基于人工神经网络的电力系统电压稳定

M. Khaldi
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引用次数: 5

摘要

维持电压稳定的稳态运行是通过切换分散在电网中的各种控制器来完成的。当意外事件发生时,无论是强制的还是非强制的,调度员都要以最小的时间、成本和努力来缓解问题。持续的问题可能导致停电。调度器应根据控制器的类型、位置和大小进行适当的切换,以消除偶然性,保持电压稳定。错误的开关可能会使问题恶化,并可能导致停电。本文提出并利用人工神经网络(ANN)辅助调度员进行决策。在静态电压稳定性中,人工神经网络用于将突发事件即时映射到一组控制器,其中感应开关的类型、位置和数量。提出了拟使用的人工神经网络的类型和体系结构以及训练数据的大小。
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Power Systems Voltage Stability Using Artificial Neural Network
The steady-state operation of maintaining voltage stability is done by switching various controllers scattered all over the network. When a contingency occurs, whether forced or unforced, the dispatcher is to alleviate the problem in a minimum time, cost, and effort. Persistent problem may lead to blackout. The dispatcher is to have the appropriate switching of controllers in terms of type, location, and size to remove the contingency and maintain voltage stability. Wrong switching may worsen the problem and that may lead to blackout. This work proposed and used an artificial neural network (ANN) to assist the dispatcher in the decision making. The ANN is used in the static voltage stability to map instantaneously a contingency to a set of controllers where the types, locations, and amount of switching are induced. The work proposes the type and architecture of the ANN to be used and the training data size.
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