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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
