Oubail, Youssef
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Optimization and management of solar and wind production for standalone microgrid: a Moroccan case study El Hafydy, Mohamed; Oubail, Youssef; Benydir, Mohamed; Elmahni, Lahoussine; Alaoui My Rachid, Elmoutawakil
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i1.pp202-211

Abstract

The increasing demand for sustainable and efficient energy solutions has prompted extensive research into optimizing renewable energy sources in microgrid systems. This paper focuses on optimizing renewable energy sources within a standalone microgrid using particle swarm optimization (PSO) as the sole algorithm. The microgrid model proposed integrates photovoltaic (PV), wind, battery storage, and serves a load represented by an agricultural firm. Real-world data from Agdz in Ouarzazate, Morocco, is utilized for analysis. The primary objective is to minimize excess production from PV and wind sources when the battery reaches full charge. This research addresses the increasing demand for sustainable energy solutions by emphasizing a single optimization technique, PSO, for achieving a balanced and efficient energy generation system. The study aims to closely align energy production with load demand to reduce wastage and ensure a reliable energy supply within the microgrid. The evaluation is conducted based on the ability of the PSO algorithm to diminish the gap between total energy production and load demand. The use of the PSO algorithm resulted in a 30% reduction in excess energy, effectively mitigating unnecessary energy wastage when the battery is fully charged. This outcome highlights the algorithm's capacity to adapt and optimize energy production from primary sources to precisely align with the specific requirements of the load
Comparative analysis of MPPT techniques for photovoltaic systems: classical, fuzzy logic, and sliding mode approaches hafydy, Mohamed El; Benydir, Mohamed; Lahoussine, Elmahni; My Rachid, Elmoutawakil Alaoui; Oubail, Youssef
International Journal of Applied Power Engineering (IJAPE) Vol 14, No 3: September 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v14.i3.pp688-700

Abstract

This study presents a comprehensive comparative analysis of maximum power point tracking (MPPT) strategies for photovoltaic systems, focusing on the classical perturb and observe (P&O) method, an artificial intelligence based fuzzy logic controller (FLC), and a robust sliding mode control (SMC) technique. These methods aim to maximize power output by dynamically adapting to rapid and unpredictable environmental variations, such as changes in solar irradiance. Simulations performed the MATLAB/Simulink environment under diverse real-world scenarios demonstrate that SMC and FLC outperform the conventional P&O approach, particularly under conditions of sudden and severe environmental in fluctuations. The findings highlight the advanced controllers’ ability to sustain optimal power extraction, minimize energy losses, and maintain system stability across varying operating conditions. These results underscore the potential of SMC-based MPPT systems to enhance the efficiency and resilience of renewable energy applications, making them highly viable for deployment in real-world scenarios characterized by volatile environmental conditions.