利用软计算和机器学习提高电力系统安全性

Peruthambi Venkatesh, R. Scholar, N. Visali
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引用次数: 1

摘要

目的。为了保证系统的正常运行,建议的方法是通过推断单线的损耗来计算应急额定值。方法。利用机器学习和粒子群优化算法建立的数学模型,观察了有无统一潮流控制器和线间潮流控制器的稳定性分析,以及相关的成本。这样可以快速预测受影响最大的传输线和补偿的位置。结果。许多突发情况,如单条输电线路的故障和负荷的变化,都被纳入电力系统。采用单线停电和负荷波动来确定应急排序是本工作的主要重点。实用价值。为建设安全的输电系统,提出了稳定分析建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancing power system security using soft computing and machine learning
Purpose. To guarantee proper operation of the system, the suggested method infers the loss of a single transmission line in order to calculate a contingency rating. Methods. The proposed mathematical model with the machine learning with particle swarm optimization algorithm has been used to observe the stability analysis with and without the unified power flow controller and interline power flow controller, as well as the associated costs. This allows for rapid prediction of the most affected transmission line and the location for compensation. Results. Many contingency conditions, such as the failure of a single transmission line and change in the load, are built into the power system. The single transmission line outage and load fluctuation used to determine the contingency ranking are the primary emphasis of this work. Practical value. In order to set up a safe transmission power system, the suggested stability analysis has been quite helpful.
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