DocumentCode :
3038986
Title :
Optimal location and sizing of distributed generation based on gentic algorithm
Author :
Helal, Abdelsalam ; Amer, Muhammad ; Eldosouki, H.
Author_Institution :
Electr. & Control Eng. Dept., Arab Acad. for Sci. & Technol. & Maritime Transp., Alexandria, Egypt
fYear :
2012
fDate :
6-8 Dec. 2012
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a methodology for optimal distributed generation (DG) location and sizing in distribution systems. The main objective of the added DG units is minimizing the total electrical network losses with acceptable voltage profile. Genetic Algorithm (GA) Technique is used as the optimization searching algorithm due to its advantages over the other optimization techniques in this application. The system losses and voltage profile evaluation is based on a power flow analysis for the distribution network with the representation of the distributed generators using MATPOWER software package. Cost Benefit Factor (CBF) is used to evaluate the benefits of the added DG units to the system performance. This factor combined the cost of adding new DG unit with the saving gained from total power losses reduction and reserved power generation. The optimization algorithm is applied to two different test distribution systems; 13-Bus radial system and actual 66 kV distribution network of Alexandria, EGYPT. The results indicated that if the DG units are placed at their optimal location and have optimal sizing, the total distribution system losses will be reduced.
Keywords :
cost-benefit analysis; genetic algorithms; power engineering computing; power generation economics; software packages; Alexandria; Egypt; GA technique; MATPOWER software package; cost benefit factor; distributed generation location; distributed generation sizing; electrical network loss; genetic algorithm; optimization searching algorithm; power flow analysis; voltage 66 kV; voltage profile evaluation; Distributed power generation; Generators; Genetic algorithms; Optimization; Power systems; Sociology; Statistics; CBF; Distributed Generation; Genetic Algorithm; Losses; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computing and Control Applications (CCCA), 2012 2nd International Conference on
Conference_Location :
Marseilles
Print_ISBN :
978-1-4673-4694-8
Type :
conf
DOI :
10.1109/CCCA.2012.6417905
Filename :
6417905
Link To Document :
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