连接到电网的光伏/风能混合可再生能源系统与电池和超级电容器存储的最佳尺寸化 一个统计验证元启发式算法性能算法的统计验证
Mohamed Mahmoud Samy1, Aykut Fatih Güven2
1Department of Electrical Engineering, Beni-Suef University, Beni-Suef, Egypt. Mohamed.samy@eng.bsu.edu.eg.
Scientific reports
|December 29, 2025
概括
这项研究使用元启发式算法优化了混合可再生能源系统. 饥饿游戏搜索算法被证明是最有效的,大大降低了大学校园的能源成本.
科学领域:
- 能源系统工程 能源系统工程
- 优化算法 优化算法
- 可持续能源 可持续能源
背景情况:
- 对化石燃料日益增长的环境和经济担忧推动了向可再生能源的转变.
- 混合可再生能源系统 (HRES) 的最佳设计对于可持续和成本效益的发电至关重要.
研究的目的:
- 为了优化电网连接的HRES的尺寸,包括光伏电池板,风力轮机,电池和超级电容器.
- 尽量减少系统的年度成本 (ACS),同时最大限度地提高可再生能源的利用率和效率.
主要方法:
- 为HRES优化开发了一个数学模型.
- 应用并统计验证了五种元启发式算法:饥饿游戏搜索 (HGS),蜘蛛黄蜂优化器 (SWO),开普勒优化算法 (KOA),火优化器 (FHO) 和冠状病毒疾病优化算法 (COVIDOA).
- 使用土耳其大学校园的真实气象和负载数据测试了该模型.
主要成果:
- 饥饿游戏搜索 (HGS) 算法产生了最好的表现.
- 实现了603,538.44美元的年度系统成本 (ACS),0.23801美元/千瓦时的能源成本 (COE) 和80.04%的可再生能源部分 (REF).
- 与电网电力相比,显示出显著的经济效益 (0.35美元/千瓦时).
结论:
- 优化的HRES对于大型消费者来说在商业上是可行的.
- 超启发式算法是混合能源系统设计的有效工具.
- 该研究为未来能源系统优化研究提供了经过验证的框架.
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