使用修改后的灰狼优化和ETAP进行最佳分布式发电配置和尺寸调整,以提高电力系统性能和适应保护
Nasreddine Bouchikhi1, Fethi Boussadia1, Riyadh Bouddou2
1Department of Electrical Engineering, Mechatronics Laboratory (LMETR), University of Setif 1, 19000, Sétif, Algeria.
Scientific reports
|April 22, 2025
概括
本研究介绍了一种混合优化技术,用于将分布式发电 (DG) 集成到发电网中. 该方法有效地最大限度地减少功率损失,提高电压稳定性,同时适应保护系统的故障电流变化.
科学领域:
- 电气工程 电气工程
- 电力系统 电力系统
- 优化算法 优化算法
背景情况:
- 分布式发电 (DG) 集成对于提高发电网 (EDN) 性能,电力质量和可靠性至关重要.
- 为了最大限度地发挥效益并减轻电压不稳定性和保护系统挑战等潜在问题,GD单位的最佳位置和尺寸至关重要.
- 现有的优化方法在处理复杂的多式联运问题和避免 DG 集成研究中的局部最佳时可能面临局限性.
研究的目的:
- 开发和评估一种混合技术,将修改后的灰狼优化 (MGWO) 算法与ETAP软件集成,以实现最佳的GD配置和大小.
- 为了最大限度地减少主动和反应功率损失 (APL和RPL) 并改善EDN中的电压稳定性 (VS).
- 分析总局集成对断裂电流变化的影响,并确保保护系统的适应性.
主要方法:
- 一个改进的灰狼优化 (MGWO) 算法,具有适应性权重和动态循环,被开发来改善勘探和开发平衡.
- 该MGWO算法与MATLAB和电气短暂分析程序 (ETAP) 集成,用于安全分析和最佳的GD放置/大小.
- 在IEEE 33 总线和 114 总线配送网络上进行模拟,并使用牛顿-拉普森方法进行负载流分析.
主要成果:
- 拟议的MGWO-ETAP方法实现了功率损耗的显著降低 (在33公交系统中高达69.7%,在114公交系统中高达65.2%的APL) 和增强的电压稳定性 (在33公交系统中7.3%,在114公交系统中6.5%).
- 总局的整合导致了相当大的故障电流变化,最大故障电流 (I_max) 增加了高达21.5%,需要调整保护策略.
- 在降低功耗损失和保持系统稳定方面,MGWO-ETAP技术优于传统和先进的元启发算法.
结论:
- 混合MGWO-ETAP技术提供了一种有效的整体解决方案,可以优化GD的位置和尺寸,同时确保适应性保护控制.
- 这种方法确保了GD可靠和高效地集成到复杂的电力系统中,解决与功率损失,电压稳定性和故障电流相关的挑战.
- 该研究强调了在整合总局单位时考虑保护系统适应性的重要性,以保持整体网络安全性和性能.
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