Differential Energy-saving and Loss-reducing Method for Distribution Network Based on Improved Artificial Neural Network Algorithm
In order to solve the problem that the loss of the distribution network is large due to the blind selection of energy-sav-ing and loss-reducing measures,a differentiated energy-saving and loss-reducing method for the distribution network based on the improved artificial neural network algorithm is studied.It sets a reasonable operating voltage as the upper-level planning target,establishes a differentiated energy-saving and loss-reduction planning model for the distribution network,and sets safe load constraints,current over-limit constraints,and reactive power compensation equipment constraints as the basis of the dif-ferentiated energy-saving and loss-reduction planning model for the distribution network.The adaptive genetic algorithm is used to improve the artificial neural network algorithm.For different lines of the distribution network,the improved artificial neural network algorithm is used to solve the differentiated energy-saving and loss-reducing planning model of the distribution net-work,and obtain the energy-saving and loss-reducing methods that can make the distribution network differentiated.It can ob-tain the optimal distribution network operating parameters to match the differentiated energy-saving and loss-reducing scheme of the distribution network.The experimental results show that the active power loss and reactive power loss of each branch are significantly reduced,and the network loss rate of each branch of the distribution network is less than 1％.
artificial neural networkdistribution networkenergy saving and loss reductionconstraints
万方数据
维普
