认知模糊逻辑集成能源管理,用于自给自足的混合可再生微电网
Edel Quinn Julin M1, Vijayalakshmi Subramanian2, Victoriia Bereznychenko3
1Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Kattankulathur, 603203, Tamilnadu, India.
Scientific reports
|March 23, 2025
概括
本研究介绍了微电网的基于模糊逻辑的能源管理系统 (EMS),优化可再生能源的使用并降低成本. 与其他优化方法相比,拟议的EMS显著降低了等级能源成本 (LCOE).
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 控制系统 控制系统
背景情况:
- 微电网需要有效的能源管理,以整合可持续的资源和储存.
- 需求高峰期对能源消费监管构成挑战.
- 优化混合能源 (电网,光伏,风能,电池) 的使用对于微电网效率至关重要.
研究的目的:
- 提出一个使用微电网模糊逻辑的综合能源管理系统 (EMS).
- 通过优化可再生能源资源的利用和储存来管理能源需求.
- 提高能源供应中的系统弹性和成本效益.
主要方法:
- 实施基于模糊逻辑的能源管理系统 (EMS).
- 混合公用事业电网,光伏 (PV),风能和电池存储的整合.
- 考虑电力需求,可再生能源的可用性和电荷状态 (SoC).
- 使用火,粒子群优化 (PSO) 和遗传算法 (GA) 的成本分析进行比较.
主要成果:
- 模糊的EMS实现了比火算法低41.40%的水平化能源成本 (LCOE).
- 模糊的EMS比PSO算法更有效地减少了24.09%的费用.
- 与遗传算法相比,模糊的EMS在LCOE中显示了45.02%的降低.
结论:
- 拟议的基于模糊逻辑的EMS为微电网提供了更经济的能源解决方案.
- 该系统根据电网电力成本和安全限制,智能地选择能源.
- 电气系统有效地最大限度地提高了系统的弹性和绿色能源的利用.
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