Abstract
This paper provides a brand-new metaheuristic method that draws inspiration from COOT bird behavior, which is applied to optimize the configuration of a micro-grid consisting of a Diesel Generator (DG), Photovoltaic (PV) panels, Wind Turbine (WT), and battery storage system. The optimized configuration aims to meet the energy needs of Dakhla City in Morocco, taking into account the prevailing weather conditions in the area. Two indices, Power Supply Loss Probability Factor (LPSP) and Cost Of Electricity (COE), are improved through this algorithm. The performance of COOT algorithm in finding the optimal solution is assessed through statistical analysis and compared to well-known optimizers such as Salp Swarming Algorithms (SSA) and Gray Wolf Optimizer (GWO). The results show that the COOT algorithm outperforms other optimizers in terms of system design.
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EL Marzougui, A., Bahsine, S., Chihab, Y., Ait Nouh, F., Oukennou, A. (2024). Micro-Grid Design and Optimization Using COOT Optimization Algorithm. In: Bendaoud, M., El Fathi, A., Bakhsh, F.I., Pierluigi, S. (eds) Advances in Electrical Systems and Innovative Renewable Energy Techniques. ICESA 2023. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-031-49772-8_22
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