DocumentCode :
1697533
Title :
Distribution network reconfiguration considering the random character of wind power generation
Author :
Zhou Suwen ; Chen Xingying ; Liu Jian ; Dong Xinzhou ; Liao Yingchen
Author_Institution :
Coll. of Energy & Electr., Hohai Univ., Nanjing, China
Volume :
2
fYear :
2011
Firstpage :
1195
Lastpage :
1200
Abstract :
A chance constrained programming formulation for distribution reconfiguration with wind power generator (WPG) is proposed that aims at minimum power loss and increment voltage quality. A scenario analysis method is applied to describe the random output of WPG through the scenario probability and scenario output. A multiple objective particle algorithm (MOPSO) is employed to solve the multi-objective discrete nonlinear optimization problem. The dedicated particle encoding with the mesh information of the distribution network can effectively avoid producing a large amount of invalid solutions. With MOSPO, it is possible to obtain the optimum solution set of each objective while helping the operator to choose the most appropriate plan for reconfiguration. Application of the model and MOPSO algorithm to the 69 distribution network has verified their feasibility and correctness.
Keywords :
distributed power generation; nonlinear programming; particle swarm optimisation; probability; wind power plants; MOPSO algorithm; WPG; chance constrained programming; distribution network reconfiguration; mesh information; multiobjective discrete nonlinear optimization; multiple objective particle algorithm; particle encoding; scenario analysis method; scenario probability; wind power generation; Automatic voltage control; Automation; Power systems; Programming; Wind farms; Wind speed; MOPSO; chance constrained programming; distribution network reconfiguration; scenario analysis; wind power generator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Power System Automation and Protection (APAP), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-9622-8
Type :
conf
DOI :
10.1109/APAP.2011.6180559
Filename :
6180559
Link To Document :
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