DocumentCode
724513
Title
Research on improvement method of distributed generation optimization configuration
Author
Gu Cailian ; Ji Jianwei ; Liu Li ; Guo Cheng
Author_Institution
Shenyang Agric. Univ., Shenyang, China
fYear
2015
fDate
23-25 May 2015
Firstpage
5039
Lastpage
5043
Abstract
The influence on distribution network of the distributed generation (DG) is closely related to the location and capacity connected to the DG, therefore it is very important to study the problems of site selection and capacity determination. The reactive power optimization is considered to improve the voltage level of power grid and reduce line losses. According to the capacity of the DG, The problem about selecting site and determining capacity is decomposed into two kinds of pattern with Parallel operation and island operation, which means comprehensive target of grid losses. voltage deviation and static voltage stability margin is optimal while DG is full load. Optimal allocation model of DG is established, the constraints condition includes node voltage, the transmission current of line, the single DG capacity and the total capacity of all DG. The genetic - ant colony hybrid intelligent algorithm is put forward to calculate the location and capacity of the DG. Simulation results show that the method is effective in problem of location selecting and capacity determing of DG.
Keywords
ant colony optimisation; distributed power generation; distribution networks; optimisation; reactive power; ant colony hybrid intelligent algorithm; capacity determination; distributed generation optimization configuration; distribution network; optimal allocation model; power grid; reactive power optimization; site selection; static voltage stability margin; voltage deviation; Distributed power generation; Optimization; Ant Colony Algorithm; DG; Distribution Network; Genetic Algorithm; Reactive Power Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7162826
Filename
7162826
Link To Document