开普勒算法用于热优化经济调度的大规模系统
Sultan Hassan Hakmi1, Abdullah M Shaheen2, Hashim Alnami1
1Electrical Engineering Department, College of Engineering, Jazan University, Jazan 45142, Saudi Arabia.
Biomimetics (Basel, Switzerland)
|December 22, 2023
概括
一个新的开普勒优化算法 (KOA) 有效地降低了热和功率组合单位经济调度 (CHPUED) 问题的成本. 这种新的方法在大型电力系统中表现优于其他算法.
科学领域:
- 电力系统工程 电力系统工程
- 优化算法 优化算法
- 计算智能是一种计算智能.
背景情况:
- 热电组合单位经济调度 (CHPUED) 是一个复杂的,非凸的优化问题.
- 在电力系统中最大限度地降低生产成本,需要有效地安排热能和发电.
研究的目的:
- 设计和实施开普勒优化算法 (KOA) 来解决CHPUED问题.
- 为了应对在大型电力系统中门点影响所带来的挑战.
主要方法:
- 开发了一种以行星运动为灵感的开普勒优化算法 (KOA).
- 将KOA应用于48,96和192个单位的大型系统.
- 在192个单元系统上,比较KOA与DMOA,EVO,GWO和PSO的性能.
主要成果:
- 在48,96和192单元系统中,KOA显著降低了燃料成本.
- 在192个单位的系统中,KOA比DMOA (19.43%),EVO (17.49%),GWO (39.19%) 和PSO (62.83%) 取得了显著的改进.
- 一项可行性研究证实了KOA在维持在边界内的运营点方面的稳定性.
结论:
- 提出的开普勒优化算法 (KOA) 是解决CHPUED问题的优越方法.
- 对于具有门点效应的大型电力系统,KOA表现出高效率和稳定性.
- 与现有的优化技术相比,KOA提供了显著的成本降低和可靠的性能.
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