Features/#665 interface pre market market optimization

etrago/appl.py

@@ -54,6 +54,11 @@
         "type": "market_grid",  # type of optimization, currently only 'lopf'
         "n_iter": 1,  # abort criterion of iterative optimization, 'n_iter' or 'threshold'
         "pyomo": True,  # set if pyomo is used for model building
+        "formulation": "pyomo",
+        "rolling_horizon": { # Define parameter of market optimization
+            "planning_horizon": 72, # number of snapshots in each optimization
+            "overlap": 24, # number of overlapping hours
+            },
     },
     "pf_post_lopf": {
         "active": False,  # choose if perform a pf after lopf

etrago/cluster/electrical.py

@@ -95,7 +95,7 @@ def leader(x):
     return leader
 
 
-def adjust_no_electric_network(etrago, busmap, cluster_met):
+def adjust_no_electric_network(etrago, busmap, cluster_met, apply_on="grid_model"):
     """
     Adjusts the non-electric network based on the electrical network
     (esp. eHV network), adds the gas buses to the busmap, and creates the
@@ -139,7 +139,16 @@ def find_de_closest(network, bus_ne):
 
         return new_ehv_bus
 
-    network = etrago.network.copy()
+    if apply_on=="grid_model":
+        network = etrago.network.copy()
+    elif apply_on == "market_model":
+        network = etrago.network_tsa.copy()
+    else:
+        logger.warning(
+            """Parameter apply_on must be either 'grid_model' or 'market_model'
+            """
+        )
+
     # network2 is supposed to contain all the not electrical or gas buses
     # and links
     network2 = network.copy(with_time=False)
@@ -457,7 +466,7 @@ def ehv_clustering(self):
         logger.info("Network clustered to EHV-grid")
 
 
-def select_elec_network(etrago):
+def select_elec_network(etrago, apply_on="grid_model"):
     """
     Selects the electric network based on the clustering settings specified
     in the Etrago object.
@@ -475,7 +484,15 @@ def select_elec_network(etrago):
         n_clusters : int
             number of clusters used in the clustering process.
     """
-    elec_network = etrago.network.copy()
+    if apply_on=="grid_model":
+        elec_network = etrago.network.copy()
+    elif apply_on=="market_model":
+        elec_network=etrago.network_tsa.copy()
+    else:
+        logger.warning(
+            """Parameter apply_on must be either 'grid_model' or 'market_model'
+            """
+        )
     settings = etrago.args["network_clustering"]
     if settings["cluster_foreign_AC"]:
         elec_network.buses = elec_network.buses[
@@ -626,7 +643,7 @@ def unify_foreign_buses(etrago):
     return busmap_foreign
 
 
-def preprocessing(etrago):
+def preprocessing(etrago, apply_on="grid_model"):
     """
     Preprocesses an Etrago object to prepare it for network clustering.
 
@@ -647,7 +664,16 @@ def preprocessing(etrago):
         The Series object with the foreign bus mapping data.
     """
 
-    network = etrago.network
+    if apply_on == "grid_model":
+        network = etrago.network
+    elif apply_on == "market_model":
+        network = etrago.network_tsa
+    else:
+        logger.warning(
+            """Parameter apply_on must be either 'grid_model' or 'market_model'
+            """
+        )
+
     settings = etrago.args["network_clustering"]
 
     # problem our lines have no v_nom. this is implicitly defined by the
@@ -736,7 +762,7 @@ def preprocessing(etrago):
     else:
         busmap_foreign = pd.Series(name="foreign", dtype=str)
 
-    network_elec, n_clusters = select_elec_network(etrago)
+    network_elec, n_clusters = select_elec_network(etrago, apply_on=apply_on)
 
     if settings["method"] == "kmedoids-dijkstra":
         lines_col = network_elec.lines.columns
@@ -777,6 +803,7 @@ def postprocessing(
     medoid_idx=None,
     aggregate_generators_carriers=None,
     aggregate_links=True,
+    apply_on="grid_model"
 ):
     """
     Postprocessing function for network clustering.
@@ -846,7 +873,7 @@ def postprocessing(
         )
 
     network, busmap = adjust_no_electric_network(
-        etrago, busmap, cluster_met=method
+        etrago, busmap, cluster_met=method, apply_on=apply_on
     )
 
     # merge busmap for foreign buses with the German buses

etrago/cluster/snapshot.py

@@ -811,7 +811,7 @@ def skip_snapshots(self):
     if (
         self.args["temporal_disaggregation"]["active"]
         and not self.args["snapshot_clustering"]["active"]
-    ):
+    ) or self.args["method"]["type"]=="market_grid":
         self.network_tsa = self.network.copy()
 
     n_skip = self.args["skip_snapshots"]

etrago/execute/grid_optimization.py

@@ -68,33 +68,33 @@ def fix_chp_generation(self):
     # Fix generator dispatch from market simulation:
     # Set p_max_pu of generators using results from (disaggregated) market
     # model
-    self.network.generators_t.p_max_pu.loc[
-        :, gens_fixed
-    ] = self.market_model.generators_t.p[gens_fixed].mul(
-        1 / self.market_model.generators.p_nom[gens_fixed]
+    self.network.generators_t.p_max_pu.loc[:, gens_fixed] = (
+        self.market_model.generators_t.p[gens_fixed].mul(
+            1 / self.market_model.generators.p_nom[gens_fixed]
+        )
     )
 
     # Set p_min_pu of generators using results from (disaggregated) market
     # model
-    self.network.generators_t.p_min_pu.loc[
-        :, gens_fixed
-    ] = self.market_model.generators_t.p[gens_fixed].mul(
-        1 / self.market_model.generators.p_nom[gens_fixed]
+    self.network.generators_t.p_min_pu.loc[:, gens_fixed] = (
+        self.market_model.generators_t.p[gens_fixed].mul(
+            1 / self.market_model.generators.p_nom[gens_fixed]
+        )
     )
 
     # Fix link dispatch (gas turbines) from market simulation
     # Set p_max_pu of links using results from (disaggregated) market model
-    self.network.links_t.p_max_pu.loc[
-        :, links_fixed
-    ] = self.market_model.links_t.p0[links_fixed].mul(
-        1 / self.market_model.links.p_nom[links_fixed]
+    self.network.links_t.p_max_pu.loc[:, links_fixed] = (
+        self.market_model.links_t.p0[links_fixed].mul(
+            1 / self.market_model.links.p_nom[links_fixed]
+        )
     )
 
     # Set p_min_pu of links using results from (disaggregated) market model
-    self.network.links_t.p_min_pu.loc[
-        :, links_fixed
-    ] = self.market_model.links_t.p0[links_fixed].mul(
-        1 / self.market_model.links.p_nom[links_fixed]
+    self.network.links_t.p_min_pu.loc[:, links_fixed] = (
+        self.market_model.links_t.p0[links_fixed].mul(
+            1 / self.market_model.links.p_nom[links_fixed]
+        )
     )
 
 
@@ -139,33 +139,33 @@ def add_redispatch_generators(self):
     # Fix generator dispatch from market simulation:
     # Set p_max_pu of generators using results from (disaggregated) market
     # model
-    self.network.generators_t.p_max_pu.loc[
-        :, gens_redispatch
-    ] = self.market_model.generators_t.p[gens_redispatch].mul(
-        1 / self.market_model.generators.p_nom[gens_redispatch]
+    self.network.generators_t.p_max_pu.loc[:, gens_redispatch] = (
+        self.market_model.generators_t.p[gens_redispatch].mul(
+            1 / self.market_model.generators.p_nom[gens_redispatch]
+        )
     )
 
     # Set p_min_pu of generators using results from (disaggregated) market
     # model
-    self.network.generators_t.p_min_pu.loc[
-        :, gens_redispatch
-    ] = self.market_model.generators_t.p[gens_redispatch].mul(
-        1 / self.market_model.generators.p_nom[gens_redispatch]
+    self.network.generators_t.p_min_pu.loc[:, gens_redispatch] = (
+        self.market_model.generators_t.p[gens_redispatch].mul(
+            1 / self.market_model.generators.p_nom[gens_redispatch]
+        )
     )
 
     # Fix link dispatch (gas turbines) from market simulation
     # Set p_max_pu of links using results from (disaggregated) market model
-    self.network.links_t.p_max_pu.loc[
-        :, links_redispatch
-    ] = self.market_model.links_t.p0[links_redispatch].mul(
-        1 / self.market_model.links.p_nom[links_redispatch]
+    self.network.links_t.p_max_pu.loc[:, links_redispatch] = (
+        self.market_model.links_t.p0[links_redispatch].mul(
+            1 / self.market_model.links.p_nom[links_redispatch]
+        )
     )
 
     # Set p_min_pu of links using results from (disaggregated) market model
-    self.network.links_t.p_min_pu.loc[
-        :, links_redispatch
-    ] = self.market_model.links_t.p0[links_redispatch].mul(
-        1 / self.market_model.links.p_nom[links_redispatch]
+    self.network.links_t.p_min_pu.loc[:, links_redispatch] = (
+        self.market_model.links_t.p0[links_redispatch].mul(
+            1 / self.market_model.links.p_nom[links_redispatch]
+        )
     )
 
     # Calculate costs for redispatch
@@ -221,7 +221,8 @@ def add_redispatch_generators(self):
             self.network.generators_t.p_max_pu.loc[:, gens_redispatch].mul(
                 self.network.generators.loc[gens_redispatch, "p_nom"]
             )
-            - (self.market_model.generators_t.p.loc[:, gens_redispatch])
+            - (self.market_model.generators_t.p.loc[self.network.snapshots,
+                                                    gens_redispatch])
         )
         .clip(lower=0.0)
         .values
@@ -247,7 +248,7 @@ def add_redispatch_generators(self):
     self.network.links_t.p_max_pu.loc[:, links_redispatch + " ramp_up"] = (
         (
             self.network.links.loc[links_redispatch, "p_nom"]
-            - (self.market_model.links_t.p0.loc[:, links_redispatch])
+            - (self.market_model.links_t.p0.loc[self.network.snapshots, links_redispatch])
         )
         .clip(lower=0.0)
         .values
@@ -273,7 +274,13 @@ def add_redispatch_generators(self):
     # (disaggregated) generators in the market model
     self.network.generators_t.p_min_pu.loc[
         :, gens_redispatch + " ramp_down"
-    ] = (-(self.market_model.generators_t.p.loc[:, gens_redispatch])).values
+    ] = (
+        -(
+            self.market_model.generators_t.p.loc[self.network.snapshots, gens_redispatch].clip(
+                lower=0.0
+            )
+        )
+    ).values
 
     # Add ramp down links to the network for the grid optimization
     # Marginal cost are currently only the management fee of 4 EUR/MWh,
@@ -295,7 +302,11 @@ def add_redispatch_generators(self):
     # Ramp down can be at maximum as high as the feed-in of the
     # (disaggregated) links in the market model
     self.network.links_t.p_min_pu.loc[:, links_redispatch + " ramp_down"] = (
-        -(self.market_model.links_t.p0.loc[:, links_redispatch])
+        -(
+            self.market_model.links_t.p0.loc[self.network.snapshots, links_redispatch].clip(
+                lower=0.0
+            )
+        )
     ).values
 
     # Check if the network contains any problems