Optimization of Grid-Connected Microgrids with Residential Prosumers Using an Improved Genetic Algorithm

Abstract

With the continuous increase of the microgrids’ implementation into the power system the problem of maintaining their stability and balance arises and the necessity to adopt an appropriate energy management system emerges. This paper analyses the optimization of the grid-connected microgrid, which consists of a photovoltaic generator, a wind generator, a battery, and residential prosumers. The paper presents the application of an improved genetic algorithm, which takes into consideration the voltage levels on the connection points of the generators and the prosumers, as well as the trading with the local grid. The proposed algorithm suggests the usage of the standard genetic algorithm with the improvement in the fitness and selection process. The results of the simulation are compared with the results obtained when using a standard genetic algorithm with five different types of selection.