Implementation and analysis of soc using optimization techniques for energy management in sustainable power distribution system

Abstract

newline The rapid advancement of distributed energy storage systems, such as batteries, alongside renewable energy sources, is transforming the energy landscape swiftly. Maintaining balanced state-of-charge (SoC) levels in batteries within DC microgrids is a critical challenge in distributed energy systems. Inconsistent State of Charge (SoC) levels may lead to accelerated degradation of certain batteries, thereby diminishing the overall lifespan and performance of the system. This transition has led to various operational challenges, including maintaining energy distribution efficiency, ensuring system stability, managing battery health, and optimizing energy flow in fluctuating conditions. This thesis presents comprehensive research on advanced energy management strategies for distributed and hybrid renewable energy systems, focusing on the integration of cutting-edge machine learning and optimization algorithms with droop control methods. The increasing utilization of distributed battery systems and renewable energy sources has rendered issues such as efficient energy distribution, system reliability, and battery health management imperative.