outputs={bus_el: Flow(variable_costs=100000)})
# ## Add all to the energysystem
energysystem.add(bus_coal, bus_gas, bus_el, source_gas, source_coal, wind, pv,
demand_el, pp_coal, storage_el, excess_el, shortage_el)
# ## Create an Optimization Model and solve it
# create optimization model based on energy_system
optimization_model = Model(energysystem=energysystem)
# solve problem
optimization_model.solve(solver=solver)
# ## Get results
results_main = outputlib.processing.results(optimization_model)
results_meta = outputlib.processing.meta_results(optimization_model)
params = outputlib.processing.parameter_as_dict(energysystem)
# ## Pass results to energysystem.results object before saving
energysystem.results['main'] = results_main
energysystem.results['meta'] = results_meta
energysystem.params = params
# ## Save results - Dump the energysystem (to ~/home/user/.oemof by default)
# Specify path and filename if you do not want to overwrite
energysystem.dump(dpath=None, filename=None)
print(results_meta)
sequences_el = outputlib.views.node(results_main, 'electricity')['sequences']
print(sequences_el.head())
optimization_model = Model(energysystem=energysystem)
# solve problem
optimization_model.solve(solver=solver,
solve_kwargs={
'tee': True,
'keepfiles': False
})
# write back results from optimization object to energysystem
energysystem.results['main'] = outputlib.processing.results(optimization_model)
energysystem.results['meta'] = outputlib.processing.meta_results(
optimization_model)
energysystem.results['param'] = outputlib.processing.parameter_as_dict(
optimization_model)
# ################################ results ################################
# subset of results that includes all flows into and from electrical bus
# sequences are stored within a pandas.DataFrames and scalars e.g.
# investment values within a pandas.Series object.
# in this case the entry data['scalars'] does not exist since no investment
# variables are used
# data = views.node(optimization_model.results(), 'bel')
results = outputlib.processing.results(optimization_model)
string_results = outputlib.views.convert_keys_to_strings(results)
# dump energysystem (to ~/home/user/.oemof by default)
energysystem.dump(dpath=abs_path, filename='energysystem.dump')
