基于支持向量机的区域电网无功电压自动控制

Xiangxing Meng, Guozhong Sun, Jianxiang Li, Haibo Liu
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引用次数: 3

摘要

本文将传统的无功电压控制问题视为一个多类分类问题,提出了一种基于支持向量机(SVM)分类器的新方法。该方法根据各变电站的功率因数和电压对电网运行状态进行分类,并选择相应的控制策略来控制电容器和变压器分接。为了保证分类器在操作过程中能够持续学习,提出了一种朴素渐进学习策略。该方法适用于在线操作。决策结果鲁棒性好,可实现变电站间的协调运行。采用一个包含三个变电站的简单径向系统作为案例研究。结果表明了该方法的有效性。
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Automatic reactive power and voltage control for regional power grid based on SVM
In this paper, the traditional reactive power and voltage control problem is regarded as a multi-class classification problem, and a novel approach based on Support Vector Machine (SVM) classifier is proposed. According to the approach, the power grid operating status is classified according to the power factor and voltage at each substation and the corresponding control strategy is selected to control the capacitors and transformer taps. A naive progressive learning strategy is also presented to make sure the classifier can keep learning in the operation process. The approach is suitable for online operation. The decision results are robust and coordination operation between the substations can be achieved. A simple radial system containing three substations is used for case study. The results illustrate the effectiveness of the proposed approach.
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