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Intelligent Hybrid Renewable Energy System Optimization for Enhanced Microgrid Resilience and Economic Viability: A Multi-Objective Approach

Authors: Soni

Published: 2025/5/2

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Abstract

This research investigates the optimal design and operation of an intelligent hybrid renewable energy system (HRES) for microgrid applications, focusing on enhancing both resilience and economic viability. A multi-objective optimization framework is developed, integrating HOMER Pro for initial system sizing and simulation with a Genetic Algorithm (GA) for refined optimization. The study considers solar photovoltaic (PV) panels, wind turbines, battery energy storage systems (BESS), and diesel generators as key components of the HRES. The objectives are to minimize the Levelized Cost of Energy (LCOE) and maximize system resilience, quantified by metrics such as Loss of Power Supply Probability (LPSP) and System Average Interruption Duration Index (SAIDI). The proposed methodology is applied to a case study representing a remote community in India. Results demonstrate that the optimized HRES configuration achieves a significant reduction in LCOE while simultaneously improving microgrid resilience compared to traditional grid-connected or diesel-only systems. The study highlights the importance of integrating intelligent optimization techniques for designing sustainable and reliable energy solutions for off-grid and grid-connected applications.

Keywords

Renewable Energy, Microgrid, Hybrid Optimization, HOMER Pro, Genetic Algorithm, Multi-Objective Optimization, Resilience, Economic Analysis, Energy Management, Smart Grid

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How to Cite

Soni, (2025/5/2). Intelligent Hybrid Renewable Energy System Optimization for Enhanced Microgrid Resilience and Economic Viability: A Multi-Objective Approach. JANOLI International Journal of Humanities and Linguistics , Volume UIh3MC5UrwhGKptS6jkQ, Issue 3.

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