MOEA for energy scenario optimization

This repository reproduces a few case studies on multi-objective optimization of multi-energy systems developed by members of the Sustainable Energy Centre at the Bruno Kessler Foundation.

The case studies reproduced here rely on the EnergyPLAN software, a simulator of the operation of national energy systems on an hourly basis, including the electricity, heating, cooling, industry, and transport sectors.

Multi-objective optimization algorithms are developed using PyMOO, a framework implementing state of the art single- and multi-objective optimization algorithms and many more features related to multi-objective optimization such as visualization and decision making.

Reading guide

• The Get started page shows how to initialize a Python environment, and optimize a case study from the command line.

• An in-depth guide to the declaration of models and the use of the optimizer is provided in the Usage section.

• The Documentation page provides a complete guide of the available models and algorithms.

• A collection of case studies help to get familiar with the use of the optimization suite.