Energy management and optimal sizing of a standalone hybrid renewable energy system PV/battery/diesel generator

Abstract

Providing electricity to rural towns that are disconnected from the grid and suffer from a shortage of energy, where development of the distribution network is neither possible or economically viable, needs the adoption of suitable technologies. Microgrids powered by hybrid renewable energy sources are becoming more prevalent, and they provide an exciting opportunity to electrify distant places. Stand-alone microgrids powered by hybrid renewable energy sources are an economical way to assure system dependability and energy security. In this project, a stand-alone hybrid system comprising Photovoltaic (PV), battery storage and Diesel Generator (DG) is considered. A rule-based algorithm for energy management is used to optimize the usage of renewable resources and limit the use of the battery bank and DG in order to satisfy a certain demand and minimize the Cost of Energy (COE). The proper size of this hybrid system is a critical factor affecting the performance of this system. The COE and Loss of Power Supply Probability (LPSP) are the main objectives of this project, and they are also taken as indicators for the reliability and feasibility of the proposed system. It is proposed in this dissertation to use Particle Swarm Optimization (PSO) and Gray Wolf Optimization (GWO) to fine-tune the ideal size of the system in order to fulfil the project's goals and objectives. The suggested values of LPSP that implemented in this study were 0%, 1%, and 2%. The results obtained based on these values gave more flexibility in choosing the suitable system among the three options that have been presented. The collected findings demonstrate that the suggested techniques deliver the most optimum configuration of the hybrid system. It has provided the fast and effective achievement of the ideal solution as well as a reduction of the total COE with a desired value of LPSP. These optimization algorithms were conducted using MATLAB coding. This hybrid system can be a suitable model to electrify remote areas and recommend it as solar radiation is an abundant resource.