Merge pull request #98 from rl-institut/release/v.4.3

Release Offgridders v.4.4
rl-institut · Jul 9, 2020 · a6e31d7 · a6e31d7
2 parents 7b0e9db + cd1c9c5
commit a6e31d7
Show file tree

Hide file tree

Showing 21 changed files with 618 additions and 876 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -15,7 +15,30 @@ Here is a template for new release sections
 -
 ### Removed
 -
+### Fixed
+-
 ```
+## [Offgridders V4.4] - 2020-07-09
+
+### Added
+- Error message if parameter `evaluation_perspective` is not chosen correctly (#97)
+- Warning message if `fuel_price_change_annual` != 0, as calculation may be faulty (#97)
+
+### Changed
+- Added parameter `consumption_fuel_annual_kWh` to simulation outputs (#97)
+- Input template file so that it runs MCA and gives options of `evaluation_perspective` (#97)
+- If `fuel_price_change_annual` == 0, function `present_value_changing_fuel_price` is not executed and returns fuel price (#97)
+- Order of cost results in simulation outputs, as `first_investment_cost`, `operation_mantainance_expenditures` as these are not to be added to costs, expenditures and revenues to calculate the NPC (#97)
+- Formula calculating the residual value of an asset. Now, the sales revenue is translated into a present value: 
+`linear_depreciation_last_investment = last_investment / lifetime` and `capex = capex - linear_depreciation_last_investment * (number_of_investments * lifetime - project_life) / (1 + wacc) ** (project_life)` (#97)
+                )`
+### Removed
+- Removed unused function call in G2a (`genset_oem_minload`) (#97)
+
+### Fixed
+- Miscalculation of `total_demand_supplied_annual_kWh` due to wrong `evaluation_perspective` on tab `case_definitions`  (#97)
+- Function call of `present_value_changing_fuel_price` (#97)
+- Typo: Replace `operation_mantainance_expenditures` by `operation_maintenance_expenditures` (#97)
 
 ## [Offgridders V4.3] - 2020-07-02
 

diff --git a/Offgridders.py b/Offgridders.py
@@ -20,6 +20,7 @@
 import src.G0_oemof_simulate as oemof_simulate
 import src.H0_multicriteria_analysis as multicriteria_analysis
 
+
 def main():
     # Logging
     logger.define_logging(
@@ -31,8 +32,7 @@ def main():
     )
 
     logging.info(
-        "\n Coded by: Martha M. Hoffmann "
-        "\n Reiner Lemoine Institute (Berlin) \n \n "
+        "\n Coded by: Martha M. Hoffmann " "\n Reiner Lemoine Institute (Berlin) \n \n "
     )
 
     ###############################################################################
@@ -107,7 +107,7 @@ def main():
     # noisy timeseries at a project site, noise has to be included in csv data!   #
     # -----------------------------------------------------------------------------#
     # todo test and optionally delete noise function
-    process_input.apply_noise(sensitivity_experiment_s) #Applies white noise
+    process_input.apply_noise(sensitivity_experiment_s)  # Applies white noise
 
     # Calculation of grid_availability with randomized blackouts
     if settings["necessity_for_blackout_timeseries_generation"] == True:

diff --git a/inputs/test_input_template.xlsx b/inputs/test_input_template.xlsx
diff --git a/simulation_results/test/grid_availability.csv b/simulation_results/test/grid_availability.csv
diff --git a/src/A1_general_functions.py b/src/A1_general_functions.py
@@ -14,7 +14,6 @@
     plt = None
 
 
-
 def plot_results(pandas_dataframe, title, xaxis, yaxis):
     """ general function for plots"""
     if plt is not None:
@@ -26,6 +25,7 @@ def plot_results(pandas_dataframe, title, xaxis, yaxis):
         plt.show()
     return
 
+
 def define_base_capacities(oemof_results):
     capacities_base = {
         "capacity_pv_kWp": oemof_results["capacity_pv_kWp"],
@@ -39,6 +39,7 @@ def define_base_capacities(oemof_results):
     }
     return capacities_base
 
+
 def store_result_matrix(overall_results, experiment, oemof_results):
     """
     Storing results to vector and then result matrix for saving it in csv.
@@ -55,9 +56,7 @@ def store_result_matrix(overall_results, experiment, oemof_results):
                 )
             else:
                 result_series = result_series.append(
-                    pd.Series(
-                        [round(oemof_results[key], round_to_comma)], index=[key]
-                    )
+                    pd.Series([round(oemof_results[key], round_to_comma)], index=[key])
                 )
         # extend by item of demand profile
         elif key == "demand_profile":