DocumentCode
2017110
Title
Multi-objective evolutionary scheme for distributed generations planning in distribution networks
Author
Ojaghi, M. ; Azari, M. ; Darabian, M.
Author_Institution
Dept. of Electr. Eng., Univ. of Zanjan, Zanjan, Iran
fYear
2013
fDate
25-28 Feb. 2013
Firstpage
1597
Lastpage
1602
Abstract
Distributed generation (DG) planning problem, i.e. finding the optimal size and location of DG units, is a Mixed Integer Non-linear Problem (MINLP). Typically finding the optimal solution of a MINLP problem is a complicated duty. This paper is focused on optimal solution of DG planning problem (DGPP) using Imperialist Competitive Algorithm (ICA) in distribution networks. DGPP is converted to an optimization problem with the multi-objective function including the minimum network power losses, the better voltage regulation and the improving voltage stability of the distribution system. The effectiveness of the proposed approach is confirmed on 33-bus and 69-bus test systems under different operating conditions. The comparative analysis is made between other evolutionary methods like GA and PSO through some performance indices to demonstrate its flexibility and effectiveness.
Keywords
distributed power generation; evolutionary computation; integer programming; nonlinear programming; power distribution planning; power generation planning; 33-bus test systems; 69-bus test systems; DGPP; MINLP problem; distributed generation planning problem; distribution networks; distribution system voltage stability; mixed integer nonlinear problem; multiobjective evolutionary scheme; optimization problem; voltage regulation; Indexes; Optimization; Planning; Reactive power; Stability criteria; Voltage control; Distributed generation; Multi-objective optimization; Optimal planning; imperialist competitive algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology (ICIT), 2013 IEEE International Conference on
Conference_Location
Cape Town
Print_ISBN
978-1-4673-4567-5
Electronic_ISBN
978-1-4673-4568-2
Type
conf
DOI
10.1109/ICIT.2013.6505911
Filename
6505911
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