使用新的斑马优化和随机负载配置文件的离网混合系统的最佳设计
Ahunim Abebe Ashetehe1, Fekadu Shewarega2, Belachew Bantyirga3
1Electrical and Computer Engineering, Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar, Ethiopia. ahunim@gmail.com.
Scientific reports
|November 25, 2024
概括
一个新的斑马优化算法 (ZOA) 有效地设计了埃塞俄比亚农村的离网可再生能源系统. 光伏电池 (PV-BAT) 系统被证明是最具成本效益的,总成本降低了3.3%,未满足负载提高了1.3%.
科学领域:
- 可再生能源系统可再生能源系统
- 优化算法 优化算法
- 技术经济分析 技术经济分析
背景情况:
- 由环境,技术和经济因素驱动的可再生能源需求不断增长.
- 用可再生能源实现农村电气化的可靠和经济最佳尺寸的挑战.
- 需要先进的算法来解决随机负载配置文件和系统设计复杂性的问题.
研究的目的:
- 开发和评估一个新的斑马优化算法 (ZOA) 以实现离网可再生能源系统的最佳设计和技术经济分析.
- 确定以埃塞俄比亚农村电气化最具成本效益的系统配置,考虑随机负载配置和电力供应损失概率 (LPSP).
- 将ZOA的性能和可靠性与现有的方法比较,例如灰狼优化 (GWO) 和HOMER Pro软件.
主要方法:
- 电源系统组件 (光伏,电池,转换器,风力轮机) 的建模.
- 制定一个客观的功能,以尽量减少年度总成本,考虑到LPSP和最佳的太阳能模块倾斜角度.
- 应用斑马优化算法 (ZOA) 来分析三种离网系统配置:PV-BAT,PV-WT-BAT和WT-BAT.
主要成果:
- 光伏电池 (PV-BAT) 系统被确定为最佳配置,需要3483.161千瓦的光伏,3668个电池单元 (11,444.160千瓦时) 和2082千瓦的转换器在0.044030%LPSP.
- 最优的PV-BAT系统实现了最低年总成本为621,736,056美元,能源成本 (COE) 为0.227063美元/千瓦时.
- 与HOMER软件相比,ZOA表现出卓越的性能,实现了总净当前成本的16.76%的降低,并且显示出比GWO更高的可靠性 (较低的标准偏差).
结论:
- 拟议的ZOA是一种可靠和有效的算法,用于优化农村电气化的基于可再生能源的电力供应系统的尺寸和技术经济性能.
- 对于被研究的埃塞俄比亚农村社区,PV-BAT系统配置提供了最经济,最有效的解决方案.
- 与已有的优化工具和算法相比,ZOA提供了显著的成本降低和性能改进.
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