re-introduce unmet demand in spores objective; remove hardcoded spores parameter setting

Author: brynpickering

src/calliope/math/spores.yaml

@@ -19,9 +19,17 @@ global_expressions:
 
 objectives:
   min_spores:
-    description: >-
-      SPORES score minimisation objective, activated for all iterations after the baseline optimisation.
-      The SPORES scores are applied to flow capacity for each technology at each node.
     equations:
-      - expression: sum(flow_cap * spores_score, over=[nodes, techs, carriers])
+      - expression: sum(flow_cap * spores_score, over=[nodes, techs, carriers]) + $unmet_demand
+    sub_expressions:
+      unmet_demand:
+        - where: "config.ensure_feasibility=True"
+          expression: >-
+            sum(
+              sum(unmet_demand - unused_supply, over=[carriers, nodes])
+              * timestep_weights,
+              over=timesteps
+            ) * bigM
+        - where: "NOT config.ensure_feasibility=True"
+          expression: "0"
     sense: minimise

src/calliope/model.py

@@ -8,7 +8,6 @@
 from pathlib import Path
 from typing import TYPE_CHECKING
 
-import numpy as np
 import pandas as pd
 import xarray as xr
 
@@ -263,16 +262,6 @@ def build(
                     "there exist non-uniform timesteps (e.g. from time clustering)"
                 )
             backend_input = self._prepare_operate_mode_inputs(self.config.build.operate)
-        elif mode == "spores":
-            backend_input = self._model_data.copy()
-            if "spores_score" not in backend_input:
-                backend_input["spores_score"] = xr.DataArray(0).assign_attrs(
-                    is_result=0
-                )
-            if "spores_baseline_cost" not in backend_input:
-                backend_input["spores_baseline_cost"] = xr.DataArray(
-                    np.inf
-                ).assign_attrs(is_result=0)
         else:
             backend_input = self._model_data