智能配电网络中集成能源系统的强大的电力管理能力,包括线性和非线性负载
Kai Jin1, Hamed Banizaman2, Sina Samadi Gharehveran3
1Sanya Research Institute, Hunan University of Science and Technology, Sanya, 572000, China.
Scientific reports
|February 24, 2025
概括
这项研究优化了智能配电网络 (SDN) 内灵活可再生能源综合能源系统 (FRIES) 的电力管理,尽管存在不确定性,但最大限度地降低了成本,损失和波扭曲. 拟议的自适应性强大优化确保了系统的弹性,并提高了性能指标.
科学领域:
- 电气工程 电气工程
- 电力系统工程 电力系统工程
- 优化理论 优化理论
背景情况:
- 灵活可再生能源综合能源系统 (FRIES) 对现代电网至关重要.
- 智能配电网络 (SDN) 需要先进的电力管理策略.
- 非线性负载波扭曲给电源质量带来了重大挑战.
研究的目的:
- 为与SDN集成的FRIES开发一个最佳的电源管理策略.
- 为了最大限度地降低运营成本,能源损失和电压波扭曲.
- 解决可再生能源发电,负载需求和能源成本的不确定性.
主要方法:
- 制定一个决定性的多目标优化模型.
- 将非线性模型与线性模型进行近似,以有效解决问题.
- 适应性强优化的应用,以处理系统不确定性.
主要成果:
- 拟议的SDN操作能够抵御不确定性,预测错误高达45%.
- 网络性能有显著的改善:能源损耗减少8.2%,电压概况提高43.5%,和状态改善51.2%.
- 该战略有效地平衡了运营成本,能源损失和波扭曲.
结论:
- 开发的电源管理策略有效地提高了SDN中的FRIES的性能.
- 适应性强大的优化为管理可再生能源系统的不确定性提供了强大的解决方案.
- 在配电变电站保持超过0.9的功率系数是实现最佳网络性能的关键.
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