Grey Relational Optimization Planning Model of Reactive Power Compensation in Distribution Network under Distributed Deep Learning Framework
The distribution network loss is high,the input cost is high,and the node power parameters are unstable.Taking the minimum network loss,the optimal voltage quality and the maximum economic benefits as the objective functions,and integra-ting the constraints of power flow,control variables and voltage constraints,a reactive power compensation planning model for distribution network is established.The grey correlation analysis method is used to determine the correlation degree.Through the deep learning neural network and the distributed deep learning framework with updated parameters,the global optimal solu-tion is obtained to complete the optimal planning of distribution network reactive power compensation.The experiment shows that the reactive power compensation mode of the distribution network can be effectively planed,reduce the network loss and input cost,improve the voltage quality,ensure the reactive power compensation effect of the distribution network,and promote the stable operation of the entire network.
deep learningreactive power compensationdistributed frameworkgrey relation
万方数据
维普
