EPLANopt - A multi-objective optimization approach for energy scenarios

Inspecting the best future alternatives of the energy system requires particular characteristics and resolution to completely assess the challenges of the energy transition. A high temporal resolution in the modelling is required to properly catch renewable energy variability. Sector-coupling is needed to accurately evaluate the synergies between energy sectors. EPLANopt model based on EnergyPLAN software, developed by Aalborg University, has the above-mentioned features.

Eurac research has coupled the EnergyPLAN software with a multi-objective evolutionary algorithm to perform the expansion capacity optimization with a multi-objective approach. The multiobjective optimization approach allows the modelers to present the final results to the policy makers in the most transparent way enabling a participatory process for the selection of best futurealternatives fo r the energy system.

EPLANopt - EnergyPLAN Optimization - is a script to run a genetic optimization for the EnergyPLAN software developed by Aalborg University, based on the DEAP Distributed Evolutionary Algorithms in Python. The script has been developed during the RegEnMod project of Eurac Research. The main purpose of the EPLANopt model is to define solutions that satisfy minimum criteria in the analysis of various energy strategies by means of EnergyPLAN and DEAP.

The model is publicly accessible through the GNU Lesser General Public License. It is published on a public GitLab repository Eurac Research is offering consultancy services to the correct use of the EPLANopt tool. For more information, please see contacts below