基于人工智能的PMU优化布局

Rachana Pandey, Dr. H. K. Verma, Dr. Arun Parakh, Dr. Cheshta Jain Khare
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引用次数: 0

摘要

电力系统的扰动研究对于保证供电的可靠性和安全性至关重要。相量测量单元(PMU)是我国电网的重要设备,安装在系统上实现对电力系统的监测和控制。通过在高采样率下进行同步测量,相量测量单元具有高精度记录快速瞬态的潜力。由于pmu在正常和异常情况下为电力系统的保护和控制提供了重要的相位信息,因此逐渐被集成到电力系统中。在网络的每个总线上放置PMU并不容易实现,要么是因为费用,要么是因为系统某些部分的通信设施有限。为了提高状态估计的鲁棒性,研究了不同的pmu放置方法。提出了独特的相量测量单元优化布置方法。由于具有完全的网络可观察性,建议的方法将确保最佳的PMU放置。所提出的算法将使用IEEE 7、9、14和24标准测试系统进行彻底测试,并将结果与现有方法进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence Based Optimal Placement of PMU
The investigation of power system disturbances is critical for ensuring the supply’s dependability and security. Phasor Measurement Unit (PMU) is an important device of our power network, installed on system to enable the power system monitoring and control. By giving synchronised measurements at high sample rates, Phasor Measurement Units have the potential to record quick transients with high precision. PMUs are gradually being integrated into power systems because they give important phasor information for power system protection and control in both normal and abnormal situations. Placement of PMU on every bus of the network is not easy to implement, either because of expense or because communication facilities in some portions of the system are limited. Different ways for placing PMUs have been researched to improve the robustness of state estimate. The paper proposes unique phasor measurement unit optimal placement methodologies. With full network observability, the suggested methods will assure optimal PMU placement. The proposed algorithm will be thoroughly tested using IEEE 7, 9, 14, and 24 standard test systems, with the results compared to existing approaches.
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