Optimizing Grid-Dependent Hybrid Renewable Energy System with the African Vultures Optimization Algorithm | ||||
| SVU-International Journal of Engineering Sciences and Applications | ||||
| Volume 5, Issue 1, June 2024, Page 89-98 PDF (1.39 MB) | ||||
| Document Type: Original research articles | ||||
| DOI: 10.21608/svusrc.2023.240888.1153 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Montaser Abdelsattar   ; Abdelgayed Mesalam; Adelrahman Fawzi; I. Hamdan
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| Electrical Engineering Department, Faculty of Engineering, South Valley University, Qena 83523, Egypt | ||||
| Abstract | ||||
| Countries aiming to achieve their sustainable development goals recognize the significance of adopting hybrid power systems to ensure access to clean, dependable, and cost-effective energy. In this study, an african vultures optimization algorithm (AVOA) is introduced for the efficient design of a grid-tied hybrid renewable energy (HRE) system that incorporates wind turbines, photovoltaic (PV) panels, and energy storage through batteries. The system is meticulously designed to ensure the provision of clean, dependable, and cost-effective energy through the utilization of HRE systems. Because of the complex and non-linearity of the sizing problem, AVOA, being an efficient metaheuristic approach, presents a promising solution. An empirical case study is presented, focusing on an HRE system introduced in the Zafarana region of Egypt. This case study serves as an evaluation of the effectiveness of the proposed optimizer. This study will provide valuable insights for decision-makers in Egypt, offering a practical solution to enhance the integration of intermittent renewable systems and ensure a continuous and reliable energy supply. The results achieved through AVOA are compared with those obtained using the particle swarm optimization (PSO) algorithm for evaluation. Simulation results validate the superior of the AVOA over the PSO, showing its potential to deliver promising results. | ||||
| Keywords | ||||
| Hybrid renewable energy system; Cost of energy; Carbon emissions; Loss of power supply probability; African vultures optimization algorithm | ||||
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