DOIONLINE 
DOIONLINE Publish In |
International Journal of Industrial Electronics and Electrical Engineering (IJIEEE)-IJIEEE |
 Journal Home Volume Issue |
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Issue |
Volume-5,Issue-11 ( Nov, 2017 ) | |||||||||
Paper Title |
Comparison of Optimal Location and Sizing of Distributed Generation using Differential Evolution and Genetic Algorithm | |||||||||
Author Name |
K.Neha, K.Hemalata | |||||||||
Affilition |
Asst. Professor, Dept. of EEE, RSRRCET, Sanjay Rungta Group of Institutions, Kohka, Bhilai, India Asst. Professor, Dept. of EEE, HKBK College of Engineering, Bengaluru, India | |||||||||
Pages |
26-30 | |||||||||
Abstract |
The ever increasing need for electrical power generation, steady progress in the power deregulation and utility restructuring, and tight constraints over the construction of new transmission lines for long distance power transmission have created increased interest in distributed power generation. Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss, etc. This paper presents a methodology using a metaheuristic approach namely Differential Evolution (DE) for the placement of Distributed Generators (DG) in the radial distribution systems to reduce the real power losses and to improve the voltage profile. The method is tested on standard IEEE 30-bus test system and the results are presented and performance of the technique is compared using Genetic algorithm (GA) technique in the MATLAB programming environment. Test results indicate that DE method can obtain better results than the GA method on the 30-bus radial distribution systems. However the results indicate DE can obtain the optimal sizing with less time of computation. The results show that proper placement and size of DG units can have a significant impact on system loss reduction and voltage profile improvement. On the other hand, improper choice of size would lead to higher losses. Keywords - Differential Evolution, Distributed Generation, Genetic Algorithm, Metaheuristic methods | |||||||||
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