一个经过修改的Dung Beetle优化器,用于考虑功率损失,点效应和操作约束的热电经济调度
Mahmoud Rihan1, Mohamed Ebeed2,3, Noor Habib Khan4
1Department of Electrical Engineering, Faculty of Engineering, Qena University, Qena, 83521, Egypt.
Scientific reports
|January 16, 2026
概括
修改后的泥虫优化器 (MDBO) 有效地解决了复杂的热电经济调度 (CHPED) 问题,降低了运营成本. 这种先进的算法克服了传统方法的局限性,用于改进电力系统优化.
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:
- 综合热电经济调度 (CHPED) 问题是复杂的,原因是运行约束,如功率损失 (PLs),点负载效应 (VPLE) 和禁止运行区域 (POZs).
- 有效的算法对于在电力系统中提供全球最佳解决方案至关重要.
研究的目的:
- 评估修改后的泥虫优化器 (MDBO) 解决CHPED问题,包括PLs,VPLE和POZs.
- 通过整合健身距离平衡 (FDB),混乱突变 (CM) 和自适应本地搜索方法 (ALSA) 来引入一种新的MDBO,以增强优化能力.
主要方法:
- 修改的泥甲虫优化器 (MDBO) 的开发和应用.
- 将FDB,CM和ALSA战略整合到DBO框架中.
- 在各种单位系统 (4,7,24,48个单位) 和基准测试套件 (CEC-2019) 上测试MDBO.
主要成果:
- 与传统的DBO和其他算法 (SCSO,AVOA,SCA,HHO,GWO,LCA,ZOA,WOA) 相比,MDBO在解决CHPED问题方面表现出更好的表现.
- 实现了运营成本的显著降低.
- MDBO有效地缓解了过早的收和局部最佳问题.
结论:
- 拟议的MDBO为CHPED问题提供了更有效和可靠的解决方案.
- MDBO的增强功能为复杂的电力系统挑战提供了强大的优化能力.
- 该算法始终优于现有的文献方法.
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