An integrated hybrid energy sizing model for multi-objective optimization of standalone power systems

Abstract

Abstract Standalone hybrid renewable energy systems offer a practical solution for electrifying remote and underserved communities where grid extension is economically impractical. However, the intermittent nature of renewable resources and the complex interactions among system components make optimal system sizing a challenging multi-objective problem. This paper proposes an integrated hybrid energy sizing model (IHESM) for the multi-objective optimization of standalone power systems, with the objective of simultaneously minimizing the levelized cost of energy, loss of power supply probability as a reliability indicator, and total carbon emissions as an environmental performance metric. The model establishes a unified mathematical framework that captures energy balance, operational constraints, and techno-environmental performance for a hybrid configuration comprising solar photovoltaic, biomass-based generation, diesel generator backup, and pumped hydro storage. The sizing problem is formulated as a constrained multi-objective optimization task and solved using the energy valley optimizer (EVO). The proposed EVO-based IHESM is implemented for a rural standalone power system in Ikere community, Iseyin, Oyo State, Nigeria, and its performance is benchmarked against the whale optimization algorithm and genetic algorithm. Simulation results demonstrate that the EVO-optimized system achieves superior trade-offs among economic efficiency, supply reliability, and carbon emission reduction. These findings validate the proposed framework as an effective and replicable decision-support tool for planning reliable and low-carbon standalone hybrid power systems in energy-constrained regions.