DocumentCode :
3356581
Title :
Optimal Planning of Substation Locating and Sizing Based on Improved QPSO Algorithm
Author :
Xiao Bai ; Qin Tao ; Feng Dan ; Mu Gang ; Li Ping ; Xiao Guang-Ming
Author_Institution :
Sch. of Electr. Eng., Northeast Dianli Univ., Jilin
fYear :
2009
fDate :
27-31 March 2009
Firstpage :
1
Lastpage :
5
Abstract :
A hybrid model for substation locating and sizing is presented in this paper to work out the number of newly-built substations and capacity-expansion, load assignment and optimal size of substation. Geographic information system is used as a platform to manage a great deal of data in this method, in which the optimum assembly model of the substation capacity and the number of substations be the first layer model, then the second layer model of load assignment is constructed by load constructing vector, and then improves traditional single location model as the third layer model of substation locating and sizing. Based on economy and reliability constraints, three- layer model is nested to each other, finally the improved quantum-behaved particle swarm optimization (IQPSO) algorithm is used as a new algorithm to solve hybrid model. The IQPSO algorithm is tested by a realistic planning project to verify the effectiveness and feasibility.
Keywords :
geographic information systems; particle swarm optimisation; power engineering computing; power system planning; reliability; substations; QPSO algorithm; geographic information system; load assignment; quantum-behaved particle swarm optimization algorithm; second layer model; substation location optimal planning; Assembly systems; Convergence; Cost function; Geographic Information Systems; Mathematical model; Meeting planning; Particle swarm optimization; Solid modeling; Substations; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2486-3
Electronic_ISBN :
978-1-4244-2487-0
Type :
conf
DOI :
10.1109/APPEEC.2009.4918571
Filename :
4918571
Link To Document :
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