Optimal design of off-grid hybrid system using a new zebra optimization and stochastic load profile - Ahunim Abebe Ashetehe; Fekadu Shewarega; Belachew Bantyirga; Getachew Biru; Samuel Lakeo (Scientific Reports)
Abstract Renewable energy systems are becoming more and more popular and used these days as a result of environmental, technical, and economic concerns. The reliable and optimal economic size of the system is the primary issue with the renewable energy-based power supply system for rural electrification. A new Zebra optimization algorithm (ZOA) is used for the optimal design and to perform the techno-economic performance analysis of the renewable energy-based off-grid power supply system with the stochastic load profile of Ethiopian rural communities. The components of the power supply system are modeled, the objective function is formulated, and optimization and techno-economic analysis are performed to get the minimum total annual cost of the hybrid system with the consideration of loss of power supply probability (LPSP), stochastic load profile and solar module optimal tilt angle. Three off-grid power supply systems, such as PV-BAT, PV-WT-BAT, and WT-BAT, are proposed to evaluate the optimal configuration for the study site at various LPSP. The study’s findings showed that the photovoltaic-battery (PV-BAT) system, with an optimal size of 3483.161 kW of PV, 3668 units of storage batteries (11,444.160 kWh), and 2082 kW of converter at 0.044030% LPSP, is the best configuration for electrifying the rural communities of the study site with the minimum annual total cost of 621,736.056 USD and 0.227063 $/kWh COE. It results in a 3.3% annual total cost reduction and a 1.3% unmet load (kWh/year) improvement as compared to the PV-WT-BAT system. The performance of the proposed ZOA in obtaining the optimal size of the renewable energy-based power supply system for rural communities is evaluated by comparing it with the previous studies, gray wolf optimization (GWO) and HOMER Pro software, and it was found that the proposed algorithm is best at finding the optimal size of the power supply system at the minimum annual cost. The standard deviation for ZOA and GWO, respectively, in determining the optimal configuration value for 25 runs is 14.295 and 36.360 for the PV-BAT configuration, indicating that ZOA is more reliable than GWO in determining the optimal size. Furthermore, ZOA yields a 16.76% reduction in the total net present cost when compared to the HOMER software results.