run_model_example.py

"""
oemof application for research project quarree100

Copyright (c) 2018 Quarree100 AB-3 Project-Team

SPDX-License-Identifier: GPL-3.0-or-later
"""

import setup_solve_model
import postprocessing
import os
import pprint as pp
import oemof.solph as solph
import oemof.outputlib as outputlib
import logging
from customized import add_contraints
from matplotlib import pyplot as plt


# getting path to data from ini file
# path_to_data = os.path.join(os.path.expanduser("~"),
#                            cfg.get('paths', 'data'))

# getting path to data from IFAM owncloud
path_to_data = 'ownCloud/FhG-owncloud-Quarree-AB3/oemof_AB1/Daten/'

# selecting input scenario file
filename = os.path.join(
    os.path.expanduser("~"), path_to_data, 'AB1_Basecase_v12.xlsx')

# reading data from excel file with data read function
node_data = setup_solve_model.nodes_from_excel(filename)

# setting up energy system
e_sys = setup_solve_model.setup_es(excel_nodes=node_data)

# optimising the energy system
# e_sys = setup_solve_model.solve_es(energysystem=e_sys, excel_nodes=node_data)

# ###########Optimise the energy system#######################################
logging.info('Optimise the energy system')

# initialise the operational model
om = solph.Model(e_sys)

# Global CONSTRAINTS: CO2 Limit
add_contraints.emission_limit_dyn(
    om, limit=node_data['general']['emission limit'][0])

logging.info('Solve the optimization problem')
# if tee_switch is true solver messages will be displayed
om.solve(solver='cbc', solve_kwargs={'tee': False})

# plot the Energy System
try:
    import pygraphviz
    import graph_model as gm
    from oemof.graph import create_nx_graph
    import networkx as nx
    grph = create_nx_graph(e_sys)
    pos = nx.drawing.nx_agraph.graphviz_layout(grph, prog='neato')
    gm.plot_graph(pos, grph)
    plt.show()
    logging.info('Energy system Graph OK')
except ImportError:
    logging.info('Module pygraphviz not found: Graph was not plotted.')

logging.info('Store the energy system with the results.')
# add results to the energy system to make it possible to store them.
e_sys.results['main'] = outputlib.processing.results(om)
e_sys.results['meta'] = outputlib.processing.meta_results(om)

# store energy system with results
# e_sys.dump(dpath=path_to_results, filename='results_val_1')

# plot the buses
# postprocessing.plot_buses(res=e_sys.results['main'], es=e_sys)

# print the solver results
print('********* Meta results *********')
pp.pprint(e_sys.results['meta'])
print('')


def print_buses(res=None, es=None):

    l_buses = []

    for n in es.nodes:
        type_name =\
            str(type(n)).replace("<class 'oemof.solph.", "").replace("'>", "")
        if type_name == "network.Bus":
            l_buses.append(n.label)

    for n in l_buses:
        print(outputlib.views.node(res, n)['sequences'].sum(axis=0))


print_buses(res=e_sys.results['main'], es=e_sys)

print('Total Emission [kg]')
print(om.total_emissions())

# plot the investments in transformer
# postprocessing.plot_trans_invest(res=e_sys.results['main'], es=e_sys)
#
# # plot the storage SoC(t)
# postprocessing.plot_storages_soc(res=results, es=e_sys)
#
# # plot the installed storage capacities
# postprocessing.plot_storages_invest(res=results, es=e_sys)
#
# # expoprt the results to excel
# postprocessing.export_excel(res=results, es=e_sys)