通过重新配置,分布式发电和电容器银行部署来提高配电系统性能
T Jayabarathi1, T Raghunathan1, N Mithulananthan2
1School of Electrical Engineering, Vellore Institute of Technology, Vellore, India.
Heliyon
|April 10, 2024
概括
本研究优化了使用灰狼优化器 (GWO) 进行重新配置和分布式发电的配电系统. GWO有效地将功率损耗降至最低,并改善各种系统中的电压配置.
科学领域:
- 电气工程 电气工程
- 电力系统工程 电力系统工程
- 优化技术 优化技术
背景情况:
- 配电系统面临电力损失和电压不稳定的挑战.
- 分布式发电 (DG) 和分流电容银行 (SCB) 的最佳放置是关键的解决方案.
- 系统重新配置为运营效率提供了进一步的改进.
研究的目的:
- 为了比较评估最佳的重新配置,DG和SCB部署,以最大限度地减少功率损失和增强电压配置.
- 为这些复杂的优化任务引入和应用灰狼优化器 (GWO) 的元启发算法.
- 为了解决较少研究的问题,即同时实施重新配置,GD和SCB部署.
主要方法:
- 使用灰狼优化器 (GWO) 算法的元启发方法被采用.
- 应用了GWO来解决一个高维,非线性,受约束的组合优化问题.
- 拟议的方法在标准IEEE 33和69bus辐射分布系统 (RDS) 和一个实际的83bus RDS上进行了测试.
主要成果:
- GWO算法在最大限度地减少功耗损失和改善电压配置方面表现出显著的有效性.
- 对比分析显示了GWO的表现与经典和其他元启发方法相比.
- 同时部署重新配置,总局和SCB取得了卓越的结果.
结论:
- 灰狼优化器 (GWO) 显示出在解决发电系统中复杂的优化问题的巨大潜力.
- 该研究验证了用于降低功率损失和改善电压的综合策略的有效性.
- 该GWO为提高发电网的性能和效率提供了一个强大的框架.
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