def setup_module(m_args):
"""Run the simulation up to module E0 and save dict_values before and after evaluation"""
if os.path.exists(TEST_OUTPUT_PATH):
shutil.rmtree(TEST_OUTPUT_PATH, ignore_errors=True)
user_input = A0.process_user_arguments()
logging.debug("Accessing script: B0_data_input_json")
dict_values = B0.load_json(
user_input[PATH_INPUT_FILE],
path_input_folder=user_input[PATH_INPUT_FOLDER],
path_output_folder=user_input[PATH_OUTPUT_FOLDER],
move_copy=False,
)
logging.debug("Accessing script: C0_data_processing")
C0.all(dict_values)
logging.debug("Accessing script: D0_modelling_and_optimization")
results_meta, results_main = D0.run_oemof(dict_values)
with open(DICT_BEFORE, "wb") as handle:
pickle.dump(dict_values, handle, protocol=pickle.HIGHEST_PROTOCOL)
logging.debug("Accessing script: E0_evaluation")
E0.evaluate_dict(dict_values, results_main, results_meta)
with open(DICT_AFTER, "wb") as handle:
pickle.dump(dict_values, handle, protocol=pickle.HIGHEST_PROTOCOL)
def setup_class(m_args):
"""Run the simulation up to module E0 and prepare bus_data for E1"""
if os.path.exists(TEST_OUTPUT_PATH):
shutil.rmtree(TEST_OUTPUT_PATH, ignore_errors=True)
logging.debug("Accessing script: A0_initialization")
user_input = A0.process_user_arguments()
A1.create_input_json(input_directory=os.path.join(
user_input[PATH_INPUT_FOLDER], CSV_ELEMENTS))
logging.debug("Accessing script: B0_data_input_json")
dict_values = B0.load_json(
user_input[PATH_INPUT_FILE],
path_input_folder=user_input[PATH_INPUT_FOLDER],
path_output_folder=user_input[PATH_OUTPUT_FOLDER],
move_copy=True,
set_default_values=True,
)
logging.debug("Accessing script: C0_data_processing")
C0.all(dict_values)
logging.debug("Accessing script: D0_modelling_and_optimization")
results_meta, results_main = D0.run_oemof(dict_values)
bus_data = {}
# Store all information related to busses in bus_data
for bus in dict_values[ENERGY_BUSSES]:
# Read all energy flows from busses
bus_data.update({bus: solph.views.node(results_main, bus)})
# Pickle dump bus data
with open(BUS_DATA_DUMP, "wb") as handle:
pickle.dump(bus_data, handle, protocol=pickle.HIGHEST_PROTOCOL)
def run_simulation(json_dict, **kwargs):
r"""
Starts MVS tool simulation from an input json file
Parameters
-----------
json_dict: dict
json from http request
Other Parameters
----------------
pdf_report: bool, optional
Can generate an automatic pdf report of the simulation's results (True) or not (False)
Default: False.
display_output : str, optional
Sets the level of displayed logging messages.
Options: "debug", "info", "warning", "error". Default: "info".
lp_file_output : bool, optional
Specifies whether linear equation system generated is saved as lp file.
Default: False.
"""
welcome_text = (
"\n \n Multi-Vector Simulation Tool (MVS) V" + version_num + " " +
"\n Version: " + version_date + " " +
'\n Part of the toolbox of H2020 project "E-LAND", ' +
"Integrated multi-vector management system for Energy isLANDs" +
"\n Coded at: Reiner Lemoine Institute (Berlin) " +
"\n Contributors: Martha M. Hoffmann \n \n ")
logging.info(welcome_text)
logging.debug("Accessing script: B0_data_input_json")
dict_values = data_input.convert_from_json_to_special_types(json_dict)
print("")
logging.debug("Accessing script: C0_data_processing")
data_processing.all(dict_values)
print("")
logging.debug("Accessing script: D0_modelling_and_optimization")
results_meta, results_main = modelling.run_oemof(dict_values)
print("")
logging.debug("Accessing script: E0_evaluation")
evaluation.evaluate_dict(dict_values, results_main, results_meta)
logging.debug("Convert results to json")
epa_dict_values = data_parser.convert_mvs_params_to_epa(dict_values)
output_processing.select_essential_results(epa_dict_values)
json_values = output_processing.store_as_json(epa_dict_values)
return json.loads(json_values)
def run_parts(margs):
if os.path.exists(TEST_OUTPUT_PATH):
shutil.rmtree(TEST_OUTPUT_PATH, ignore_errors=True)
user_input = A0.process_user_arguments()
logging.debug("Accessing script: B0_data_input_json")
dict_values = B0.load_json(
user_input[PATH_INPUT_FILE],
path_input_folder=user_input[PATH_INPUT_FOLDER],
path_output_folder=user_input[PATH_OUTPUT_FOLDER],
move_copy=False,
)
logging.debug("Accessing script: C0_data_processing")
C0.all(dict_values)
logging.debug("Run parts of D0_modelling_and_optimization")
model, dict_model = D0.model_building.initialize(dict_values)
model = D0.model_building.adding_assets_to_energysystem_model(
dict_values, dict_model, model)
return dict_values, model, dict_model
def main(**kwargs):
r"""
Starts MVS tool simulations.
Other Parameters
----------------
overwrite : bool, optional
Determines whether to replace existing results in `path_output_folder`
with the results of the current simulation (True) or not (False).
Default: False.
pdf_report: bool, optional
Can generate an automatic pdf report of the simulation's results (True) or not (False)
Default: False.
input_type : str, optional
Defines whether the input is taken from the `mvs_config.json` file
("json") or from csv files ('csv') located within
<path_input_folder>/csv_elements/. Default: 'json'.
path_input_folder : str, optional
The path to the directory where the input CSVs/JSON files are located.
Default: 'inputs/'.
path_output_folder : str, optional
The path to the directory where the results of the simulation such as
the plots, time series, results JSON files are saved by MVS E-Lands.
Default: 'MVS_outputs/'
display_output : str, optional
Sets the level of displayed logging messages.
Options: "debug", "info", "warning", "error". Default: "info".
lp_file_output : bool, optional
Specifies whether linear equation system generated is saved as lp file.
Default: False.
"""
welcome_text = (
"\n \n Multi-Vector Simulation Tool (MVS) V" + version_num + " " +
"\n Version: " + version_date + " " +
'\n Part of the toolbox of H2020 project "E-LAND", ' +
"Integrated multi-vector management system for Energy isLANDs" +
"\n Coded at: Reiner Lemoine Institute (Berlin) " +
"\n Contributors: Martha M. Hoffmann \n \n ")
logging.debug("Accessing script: A0_initialization")
user_input = A0.process_user_arguments(welcome_text=welcome_text, **kwargs)
# Read all inputs
# print("")
# # todo: is user input completely used?
# dict_values = data_input.load_json(user_input[PATH_INPUT_FILE ])
move_copy_config_file = False
if user_input[INPUT_TYPE] == CSV_EXT:
logging.debug("Accessing script: A1_csv_to_json")
move_copy_config_file = True
A1.create_input_json(input_directory=os.path.join(
user_input[PATH_INPUT_FOLDER], CSV_ELEMENTS))
logging.debug("Accessing script: B0_data_input_json")
dict_values = B0.load_json(
user_input[PATH_INPUT_FILE],
path_input_folder=user_input[PATH_INPUT_FOLDER],
path_output_folder=user_input[PATH_OUTPUT_FOLDER],
move_copy=move_copy_config_file,
set_default_values=True,
)
F0.store_as_json(
dict_values,
dict_values[SIMULATION_SETTINGS][PATH_OUTPUT_FOLDER_INPUTS],
MVS_CONFIG,
)
print("")
logging.debug("Accessing script: C0_data_processing")
C0.all(dict_values)
F0.store_as_json(
dict_values,
dict_values[SIMULATION_SETTINGS][PATH_OUTPUT_FOLDER],
JSON_PROCESSED,
)
if "path_pdf_report" in user_input or "path_png_figs" in user_input:
save_energy_system_graph = True
else:
save_energy_system_graph = False
print("")
logging.debug("Accessing script: D0_modelling_and_optimization")
results_meta, results_main = D0.run_oemof(
dict_values,
save_energy_system_graph=save_energy_system_graph,
)
print("")
logging.debug("Accessing script: E0_evaluation")
E0.evaluate_dict(dict_values, results_main, results_meta)
logging.debug("Accessing script: F0_outputs")
F0.evaluate_dict(
dict_values,
path_pdf_report=user_input.get("path_pdf_report", None),
path_png_figs=user_input.get("path_png_figs", None),
)
return 1
def run_simulation(json_dict, epa_format=True, **kwargs):
r"""
Starts MVS tool simulation from an input json file
Parameters
-----------
json_dict: dict
json from http request
epa_format: bool, optional
Specifies whether the output is formatted for EPA standards
Default: True
Other Parameters
----------------
pdf_report: bool, optional
Can generate an automatic pdf report of the simulation's results (True) or not (False)
Default: False.
display_output : str, optional
Sets the level of displayed logging messages.
Options: "debug", "info", "warning", "error". Default: "info".
lp_file_output : bool, optional
Specifies whether linear equation system generated is saved as lp file.
Default: False.
"""
display_output = kwargs.get("display_output", None)
if display_output == "debug":
screen_level = logging.DEBUG
elif display_output == "info":
screen_level = logging.INFO
elif display_output == "warning":
screen_level = logging.WARNING
elif display_output == "error":
screen_level = logging.ERROR
else:
screen_level = logging.INFO
# Define logging settings and path for saving log
logger.define_logging(screen_level=screen_level)
welcome_text = (
"\n \n Multi-Vector Simulation Tool (MVS) V" + version_num + " " +
"\n Version: " + version_date + " " +
'\n Part of the toolbox of H2020 project "E-LAND", ' +
"Integrated multi-vector management system for Energy isLANDs" +
"\n Coded at: Reiner Lemoine Institute (Berlin) " +
"\n Reference: https://zenodo.org/record/4610237 \n \n ")
logging.info(welcome_text)
logging.debug("Accessing script: B0_data_input_json")
dict_values = B0.convert_from_json_to_special_types(json_dict)
print("")
logging.debug("Accessing script: C0_data_processing")
C0.all(dict_values)
print("")
logging.debug("Accessing script: D0_modelling_and_optimization")
results_meta, results_main = D0.run_oemof(dict_values)
print("")
logging.debug("Accessing script: E0_evaluation")
E0.evaluate_dict(dict_values, results_main, results_meta)
logging.debug("Convert results to json")
if epa_format is True:
epa_dict_values = data_parser.convert_mvs_params_to_epa(dict_values)
json_values = F0.store_as_json(epa_dict_values)
answer = json.loads(json_values)
else:
answer = dict_values
return answer