Title :
Distribution network planning considering distributed generations based on genetic algorithm
Author :
Liu, Yongmei ; Wang, Zheshen ; Meng, Xiaoli ; Sheng, Wanxing
Author_Institution :
Dept. of Power Distrib. & Utilization & Rural Electrification, China Electr. Power Res. Inst., Beijing, China
Abstract :
Network-connected distributed generations is the development trend of future distribution network. It is important to investigate the position and determine the capacity of distributed generations (DG) in the existing distribution network. Considering the balance of power flow and the quality of electric energy supply, a DG mathematical model of position and capacity determining is built. The planning objective is to maximize the size of DG and minimize line losses of distribution system. The case studies have been carried on a 33-node distribution network through genetic algorithm. The simulation results show the proposed DG planning model and genetic algorithm are correct and feasible.
Keywords :
distributed power generation; genetic algorithms; load flow; power distribution planning; power supply quality; 33-node distribution network; distribution network planning; electric energy supply quality; genetic algorithm; mathematical model; network-connected distributed generations; power flow; Convergence; Distributed power generation; Genetic algorithms; Load flow; Particle swarm optimization; Planning; distributed generations; distribution network; generation expansion planning; genetic algorithm;
Conference_Titel :
Power Engineering and Automation Conference (PEAM), 2011 IEEE
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-9691-4
DOI :
10.1109/PEAM.2011.6135041
