Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method. Issue 11 (1st August 2015)

• Record Type: Journal Article
• Authors: Chen, Shuheng; Hu, Weihao; Su, Chi; Zhang, Xiaoxu; Chen, Zhe
• Is Part Of: IET generation, transmission & distribution. Volume 9:Issue 11(2015)
• Page Start: 1096
• Page End: 1103
• Publication Date: 2015-08-01
• Subjects: optimal control -- reactive power control -- voltage control -- power distribution control -- distributed power generation -- particle swarm optimisation -- fuzzy control -- adaptive control -- power transformers -- power capacitors -- nonlinear programming -- integer programming; optimal reactive power control -- voltage control -- distribution networks -- distributed generators -- fuzzy adaptive hybrid particle swarm optimisation method -- PSO -- comprehensive cost minimization -- power loss -- operation cost -- transformers -- capacitors -- reactive power limits -- bus voltage deviation -- allowable daily switching operation number -- mixed integer nonlinear programming problem -- HPSO -- fuzzy adaptive inference -- VC + + 6.0 program language -- IEEE 33‐node distribution system; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2014.1059
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid particle swarm optimisation (PSO) is proposed. The objective is to minimise comprehensive cost, consisting of power loss and operation cost of transformers and capacitors, and subject to constraints such as minimum and maximum reactive power limits of distributed generators, maximum deviation of bus voltages and maximum allowable daily switching operation number. PSO is used to solve the corresponding mixed integer non‐linear programming problem and the hybrid PSO (HPSO) method, consisting of three PSO variants, is presented. In order to mitigate the local convergence problem, fuzzy adaptive inference is used to improve the searching process and the final fuzzy adaptive inference‐based HPSO is proposed. The proposed algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33‐node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods.