一个基于黄金的虚拟发电厂的最佳运行和优化,涉及可再生资源
Anubhav Kumar Pandey1,2, Chaima Mansour3, Nandini K K4
1Department of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Scientific reports
|July 7, 2025
概括
这项研究优化了虚拟发电厂 (VPP) 运行,使用一种新的自然灵感算法,降低了可再生能源整合的成本和排放. 在VPP系统有效地减少对化石燃料的依赖.
科学领域:
- 能源系统工程 能源系统工程
- 优化算法 优化算法
- 整合可再生能源的整合
背景情况:
- 越来越依赖化石燃料,需要更清洁的能源解决方案.
- 虚拟发电厂 (VPP) 提供了一个整合各种可再生能源的框架.
- 优化VPP运营对于经济可行性和环境可持续性至关重要.
研究的目的:
- 为了确定虚拟发电厂 (VPP) 系统的最佳运行.
- 为了降低运营成本和温室气体排放.
- 加强太阳能,风能和水电等可再生能源的整合.
主要方法:
- 一个包含小型水力发电,风力轮机,太阳能光伏,燃料电池和联合发电单元的VPP系统被建模.
- 包括灵活的储能解决方案,包括电动汽车和专用储能系统.
- 基于金的优化算法用于单个和多个目标的优化.
- 进行了前一天的调度,并将结果与现有算法进行了比较.
主要成果:
- 拟议的VPP系统实现了成本降低2.1%和0.62%,相比Salp群和白的鱼算法,分别.
- 与鱼群和白算法相比,排放量减少了2.12%和1.18%.
- 基于金的优化表现出优越的融合行为和减少的计算时间.
- 基于帕雷托的方法进一步缩短了成本/排放权衡,证实了系统的有效性.
结论:
- 基于金的优化提供了优化VPP操作的有效方法.
- 开发的VPP系统成功地降低了成本和排放,同时增加了可再生能源的利用率.
- 该方法为可持续和高效的能源管理提供了一个有希望的解决方案.
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