Guidelines for the Application of Genetic Algorithm in Energy Management System

To keep up with the rising demand for electricity, renewable energy sources, including solar and wind power, are being increasingly utilized. However, grid stability is compromised by the intermittent nature of renewable energy resources. Technologies for energy storage provide a solution by enhancing system flexibility. As prosumer-based electrical systems and distributed energy resources expand, energy management systems are becoming more essential for optimizing system functionality and efficiency by coordinating the operation of various devices. This paper deals with a genetic algorithm-based energy management system consisting of PV generation, household load, electric vehicle, and energy storage system. The objective is to reduce electricity costs by defining the objective function and related constraints. The main novelty of this paper is the study of different parameters used in a genetic algorithm, and to find out the best set of parameters in terms of electricity cost reduction, that can be later used as guidelines to design similar types of systems.