混合基因算法模拟的基于回火的电动汽车充电站放置,以优化分配网络弹性
Boya Anil Kumar1, B Jyothi1, Arvind R Singh2
1Department of Electrical and Electronics Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, India.
Scientific reports
|April 1, 2024
概括
这项研究优化了电动汽车充电站 (EVCS) 在太阳能电网中的位置. 混合GA-SAA方法可确保可靠的电网集成,并减少能源损失.
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
- 优化技术 优化技术
背景情况:
- 越来越多的电动汽车 (EV) 采用需要快速部署电动汽车充电站 (EVCS).
- 将EVCS集成到发电网中,特别是分布式光伏 (PV) 系统中,存在重大技术挑战.
- 减少来自运输的温室气体排放依赖于广泛使用电动汽车.
研究的目的:
- 确定插电式电动汽车充电站 (PEVCS) 的最佳位置,以便无地集成到配电网络中.
- 为了应对降低功率损失和保持光伏系统的电压稳定性的多重标准挑战.
- 通过战略EVCS和分布式发电管理,提高发电配电系统的可持续性和可靠性.
主要方法:
- 采用了混合基因算法和模拟化 (GA-SAA) 的优化方法.
- 这个问题是作为一个考虑功耗损失和电压水平目标的多标准优化任务来制定的.
- 该研究调查了各种光伏系统场景,以评估整合影响.
主要成果:
- 用GA-SAA方法成功地确定了最佳的PEVCS位置,以改善电网集成.
- 拟议的战略有效地平衡了EVCS与分布式光伏发电的整合.
- 实现了电源损耗的减少,并在配电网络中保持了可接受的电压水平.
结论:
- 使用GA-SAA方法优化的EVCS的战略布局对于将EV集成到具有光伏系统的电网中至关重要.
- 该方法通过管理EVCS和分布式发电之间的相互作用来提高配电网络的可靠性和可持续性.
- 这项研究为公用事业公司和政策制定者规划电动汽车基础设施发展提供了有价值的框架.
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