Browsing by Author "DRICI, Manal"

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    Management of a multi-sources renewable energy- based power generation system = Gestion d’un system multi-sources de production électriques a énergies renouvelables
    (Université Badji Mokhtar Annaba, 2026-02-15) DRICI, Manal
    This work addresses the optimization and intelligent management of Multisource Hybrid Renewable Energy Systems (MHRES) for autonomous applications. The objective is to ensure cost-effective and reliable operation by designing an energy management framework that accounts for variability in renewable resources, dynamic load demands, and system-level integration challenges. MHRES performance depends on coordinated energy generation, storage, and distribution processes. The global efficiency of such systems results from the effective interaction of multiple energy Systems,namely photovoltaic (PV) panels, wind turbines, fuel cells (FC), electrolyzers, hydrogen tanks, and battery storage;all operating toward the final goal of sustainable and uninterrupted energy supply. The optimal management and sizing of these elements improve subsystem performance and contribute to the overall energy system efficiency at minimal cost. In this context, the optimization of hybrid energy systems is complicated by the intermittency of renewables and the nonlinear behavior of ultisource configurations. To address this complexity, this work proposes an adaptive optimization-based control strategy using several metaheuristic algorithms: Smell Agent Optimization (SAO), Modified Smell Agent Optimization (mSAO), Genetic Algorithm (GA), and Honey Badger Algorithm (HBA). Among these, the mSAO consistently demonstrates superior performance in system sizing, storage utilization, and reliability. A comparative scenario analysis is carried out under varying generation profiles and configurations. Each scenario is assessed using multi-criteria performance indicators, including generation efficiency, cost efficiency, reliability efficiency, and storage usage. The implications of these metrics on component lifespan and CO2 emissions are also evaluated. A MATLABbased implementation validates the effectiveness of the proposed optimization ramework in enhancing the performance and sustainability of MHRES under real-world constraints.