DocumentCode :
3592626
Title :
Distributed generation placement to maximize the loadability of distribution system using genetic algorithm
Author :
Nuri, Mojtaba ; Miveh, Mohammad Reza ; Mirsaeidi, Sohrab ; Gharibdoost, Mohammad Reza
Author_Institution :
Dept. of Electr. Eng., Islamic Azad Univ., Saveh, Iran
fYear :
2012
Firstpage :
1
Lastpage :
5
Abstract :
The power industry experience revolution known as "Power Industry Structure Renewal" mainly due to increasing progresses in science and technology which will result in a gradual change in methods of communication with energy tools. Part of the revolution is the application of small generation units in power generation; units with lower generation volume capacity, and cost compared to the enormous generators and power station. Increasing demand for electrical energy along with increasing efficiency of small energy-generation units has made power companies to exploit the units in distribution system close to loads. These small energy-generation units which are connected to distribution system are referred to as "Distributed Generation" (DG). Privatization of power industry and development of renewable energy are among the other important factors in the expansion of these generation units. DGs play a key role in distribution system. Improvement of reliability, stability and loss-reduction indices are example of is considered as a key issue in the utilization of DGs. Also, loadability of distribution system and their enhancement have a key role in the performance of power system. Regarding the fact that positioning of DG resources for improvement of distribution system loadability index has not yet been taken into account, the present study indicates that placing and application of DGs by genetic algorithm optimization method will maximize loadability of power systems. This method has been simulated on IEEE standard network. The obtained results reveal the effectiveness of the proposed algorithm.
Keywords :
IEEE standards; distributed power generation; load management; power distribution reliability; IEEE standard network; distributed generation placement; energy tools; genetic algorithm; loadability; power industry structure renewal; privatization; reliability; small generation units; stability; Distributed power generation; Educational institutions; Genetic algorithms; Indexes; Propagation losses; Voltage control; Distributed Generation (DG); Distribution System; Electric Power Losses; Voltage Profile;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Power Distribution Networks (EPDC), 2012 Proceedings of 17th Conference on
Print_ISBN :
978-1-4673-1418-3
Type :
conf
Filename :
6254542
Link To Document :
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