Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)
Data(s) |
2012
|
---|---|
Resumo |
This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO. |
Identificador | |
Publicador |
Scientific Information Database |
Relação |
http://www.jiaeee.org/admins/_upd_maghalat_share/_pdf_1343639284_2012_07_30_Paper5.pdf Arefi, Ali, Haghifam, Mahmood Reza, & Fathi, Seyed Hamid (2012) Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO). Journal of Iranian Association of Electrical and Electronics Engineers, 9(1), pp. 41-52. |
Direitos |
Copyright 2012 Scientific Information Database (SID) |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #Distribution networks #State estimation #POS algorithm #Mutation #Stretching function |
Tipo |
Journal Article |