摘要
首次提出一种基于人工神经网络的无功预测和优化决策相结合的变电站电压和无功综合控制策略。根据电压发生变化的原因和变化趋势确定综合控制策略，该策略的有效性在于预测指导，将变压器分接头的调节次数降低到最少。仿真测试证明了预期的效果。在该系统中还构造了控制决策神经网络模型，可实现组合优化控制策略的灵活性。
The paper presents a new approach of substation voltage and reactive power control on the basis of the combination of artificial neural network (ANN)based reactive power forecasting and optimal decision-making.The synthetic control strategy is determined according to the reason and climate of voltage variation.The efficiency of this control strategy lies in the instruction by forecasting,thus the adjusting times of transformer taps can be reduced greatly.The paper constructs neural network model of the control strategy to implement multi-factor control,so the strategy can be regulated flexibly under the consideration of power factor,reactive power,voltage and weight syntheticaly.
出处
《电力系统自动化》
EI
CSCD
北大核心
1999年第13期10-13,共4页
Automation of Electric Power Systems
基金
国家攀登计划认知科学(神经网络)重大关键项目
关键词
变电站
ANN
电压
无功功率
自动控制
电力系统
substations reactive power and voltage synthetic and automatic control artificial neural network (ANN)
