Multi-Objective Optimization Algorithms for Energy Management System in Microgrids Including Control Strategy

This paper focuses on multi-objective optimization methods to address control strategies in microgrid systems. We introduce an unique problem formulation capable of processing real-time data and propose a new methodology that integrates multiple energy management constraints within a multi-objective optimization framework. Additionally, we propose a set of objective functions tailored for this optimization approach. The goal of this paper is to implement several multi-objective optimization algorithms within this strategy and use a dataset to evaluate them. This approach is applied to optimize microgrid design based on energy requirements, while conducting optimal sizing analysis accompanied by sensitivity analysis. An Energy Management System has been developed with technical functionalities that incorporate various constraints. Our findings demonstrate that the NSGA-II algorithm delivers highly promising results, achieving significant reductions in energy costs and total net present value, while maximizing energy production from sustainable sources.