Multi-Faceted Maximization of a Microgrid- Incorporated Hybrid Photovoltaic-Wind-Battery- Diesel System in Basra, Iraq

Alsultan, Aqeel Mezher Thajeel; Bani, Nurul Aini; Muhtazaruddin, Mohd Nabil; Muhammad-Sukki, Firdaus

Abstract

Hybrid Renewable Energy Sources (HRES) in microgrids present a cost-effective option for supplying power to remote areas. This research focuses on optimizing HRES systems for Base Transceiver stations in Basra, Iraq, by using the Multiobjective Improve Salp Swarm algorithm (MOISSA) to enhance reliability, reduce energy costs, and improve energy distribution through effective design variables such as photovoltaic power, wind turbines, and battery autonomy days. Through MATLAB simulations with the MOISSA algorithm, and comparative analysis to other algorithms, the study shows a significant reduction in energy costs and a decrease in power supply probability, offering valuable design solutions for Hybrid Microgrid Systems.

Citation

Alsultan, A. M. T., Bani, N. A., Muhtazaruddin, M. N., & Muhammad-Sukki, F. (2024, October). Multi-Faceted Maximization of a Microgrid- Incorporated Hybrid Photovoltaic-Wind-Battery- Diesel System in Basra, Iraq. Presented at 2024 R10 Humanitarian Technology Conference, Kuala Lumpur, Malaysia

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 R10 Humanitarian Technology Conference
• Start Date: Oct 1, 2024
• End Date: Oct 3, 2024
• Acceptance Date: Jul 31, 2024
• Deposit Date: Oct 1, 2024
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Keywords: hybrid renewable energy sources; multiobjective salp swarm; algorithm; microgrid
• Publisher URL: https://ieeexplore.ieee.org/Xplore/home.jsp