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')