Optimal Allocation and Techno-Economic Assessment of Hybrid Energy Systems Considering Uncertainty and Reliability: A Case Study in a Remote Region

In recent years, there has been a growing interest in utilizing stand-alone renewable energy sources (RESs) in remote areas, primarily due to rising energy demand and the increasing cost of fossil fuels. This paper explores the implementation of a hybrid RES for a remote region in Iran, driven by rising energy demand and fossil fuel costs. The system combines a wind turbine, photovoltaic panels, a battery, and a diesel generator, optimized based on real load demand and simulation results. The study seeks to minimize the annualized cost of the system while addressing demand fluctuations, renewable energy uncertainty, and the loss of power supply probability. A modified particle swarm algorithm (MPSO) is used for system sizing and is compared with PSO and constriction coefficient PSO. The findings demonstrate that MPSO offers faster solutions and better cost efficiency. The optimal configuration identified is a PV/wind turbine/battery/diesel system, with a minimum cost of $3100.52. To reduce fossil fuel dependence, a cap on annual diesel consumption is implemented. Incorporating real weather data, the system meets all electric load demands and operational constraints, with an annual cost of $3974.50 and diesel consumption of 98.33 L per year.