Hybrid Renewable Energy System Design and Economic-Environmental Analysis for Isolated Islands using HOMER Pro and Pareto-Fuzzy Optimization
Keywords:
CO₂ emission reduction, Hybrid renewable energy system (HRES), Multi-objective optimization, Net Present Cost, Pareto-FuzzyAbstract
Remote islands in Malaysia currently rely heavily on diesel generators for electricity supply, resulting in high operational costs, significant carbon dioxide (CO2) emissions, and fuel supply insecurity. Despite the abundance of solar and wind resources, improper system sizing and limited consideration of energy storage capacity frequently restrict renewable energy penetration in these regions. This study aims to develop a multi-objective sizing optimization framework to design a cost-effective and low-emission hybrid renewable energy system (HRES) comprising photovoltaic (PV) panels, wind turbines (WT), a diesel generator (DG), and a battery energy storage system (BESS). While HOMER Pro is a robust tool for generating sizing combinations, it is inherently limited to single-objective optimization based on cost minimization. To overcome this limitation, a Pareto–Fuzzy decision-making method was integrated into the analysis to perform multi-objective optimization considering both cost minimization and CO2 emission reduction. The performance of these configurations was then compared against a conventional diesel-only baseline to evaluate their overall effectiveness. Results demonstrate that the Pareto-Fuzzy optimized HRES achieves a 49% reduction in CO₂ emissions and increases the renewable fraction to 91.8% compared to the HOMER cost-optimal configuration, while incurring only marginal increases of 1.45% in Net Present Cost (NPC) and 1.44% in Levelized Cost of Energy (LCOE), highlighting an effective trade-off between economic and environmental performance. Critically, the Pareto-Fuzzy solution outperforms the diesel-only baseline in terms of cost-effectiveness while delivering significantly lower annual CO₂ emissions. Consequently, this research confirms that the integration of Pareto-Fuzzy multi-objective optimization provides a superior and more sustainable pathway for isolated HRES by achieving substantial environmental gains with negligible economic impact.