Merge branch 'dev' into feature/extended_prices

simba/costs.py

@@ -76,7 +76,7 @@ class Costs:
     GARAGE = "garage"
     NOT_ELECTRIFIED = "Non_electrified_station"
 
-    DAYS_PER_YEAR = 365.2422
+    DAYS_PER_YEAR = 365
 
     def __init__(self, schedule: simba.schedule.Schedule, scenario: spice_ev.scenario.Scenario,
                  args, c_params: dict):
@@ -117,6 +117,7 @@ def info(self):
         :rtype: str
         """
         cumulated = self.costs_per_gc[self.CUMULATED]
+
         return ("\nTotal costs:\n"
                 f"Investment cost: {cumulated['c_invest']} €. \n"
                 f"Annual investment costs: {cumulated['c_invest_annual']} €/a. \n"
@@ -492,11 +493,12 @@ def set_various_kpis(self):
         """
         all_stations = self.schedule.scenario["components"]["charging_stations"]
         stepsPerHour = self.scenario.stepsPerHour
-        simulated_days = max(
-            round(self.scenario.n_intervals / self.scenario.stepsPerHour / 24, 0), 1)
-        # Factor for scaling to a year.
-        # Expects Schedules to describe whole days, with some overlap allowed
-        annual_factor = self.DAYS_PER_YEAR / simulated_days
+        # factor for scaling to a year
+        scenario_duration_s = self.scenario.n_intervals * self.scenario.interval.total_seconds()
+        if scenario_duration_s > 0:
+            annual_factor = (self.DAYS_PER_YEAR * 24 * 60 * 60) / scenario_duration_s
+        else:
+            annual_factor = 0
         # get dict with costs for specific grid operator
         for gcID, gc in self.gcs.items():
             station = self.schedule.stations[gcID]

simba/simulate.py

@@ -220,7 +220,7 @@ def _station_optimization(schedule, scenario, args, i, single_step: bool):
 
     @staticmethod
     def station_optimization(schedule, scenario, args, i):
-        return Mode._station_optimization(schedule, scenario, args, i, sinlge_step=False)
+        return Mode._station_optimization(schedule, scenario, args, i, single_step=False)
 
     @staticmethod
     def station_optimization_single_step(schedule, scenario, args, i):
@@ -263,6 +263,7 @@ def split_negative_depb(schedule, scenario, args, _i):
     @staticmethod
     def report(schedule, scenario, args, i):
         if args.output_path is None:
+            logging.warning("No output path given, skipping report")
             return schedule, scenario
 
         # create report based on all previous modes

tests/test_simulate.py

@@ -1,4 +1,6 @@
 from argparse import Namespace
+from csv import DictReader
+import json
 import logging
 from pathlib import Path
 import pytest
@@ -155,6 +157,25 @@ def test_mode_report(self, tmp_path):
             warnings.simplefilter("ignore")
             simulate(args)
 
+        # get power procurement price from price sheet
+        with open(args.cost_parameters_path) as file:
+            cost_params = json.load(file)
+            procurement_price = cost_params["default_grid_operator"]["power_procurement"]["charge"]
+            # given in ct/kWh, convert to €/kWh with sign change (direction of grid power)
+            procurement_price = -procurement_price / 100
+        # read out vehicle costs, procurement price must match
+        with (tmp_path / "report_1/summary_vehicles_costs.csv").open() as csvfile:
+            reader = DictReader(csvfile)
+            for row in reader:
+                if row["parameter"] == "unit":
+                    continue
+                energy = float(row["annual_kWh_from_grid"])
+                price = float(row["c_el_procurement_annual"])
+                if energy == 0:
+                    assert price == 0
+                else:
+                    assert pytest.approx(price / energy) == procurement_price
+
     def test_empty_report(self, tmp_path):
         # report with no rotations
         args = self.get_args()