Metamodel-based on meta-heuristic design optimization of renewable energy microgrid

Abstract

This paper presents a study of multi-objective co-optimization using metaheuristic algorithms for a renewable energy-based microgrid. The goal is to optimize the sizing of this microgrid through the design of experiments (meta-model) technique to minimize computation time. A design of experiments is conducted with the dynamic simulator, considering ranges of variation for all parameters that will be optimized during the optimization phase. The tri-objective optimization problem is formulated with a focus on minimizing the technical criterion (LPSP), embodied energy (EE), and greenhouse gas emissions (GHG). The use of this meta-model significantly reduces the co-optimization time, particularly for environmental objectives. The study showcases an efficient approach to achieve optimal microgrid sizing, balancing performance and computational efficiency in the face of intricate environmental considerations.