Revert "Change LV reniforcement"

This reverts commit 43552cf.
openego · Jan 18, 2024 · 74381c3 · 74381c3
1 parent 7b7a7e1
commit 74381c3
Showing 1 changed file with 14 additions and 55 deletions.
diff --git a/edisgo/flex_opt/reinforce_grid.py b/edisgo/flex_opt/reinforce_grid.py
@@ -903,7 +903,7 @@ def enhanced_reinforce_grid(
     logger.info("Run initial grid reinforcement for single LV grids.")
     for lv_grid in list(edisgo_object.topology.mv_grid.lv_grids):
         logger.info(f"Check initial convergence for {lv_grid=}.")
-        ts_converged, ts_not_converged = edisgo_object.analyze(
+        _, ts_not_converged = edisgo_object.analyze(
             mode="lv", raise_not_converged=False, lv_grid_id=lv_grid.id
         )
         if len(ts_not_converged) > 0:
@@ -922,32 +922,12 @@ def enhanced_reinforce_grid(
                 )
         try:
             logger.info(f"Try initial mode 'lv' reinforcement for {lv_grid=}.")
-            if len(ts_not_converged) > 0:
-                # if there are time steps that did not converge, run reinforcement
-                # first on converged time steps
-                edisgo_object.reinforce(
-                    mode="lv",
-                    lv_grid_id=lv_grid.id,
-                    catch_convergence_problems=False,
-                    timesteps_pfa=ts_converged,
-                    **kwargs,
-                )
-                # run reinforcement again in catch-convergence mode with all time steps
-                edisgo_object.reinforce(
-                    mode="lv",
-                    lv_grid_id=lv_grid.id,
-                    catch_convergence_problems=True,
-                    **kwargs,
-                )
-            else:
-                # if all time steps converged, run normal reinforcement
-                edisgo_object.reinforce(
-                    mode="lv",
-                    lv_grid_id=lv_grid.id,
-                    catch_convergence_problems=False,
-                    run_initial_analyze=False,
-                    **kwargs,
-                )
+            edisgo_object.reinforce(
+                mode="lv",
+                lv_grid_id=lv_grid.id,
+                catch_convergence_problems=True,
+                **kwargs,
+            )
             logger.info(f"Initial mode 'lv' reinforcement for {lv_grid} successful.")
         except (ValueError, RuntimeError, exceptions.MaximumIterationError):
             logger.warning(f"Initial mode 'lv' reinforcement for {lv_grid} failed.")
@@ -980,7 +960,7 @@ def enhanced_reinforce_grid(
 
         for lv_grid in list(edisgo_object.topology.mv_grid.lv_grids):
             logger.info(f"Check convergence for {lv_grid=}.")
-            ts_converged, ts_not_converged = edisgo_object.analyze(
+            _, ts_not_converged = edisgo_object.analyze(
                 mode="lv", raise_not_converged=False, lv_grid_id=lv_grid.id
             )
             if len(ts_not_converged) > 0:
@@ -1001,33 +981,12 @@ def enhanced_reinforce_grid(
                     )
             try:
                 logger.info(f"Try mode 'lv' reinforcement for {lv_grid=}.")
-                if len(ts_not_converged) > 0:
-                    # if there are time steps that did not converge, run reinforcement
-                    # first on converged time steps
-                    edisgo_object.reinforce(
-                        mode="lv",
-                        lv_grid_id=lv_grid.id,
-                        catch_convergence_problems=False,
-                        timesteps_pfa=ts_converged,
-                        **kwargs,
-                    )
-                    # run reinforcement again in catch-convergence mode with all time
-                    # steps
-                    edisgo_object.reinforce(
-                        mode="lv",
-                        lv_grid_id=lv_grid.id,
-                        catch_convergence_problems=True,
-                        **kwargs,
-                    )
-                else:
-                    # if all time steps converged, run normal reinforcement
-                    edisgo_object.reinforce(
-                        mode="lv",
-                        lv_grid_id=lv_grid.id,
-                        catch_convergence_problems=False,
-                        run_initial_analyze=False,
-                        **kwargs,
-                    )
+                edisgo_object.reinforce(
+                    mode="lv",
+                    lv_grid_id=lv_grid.id,
+                    catch_convergence_problems=True,
+                    **kwargs,
+                )
                 logger.info(f"Mode 'lv' reinforcement for {lv_grid} successful.")
             except (ValueError, RuntimeError, exceptions.MaximumIterationError):
                 logger.info(f"Mode 'lv' reinforcement for {lv_grid} failed.")