Intelligent Predictive Control for Battery Energy Management in PV-Based Renewable Energy Systems

Abstract

In this document, an advanced intelligent energy storage management system solution for clean energy sources from solar power will be outlined through the use predictive controls. The integrated intelligent energy management architecture includes a solar panel array, battery bank, local users, two-way converter, and utility providers. Using the proposed control scheme, battery storage charging and discharging cycles will be determined based on solar generation and user load forecasts that comply with specified operating constraints (SOC, power limits, and depth of discharge). The goal of this research project is to minimize dependence on the grid as well as reduce the amount of wear-and-tear placed on the batteries due to storing and using renewable energy. After completing this study, it is expected that the findings will greatly enhance the amount of energy available to users from renewable energy sources as well as improving the reliability of these systems even during time periods when the operated equipment would normally experience significant variations in performance. This study also demonstrates how predictive battery management could assist with integrating renewable energy systems into the existing infrastructure used for producing electricity.