Merge pull request #431 from agoenergy/415-add-storage-capacity-and-s…

…torage-costs-to-optimization-results-table

415 add storage capacity and storage costs to optimization results table

app/plot_functions.py

@@ -616,29 +616,34 @@ def create_profile_figure_generation(df_sel: pd.DataFrame) -> go.Figure:
     fig = go.Figure()
 
     add_trace_to_figure(
-        df_sel, fig, component="PV tilted", parameter="Power", fill=True, color="yellow"
+        df_sel,
+        fig,
+        component="PV tilted",
+        parameter="Power",
+        fill=True,
+        color="#FFE000",
     )
     add_trace_to_figure(
         df_sel,
         fig,
         component="Wind onshore",
         parameter="Power",
         fill=True,
-        color="blue",
+        color="#1E78C2",
     )
     add_trace_to_figure(
         df_sel,
         fig,
         component="Wind offshore",
         parameter="Power",
         fill=True,
-        color="blue",
+        color="#0061A4",
     )
     add_trace_to_figure(
-        df_sel, fig, component="Electrolyzer", parameter="Power", color="black"
+        df_sel, fig, component="Electrolyzer", parameter="Power", color="#0C0C0C"
     )
     add_trace_to_figure(
-        df_sel, fig, component="Derivate production", parameter="Power", color="red"
+        df_sel, fig, component="Derivate production", parameter="Power", color="#408B2E"
     )
 
     add_vertical_lines(fig)

app/tab_optimization.py

@@ -1,5 +1,6 @@
 # -*- coding: utf-8 -*-
 """Content of optimization tab."""
+import numpy as np
 import pandas as pd
 import pypsa
 import streamlit as st
@@ -57,8 +58,8 @@ def content_optimization(api: PtxboaAPI) -> None:
                 res,
                 use_container_width=True,
                 column_config={
-                    "Capacity (kW)": st.column_config.NumberColumn(format="%.1f"),
-                    "Output (kWh/a)": st.column_config.NumberColumn(format="%.0f"),
+                    "Capacity (MW)": st.column_config.NumberColumn(format="%.1f"),
+                    "Output (MWh/a)": st.column_config.NumberColumn(format="%.0f"),
                     "Full load hours (h)": st.column_config.NumberColumn(format="%.0f"),
                     "Curtailment (%)": st.column_config.NumberColumn(format="%.1f %%"),
                     "Cost (USD/MWh)": st.column_config.NumberColumn(format="%.1f"),
@@ -108,32 +109,32 @@ def calc_aggregate_statistics(
         "WIND-OFF",
     ]:
         if g in n.generators.index:
-            res.at[g, "Capacity (kW)"] = n.generators.at[g, "p_nom_opt"]
-            res.at[g, "Output (kWh/a)"] = (
+            res.at[g, "Capacity (MW)"] = n.generators.at[g, "p_nom_opt"]
+            res.at[g, "Output (MWh/a)"] = (
                 n.generators_t["p"][g] * n.snapshot_weightings["generators"]
             ).sum()
             res.at[g, "CAPEX (USD/kW)"] = n.generators.at[g, "capital_cost"]
             res.at[g, "OPEX (USD/kWh)"] = n.generators.at[g, "marginal_cost"]
             res.at[g, "Full load hours before curtailment (h)"] = (
                 n.generators_t["p_max_pu"][g] * n.snapshot_weightings["generators"]
             ).sum()
-            res.at[g, "Curtailment (kWh/a)"] = (
-                res.at[g, "Capacity (kW)"]
+            res.at[g, "Curtailment (MWh/a)"] = (
+                res.at[g, "Capacity (MW)"]
                 * res.at[g, "Full load hours before curtailment (h)"]
-                - res.at[g, "Output (kWh/a)"]
+                - res.at[g, "Output (MWh/a)"]
             )
             res.at[g, "Curtailment (%)"] = (
                 100
-                * res.at[g, "Curtailment (kWh/a)"]
-                / (res.at[g, "Output (kWh/a)"] + res.at[g, "Curtailment (kWh/a)"])
+                * res.at[g, "Curtailment (MWh/a)"]
+                / (res.at[g, "Output (MWh/a)"] + res.at[g, "Curtailment (MWh/a)"])
             )
 
     for g in ["ELY", "DERIV", "H2_STR_in"]:
         if g in n.links.index:
-            res.at[g, "Capacity (kW)"] = (
+            res.at[g, "Capacity (MW)"] = (
                 n.links.at[g, "p_nom_opt"] * n.links.at[g, "efficiency"]
             )
-            res.at[g, "Output (kWh/a)"] = (
+            res.at[g, "Output (MWh/a)"] = (
                 -n.links_t["p1"][g] * n.snapshot_weightings["generators"]
             ).sum()
             res.at[g, "CAPEX (USD/kW)"] = (
@@ -143,8 +144,8 @@ def calc_aggregate_statistics(
 
     for g in ["EL_STR"]:
         if g in n.storage_units.index:
-            res.at[g, "Capacity (kW)"] = n.storage_units.at[g, "p_nom_opt"]
-            res.at[g, "Output (kWh/a)"] = (
+            res.at[g, "Capacity (MW)"] = n.storage_units.at[g, "p_nom_opt"]
+            res.at[g, "Output (MWh/a)"] = (
                 n.storage_units_t["p_dispatch"][g] * n.snapshot_weightings["generators"]
             ).sum()
             res.at[g, "CAPEX (USD/kW)"] = n.storage_units.at[g, "capital_cost"]
@@ -157,25 +158,23 @@ def calc_aggregate_statistics(
         "N2-G_supply",
     ]:
         if g in n.generators.index:
-            res.at[g, "Output (kWh/a)"] = (
+            res.at[g, "Output (MWh/a)"] = (
                 n.generators_t["p"][g] * n.snapshot_weightings["generators"]
             ).sum()
             res.at[g, "OPEX (USD/kWh)"] = n.generators.at[g, "marginal_cost"]
 
     res = res.fillna(0)
 
-    res["Full load hours (h)"] = res["Output (kWh/a)"] / res["Capacity (kW)"]
+    res["Full load hours (h)"] = res["Output (MWh/a)"] / res["Capacity (MW)"]
     res["Cost (USD/MWh)"] = (
         (
-            res["Capacity (kW)"] * res["CAPEX (USD/kW)"]
-            + res["Output (kWh/a)"] * res["OPEX (USD/kWh)"]
+            res["Capacity (MW)"] * res["CAPEX (USD/kW)"]
+            + res["Output (MWh/a)"] * res["OPEX (USD/kWh)"]
         )
         / 8760
         * 1000
     )
 
-    res["Output (MWh/a)"] = res["Output (kWh/a)"] / 1000
-
     # rename components:
     rename_list = {
         "PV-FIX": "PV tilted",
@@ -192,16 +191,19 @@ def calc_aggregate_statistics(
 
     # drop unwanted columns:
     if not include_debugging_output:
+
+        # filter columns:
         res = res[
             [
-                "Capacity (kW)",
-                "Output (kWh/a)",
+                "Capacity (MW)",
+                "Output (MWh/a)",
                 "Full load hours (h)",
                 "Curtailment (%)",
                 "Cost (USD/MWh)",
             ]
         ]
 
+        # filter rows:
         res = res[
             res.index.isin(
                 [
@@ -210,10 +212,29 @@ def calc_aggregate_statistics(
                     "Wind offshore",
                     "Electrolyzer",
                     "Derivate production",
+                    "Electricity storage",
+                    "H2 storage",
                 ]
             )
         ]
 
+        # remove unwanted entries:
+        for i in ["Electricity storage", "H2 storage"]:
+            for c in [
+                "Output (MWh/a)",
+                "Full load hours (h)",
+                "Curtailment (%)",
+            ]:
+                if i in res.index:
+                    res.at[i, c] = np.nan
+
+        for i in [
+            "Electrolyzer",
+            "Derivate production",
+        ]:
+            if i in res.index:
+                res.at[i, "Curtailment (%)"] = np.nan
+
     # calculate total costs:
     res.at["Total", "Cost (USD/MWh)"] = res["Cost (USD/MWh)"].sum()
 

md/info_optimization_results.md

@@ -1,6 +1,6 @@
 This table shows aggregated results of the optimization:
 
-- the installed generation, electrolyzer and derivate production capacities and their annual output that are required to produce 8760kWh of final product per year
+- the installed generation, electrolyzer and derivate production capacities and their annual output that are required to produce 8760 MWh of final product per year
 - the realized full load hours of said components  
 - the curtailment of renewable generation
 - the costs per MWh of final product.