Merge pull request #135 from rl-institut/fix/optimization_return_sche…

…dule

Fix: Station Optimization now returns original rotation set

data/examples/default_optimizer.cfg

@@ -8,17 +8,17 @@ debug_level = 1
 console_level = 99
 
 #SCENARIO
-# Use "" for ids and not ''
-# these rotations are excluded from optimization. they will not be simulated
+# Use "" for ids and not ''.
+# These rotations are excluded from optimization. They will not be simulated.
 exclusion_rots = []
 
-# these stations are excluded from optimization. optimization will not electrify them
+# These stations are excluded from optimization. optimization will not electrify them.
 exclusion_stations = []
-# optimization will electrify these stations.
-# if using inclusion stations, scenario should be rebased
+# Optimization will electrify these stations.
+# if using inclusion stations, scenario should be rebased.
 inclusion_stations = []
-standard_opp_station = {"type": "opps", "n_charging_stations": 200,"distance_transformer": 50}
-# rotations which drop below this value are considered not electrified (default value is 0)
+standard_opp_station = {"type": "opps", "n_charging_stations": null}
+# rotations which drop below this value are considered not electrified (default value is 0).
 min_soc = 0.05
 
 #OPTIMIZER
@@ -31,42 +31,44 @@ solver = quick
 
 # Optimization procedure is developed from the input schedule and scenario. If the scenario is changed
 # through this configuration rebasing should be set to true. This will simulate the scenario again with the
-# given settings
+# given settings.
 rebase_scenario = False
 
-# the rebased scenario can be pickled for analysis or repeated use
+# The rebased scenario can be pickled for analysis or repeated use.
 pickle_rebased = False
-# the name of this pickle file can be defined here
+# The name of this pickle file can be defined here.
 pickle_rebased_name = ""
 # Should all rotations be rebased or can rotations which stay above the soc threshold be skipped?
 run_only_neg = False
-# Should only be opportunity vehicles be rebased, since this optimization is not meant for depot chargers
+# Should only be opportunity vehicles be rebased, since this optimization is not meant for depot chargers?
+# The optimization will return ALL original rotations of the input in all cases.
 run_only_oppb = True
-# number of stations before optimal solution, where branch is checked for pruning
+# number of stations before optimal solution, where branch is checked for pruning.
 pruning_threshold = 3
 
 # Optimization type greedy runs the optimization a single time as greedy as impossible
-# Deep repeatedly searches for promising nodes but only new nodes which have not
-# been checked before.
-# "greedy" or "deep" without ""
+# Deep repeatedly searches for promising nodes but only new nodes which have not been checked before.
+# "greedy" or "deep" without "".
 opt_type = greedy
 
-# For Deep optimization only
+# For Deep optimization only:
+#############################
 # How should the deep optimization choose the nodes.
-# Brute is only recommended in smaller systems
-# "step-by-step" or "brute" without ""
+# Brute is only recommended in smaller systems.
+# "step-by-step" or "brute" without "".
 node_choice = step-by-step
-# How many combinations is the deep method allowed to check
+# How many combinations is the deep method allowed to check?
 max_brute_loop = 300
 # Factor with which the potential evaluation is multiplied before comparing it to the missing energy. A low estimation
-# threshold will lead to a more conservative approach in dismissing branches
+# threshold will lead to a more conservative approach in dismissing branches.
 estimation_threshold = 0.80
 
 
-# Removing impossible rotations leads to a quick calculation estimating if rotations are impossible.impossible
-# If they are deemed as impossible, they are not optimized but discarded
+# Removing impossible rotations leads to a quick calculation estimating if rotations are impossible.
+# If they are deemed as impossible, they are not optimized but discarded during optimization.
+# The optimization will return ALL original rotations of the input in all cases.
 remove_impossible_rotations = True
-# Check if stations are mandatory for a fully electrified system. If they are, include them
+# Check if stations are mandatory for a fully electrified system. If they are, include them.
 check_for_must_stations = False
 
 

simba/station_optimization.py

@@ -1,8 +1,7 @@
 """ Optimization that tries minimizing the amount of electrified stations to achieve full
 electrification.
-
 """
-
+from copy import deepcopy
 import json
 import sys
 from pathlib import Path
@@ -101,6 +100,8 @@ def run_optimization(conf, sched=None, scen=None, args=None):
         assert conf.args, error_message
         sched, scen, args = opt_util.toolbox_from_pickle(conf.schedule, conf.scenario, conf.args)
 
+    original_schedule = deepcopy(sched)
+
     # setup folders, paths and copy config
     prepare_filesystem(args, conf)
 
@@ -118,8 +119,10 @@ def run_optimization(conf, sched=None, scen=None, args=None):
 
     # filter out depot chargers if option is set
     if conf.run_only_oppb:
+        optimizer.config.exclusion_rots = optimizer.config.exclusion_rots.union(
+            r for r in sched.rotations if "depb" == sched.rotations[r].charging_type)
         sched.rotations = {r: sched.rotations[r] for r in sched.rotations
-                           if "oppb" in sched.rotations[r].vehicle_id}
+                           if "oppb" == sched.rotations[r].charging_type}
         assert len(sched.rotations) > 0, "No rotations left after removing depot chargers"
 
     # rebasing the scenario meaning simulating it again with SpiceEV and the given conditions of
@@ -187,6 +190,13 @@ def run_optimization(conf, sched=None, scen=None, args=None):
 
     # Calculation with SpiceEV is more accurate and will show if the optimization is viable or not
     logger.debug("Detailed calculation of optimized case as a complete scenario")
+
+    # Restore excluded rotations
+    for rotation_id in optimizer.config.exclusion_rots:
+        optimizer.schedule.rotations[rotation_id] = original_schedule.rotations[rotation_id]
+
+    # remove exclusion since internally these would not be simulated
+    optimizer.config.exclusion_rots = set()
     _, __ = optimizer.preprocessing_scenario(
         electrified_stations=ele_stations, run_only_neg=False)
 

tests/test_station_optimization.py

@@ -1,4 +1,4 @@
-from copy import copy
+from copy import copy, deepcopy
 import json
 from pathlib import Path
 import pytest
@@ -124,6 +124,39 @@ def test_basic_optimization(self):
         conf.solver = "spiceev"
         opt_sched, opt_scen = run_optimization(conf, sched=sched, scen=scen, args=args)
 
+    def test_schedule_consistency(self):
+        """ Test if the optimization returns all rotations even when some filters are active"""
+        trips_file_name = "trips_for_optimizer.csv"
+        sched, scen, args = self.basic_run(trips_file_name)
+        config_path = example_root / "default_optimizer.cfg"
+        conf = opt_util.read_config(config_path)
+
+        sched_impossible = deepcopy(sched)
+        # Make a single trip impossible
+        next(iter(sched_impossible.rotations.values())).trips[0].distance = 99999999
+        sched_impossible.calculate_consumption()
+        scen = sched_impossible.run(args)
+
+        amount_rotations = len(sched_impossible.rotations)
+        conf.remove_impossible_rotations = True
+        conf.run_only_oppb = False
+        opt_sched, opt_scen = run_optimization(conf, sched=sched_impossible, scen=scen, args=args)
+        assert len(opt_sched.rotations) == amount_rotations
+
+        # set a single rotation to depot
+        next(iter(sched.rotations.values())).set_charging_type("depb")
+        # and run again to make everything consistent
+        scen = sched.run(args)
+
+        amount_rotations = len(sched.rotations)
+        conf.run_only_oppb = True
+        opt_sched, opt_scen = run_optimization(conf, sched=deepcopy(sched), scen=scen, args=args)
+        assert len(opt_sched.rotations) == amount_rotations
+
+        conf.run_only_oppb = False
+        opt_sched, opt_scen = run_optimization(conf, sched=deepcopy(sched), scen=scen, args=args)
+        assert len(opt_sched.rotations) == amount_rotations
+
     def test_deep_optimization(self):
         """ Check if deep analysis finds the prepared optimal solution for the test case.