Artificial Immune System Algorithms for Microgrid Energy Management

Abstract

The integration of variable renewable energy sources (RES), such as solar and wind, into the microgrid through energy storage systems and controllable loads can destabilize the network. These factors cause power supply/demand imbalances, leading to voltage fluctuations and outages. In this article, a new optimization approach is proposed to address these challenges and to effectively manage the energy balance in microgrids. The study propose an Artificial Immune System inspired algorithm to identify optimal solutions and improve the power quality through power dispatch within the microgrid. Using the predicted renewable energy production data, the T-Cell algorithm executes calculations and sends them to a MATLAB environment for real-time simulation, which will make the system flexible in terms of dynamics and optimization of the power distribution using real-time data