Modelling and optimization of hybrid renewable energy system using SBLA-MAT algorithm

Abstract

In order to enhance the reliability and economic feasibility of power systems, this research presents a hybrid control method for the optimal design of hybrid renewable energy sources (RES), including fuel cells, solar photovoltaic (PV), and wind power. Optimization of the power system to enhance efficiency and reduce downtime is achieved using the side blotched lizard optimization with multi-objective artificial tree algorithm (SBL MAT). The research intends to reduce costs in wind, PV, and FC scenarios and make it reliable for load delivery at a low cost and high level of dependability. While a mathematical model of SBL behavior demonstrates the need to discover and implement global optimizing approaches, the MAT algorithm resolves the supervised classification challenge. Possible benefits of the proposed technology include increased reliability and decreased maintenance costs for electrical systems. The proposed approach enables cost-effective and reliable load generation from PV, wind, and fuel cell systems, regardless of the volatility of the weather. Using MATLAB/Simulink, the assessment of parameters like recall, specificity, accuracy and precision is carried out and the results were 99.91%, 99.85%, 99.65%, and 99.325%, respectively. The parameters loss of load expectation (LOLE) and loss of energy expectation (LOEE) are calculated for analysis using both current and future technology.