DocumentCode
3151383
Title
Using genetic alghoritm for distributed generation allocation to reduce losses and improve voltage profile
Author
Alinejad-Beromi, Y. ; Sedighizadeh, M. ; Bayat, M.R. ; Khodayar, M.E.
Author_Institution
Univ. of Semnan, Semnan
fYear
2007
fDate
4-6 Sept. 2007
Firstpage
954
Lastpage
959
Abstract
This paper presents a method for the optimal allocation of Distributed generation in distribution systems. In this paper, our aim would be optimal distributed generation allocation for voltage profile improvement and loss reduction in distribution network. Genetic Algorithm (GA) was used as the solving tool, which referring two determined aim; the problem is defined and objective function is introduced. Considering to fitness values sensitivity in genetic algorithm process, there is needed to apply load flow for decision-making. Load flow algorithm is combined appropriately with GA, till access to acceptable results of this operation. We used MATPOWER package for load flow algorithm and composed it with our Genetic Algorithm. The suggested method is programmed under MATLAB software and applied ETAP software for evaluating of results correctness. It was implemented on part of Tehran electricity distributing grid. The resulting operation of this method on some testing system is illuminated improvement of voltage profile and loss reduction indexes.
Keywords
distributed power generation; load flow; power grids; ETAP software; MATLAB software; MATPOWER package; Tehran electricity distributing grid; genetic algorithm; load flow algorithm; optimal distributed generation allocation; voltage profile improvement; Capacity planning; Costs; Decision making; Distributed control; Genetic algorithms; Load flow; Minimization; Packaging; Technology planning; Voltage; Allocation; Distributed Generation; Genetic Algorithm; Voltage Profile; losses;
fLanguage
English
Publisher
ieee
Conference_Titel
Universities Power Engineering Conference, 2007. UPEC 2007. 42nd International
Conference_Location
Brighton
Print_ISBN
978-1-905593-36-1
Electronic_ISBN
978-1-905593-34-7
Type
conf
DOI
10.1109/UPEC.2007.4469077
Filename
4469077
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