سال انتشار: ۱۳۹۱

محل انتشار: هفدهمین کنفرانس سراسری شبکه های توزیع نیروی برق

تعداد صفحات: ۷

نویسنده(ها):

Mojtaba nuri – Department of Electrical Engineering Saveh Branch, Islamic Azad University
Mohammad Reza Miveh – Young Researchers Club Saveh Branch, Islamic Azad University
Sohrab Mirsaeidi – Young Researchers Club, Saveh Branch, Islamic Azad University
Mohammad Reza Gharibdoost – Department of Electrical Engineering Saveh Branch, Islamic Azad University

چکیده:

The power industry experience revolution known asPower Industry Structure Renewal mainly due to increasingprogresses in science and technology which will result in agradual change in methods of communication with energytools. Part of the revolution is the application of smallgeneration units in power generation; units with lowergeneration volume capacity, and cost compared to theenormous generators and power station. Increasing demandfor electrical energy along with increasing efficiency of smallenergy-generation units has made power companies to exploitthe units in distribution system close to loads. These smallenergy-generation units which are connected to distributionsystem are referred to as Distributed Generation(DG).Privatization of power industry and development ofrenewable energy are among the other important factors in theexpansion of these generation units. DGs play a key role indistribution system. Improvement of reliability, stability andloss-reduction indices are example of is considered as a keyissue in the utilization of DGs. Also, loadability of distributionsystem and their enhancement have a key role in theperformance of power system. Regarding the fact thatpositioning of DG resources for improvement of distributionsystem loadability index has not yet been taken into account,the present study indicates that placing and application of DGsby genetic algorithm optimization method will maximizeloadability of power systems. This method has been simulatedon IEEE standard network. The obtained results reveal theeffectiveness of the proposed algorithm.