologies,
                                     site_info,
-                                    interconnect_kw=interconnection_size_mw * 1000,
                                     dispatch_options=dispatch_options)
 
     # Customize the hybrid plant assumptions here...
@@ -165,7 +165,7 @@ def init_simulation_csp():
                               'solar_multiple': 2.0,
                               'tes_hours': 12.0,
                               'optimize_field_before_sim': True}, # TODO: turn on
-                    'grid': interconnection_size_mw * 1000}
+                    'grid': {'interconnect_kw': interconnection_size_mw * 1000}}
 
     # Create the hybrid plant simulation
     # TODO: turn these off to run full year simulation
@@ -176,7 +176,6 @@ def init_simulation_csp():
     # TODO: turn-on receiver and field optimization before... initial simulation
     hybrid_plant = HybridSimulation(technologies,
                                     site_info,
-                                    interconnect_kw=interconnection_size_mw * 1000,
                                     dispatch_options=dispatch_options)
 
     return hybrid_plant
@@ -251,7 +250,7 @@ def init_simulation_hybrid():
                               'optimize_field_before_sim': True}, # TODO: turn on
                     'battery': {'system_capacity_kwh': battery_capacity_mwh * 1000,
                                 'system_capacity_kw': battery_capacity_mw * 1000},
-                    'grid': interconnection_size_mw * 1000}
+                    'grid': {'interconnect_kw': interconnection_size_mw * 1000}}
 
     # Create the hybrid plant simulation
     # TODO: turn these off to run full year simulation
@@ -264,7 +263,6 @@ def init_simulation_hybrid():
     # TODO: turn-on receiver and field optimization before... initial simulation
     hybrid_plant = HybridSimulation(technologies,
                                     site_info,
-                                    interconnect_kw=interconnection_size_mw * 1000,
                                     dispatch_options=dispatch_options)
 
     # Customize the hybrid plant assumptions here...

docs/citing_hopp.rst

@@ -5,6 +5,13 @@ Hybrid Optimization Performance Platform (HOPP)
 -----------------------------------------------
 .. Software record or a report?
 
+Tripp, Charles E., Guittet, Darice, Barker, Aaron, King, Jennifer, and Hamilton, Bill. Hybrid Optimization and 
+Performance Platform (HOPP). Computer software. November 14, 2019. https://github.com/NREL/HOPP. 
+https://doi.org/10.11578/dc.20210326.1.
+
+Tripp, C., Guittet, D., King, J., and Barker, A.: A Simplified, Efficient Approach to Hybrid Wind and Solar Plant 
+Site Optimization, Wind Energ. Sci. Discuss. [preprint], https://doi.org/10.5194/wes-2021-54, in review, 2021.
+
 Dispatch Optimization
 ---------------------
 .. We can break it up based on different HOPP capabilities.

docs/conf.py

@@ -68,3 +68,14 @@
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
 html_static_path = []
+
+# -- Options for Latex pdf output --------------------------------------------
+
+fh = open('latex_preamble.tex', 'r+')
+PREAMBLE = fh.read()
+fh.close()
+latex_elements = {
+# Additional stuff for the LaTeX preamble.
+'preamble': PREAMBLE,
+'extraclassoptions': 'openany,oneside'
+}