基于TOPSIS的多目标最佳部署太阳能光伏和BESS单元在发电系统中的电动汽车负载需求
Vinod Kumar Thunuguntla1, Vijayasanthi Maineni2, Satish Kumar Injeti3
1Department of Electrical and Electronics Engineering, Vignan's LARA Institute of Technology & Science, Guntur District, Vadlamudi, 522213, Andhra Pradesh, India.
Scientific reports
|November 29, 2024
概括
该研究调查了插电式电动汽车 (PHEV) 充电对发电网的影响. 它提出了一种利用可再生能源和电池存储的优化方法,以减轻对电压和能量损失的负面影响.
科学领域:
- 电气工程 电气工程
- 电力系统 电力系统
- 整合可再生能源的整合
背景情况:
- 由于环境问题,插电式电动汽车 (PHEV) 的日益普及增加了电力需求.
- PHEV的充电会影响配电网络的参数,包括能量损耗和电压概况.
- 基于可再生能源的分布式发电 (RDG) 和电池储能系统 (BESS) 的整合旨在减轻这些影响并管理RDG的间歇性.
研究的目的:
- 分析两种PHEV充电策略 (家庭和公共快速充电) 对33辆公共汽车配电系统的技术影响.
- 研究PHEV负载对电压配置和能量损耗的影响.
- 优化光伏 (PV) 单元和PV-BESS单元的放置,以在PHEV负载条件下提高系统性能.
主要方法:
- 使用到达时间和行程距离的概率密度函数对PHEV充电需求的建模.
- 在33辆公共汽车和500辆PHEV的测试系统上实施,考虑家庭和公共快速充电场景.
- 使用基于帕雷托的多目标混沌基于速度的蝶优化算法 (MOCVBOA) 进行光伏和PV-BESS放置的优化.
主要成果:
- 量化了PHEV充电对电压配置和配电网络能量损失的影响.
- 证明了拟议的MOCVBOA算法在优化光伏和PV-BESS放置方面的有效性.
- 将MOCVBOA的性能与NSGA-II和MOBOA进行比较,显示出优越或可比的结果.
结论:
- RDG和BESS的最佳整合可以有效地减轻PHEV收费对配电网络的负面影响.
- MOCVBOA算法提供了一种有效的方法来规划可再生能源资源和储能系统在具有显著PHEV透率的电网中.
- 解决PHEV充电的不确定性对于保持稳定和高效的发电分配至关重要.
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