Ashetehe Ahunim Abebe, Shewarega Fekadu, Bantyirga Belachew, Biru Getachew, Lakeo Samuel
Electrical and Computer Engineering, Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar, Ethiopia.
Electrical Power Systems, University Duisburg-Essen, Duisburg, Germany.
Sci Rep. 2024 Nov 26;14(1):29255. doi: 10.1038/s41598-024-80558-0.
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.
由于环境、技术和经济方面的考虑,可再生能源系统如今正变得越来越受欢迎且得到广泛应用。系统可靠且最优的经济规模是基于可再生能源的农村电气化供电系统的首要问题。一种新的斑马优化算法(ZOA)被用于基于埃塞俄比亚农村社区随机负荷曲线的可再生能源离网供电系统的优化设计及进行技术经济性能分析。对供电系统的组件进行建模,制定目标函数,并进行优化和技术经济分析,以在考虑供电中断概率(LPSP)、随机负荷曲线和太阳能组件最佳倾斜角度的情况下,使混合系统的年度总成本最小化。提出了三种离网供电系统,即光伏 - 电池(PV - BAT)、光伏 - 风力 - 电池(PV - WT - BAT)和风力 - 电池(WT - BAT),以评估不同LPSP下研究地点的最优配置。研究结果表明,光伏 - 电池(PV - BAT)系统,其最优规模为3483.161千瓦的光伏、3668个蓄电池单元(11444.160千瓦时)以及2082千瓦的转换器,在LPSP为0.044030%时,是为研究地点农村社区供电的最佳配置,年度总成本最低,为621,736.056美元,平准化度电成本为0.227063美元/千瓦时。与光伏 - 风力 - 电池(PV - WT - BAT)系统相比,其年度总成本降低了3.3%,未满足负荷(千瓦时/年)改善了1.3%。通过将所提出的ZOA与先前的研究、灰狼优化算法(GWO)和HOMER Pro软件进行比较,评估了该算法在获取农村社区基于可再生能源的供电系统最优规模方面的性能,结果发现所提出的算法在以最低年度成本找到供电系统的最优规模方面表现最佳。对于PV - BAT配置,在25次运行中确定最优配置值时,ZOA和GWO的标准差分别为14.295和36.360,这表明在确定最优规模方面,ZOA比GWO更可靠。此外,与HOMER软件结果相比,ZOA使总净现值成本降低了16.76%。