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The Control Strategy for Optimization of Voltage and Reactive Power in Substation Based on Load Forecasting

机译:基于负载预测的变电站电压和无功功率优化控制策略

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In order to avoid some phenomena such as too many regulating times of on load tap changer, too frequent actions of capacitor switching, lower bus voltage qualification rate and higher network loss, it is presented that a control strategy for optimization of voltage and reactive power in substation based on load forecasting in this paper. The load and system voltage forecasting are realized by using radical basis function neural network. With the times of equipments' actions and the voltage quality as constraint conditions, the optimization objective function of the minimum system loss is established. The initial subsection load is based on apparent power fully compensated by the existing compensation capacitors. According to the subsection principle that voltage quality should be as high as possible, the tap position of transformer is determined. According to the initial optimization results, the reactive power is used as subsection load by the principle of as much as possible compensation. The best amount of groups of compensation capacitor is determined in the secondary subsection optimization. The application of 35kV distribution system in Yucheng County of Henan Province is analyzed in this paper. The voltage quality, the equipments' actions number limit, the maximum reducing system network loss can be achieved.
机译:为了避免一些现象,如载荷抽头更换器的太多调节时间,电容器切换的频繁常规,较低的总线电压资格率和更高的网络损耗,介绍了用于优化电压和无功功率的控制策略基于本文负荷预测的变电站。利用自由基基函数神经网络实现负载和系统电压预测。随着设备行动的时间和电压质量作为约束条件,建立了最小系统损耗的优化目标函数。初始子部分负载基于现有补偿电容完全补偿的表观功率。根据电压质量应尽可能高的分段原则,确定变压器的敲击位置。根据初始优化结果,通过尽可能多的补偿,无功功率用作子部分负载。在二级子部分优化中确定了最佳的补偿电容组。本文分析了河南省豫城县35kV分配系统。电压质量,设备的动作号限制,可以实现最大减少系统网络损耗。

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