基于限制混合整数编程的有效混合搜索技术,用于智能家居住宅负载调度
Esam H Abdelhameed1, Samah Abdelraheem2,3, Yehia Sayed Mohamed3
1Faculty of Energy Engineering, Aswan University, Aswan, Egypt. ehhameed@energy.aswu.edu.eg.
Scientific reports
|December 10, 2023
概括
本研究介绍了用于智能家居能源调度的混合优化技术,显著降低了电力成本并提高了用户舒适度. 该方法在动态定价和光伏电力系统下有效地管理住宅负载.
科学领域:
- 智能电网技术 智能电网技术
- 优化算法 优化算法
- 能源管理系统 能源管理系统
背景情况:
- 住宅负载调度对于最大限度地降低电力成本和提高用户舒适度至关重要.
- 现有的优化方法与智能家居 (SH) 调度问题的非凸性质作斗争.
- 动态电力定价和可再生能源的整合,如光伏 (PV) 系统增加了复杂性.
研究的目的:
- 开发和评估一种新的混合搜索技术,以优化SH住宅负载调度.
- 在各种供电场景下,最大限度地提高用户舒适性,同时最大限度地降低电费.
- 解决多目标约束混合整数优化问题的非凸性 (CP-MIP).
主要方法:
- 一种两阶段的混合搜索技术,将放松和圆 (RnR) 与元启发算法结合起来.
- 第1阶段:使用元启发学 (BPSO,SOH-PSO,JAYA,CL-JAYA) 进行放松,以找到最佳的理性解决方案.
- 第二阶段:可行解决方案的随机圆,根据使用时间 (ToU) 定价和双功率模式 (仅供电网或电网-PV) 应用.
主要成果:
- 实现了显著的电费削减:仅在电网模式下降至20.0%,在电网-光伏模式下降至56.1%.
- 综合学习JAYA算法 (CL-JAYA) 在节省成本和用户舒适性方面表现出卓越的性能.
- 拟议的混合技术有效地处理了SH能源管理的复杂性.
结论:
- 新型混合优化方法对智能家居能源调度非常有效.
- 该技术提供了实质性的经济效益,并提高了用户的满意度.
- CL-JAYA成为先进智能家居能源管理系统的领先元启发学.
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