Application of DG-RBFNN in Power Flow Calculation of Distribution Network with DG

Abstract

With the injection of distributed generation (DG) into distribution network, complexity and uncertainty of power flow in distribution network follow. In order to calculate power flow more simply and accurately, considering the characteristics of distribution network with DG and the flexible applicability of RBF neural network, a special adaptive dynamic clustering RBFNN (DG-RBFNN) method, which clusters the input samples only according to the parameters associated with DG, has been used in this paper. Therefore, the results are more approximate to the real condition and the calculation process is simpler compared with conventional back/forward (B/F) method meanwhile the calculation scale is also relatively smaller compared with ordinary adaptive dynamic clustering RBFNN. Finally, according to a 21-bus 66 kV distribution network of Shenyang, Liaoning province simulation experiment, the availability of DG-RBFNN method is proved.