Spatial load forecasting using a demand propagation approach


Autoria(s): Melo, J. D.; Carreno, E. M.; Padilha-Feltrin, A.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

31/05/2011

Resumo

A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance. © 2011 IEEE.

Formato

196-203

Identificador

http://dx.doi.org/10.1109/TDC-LA.2010.5762882

2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010, p. 196-203.

http://hdl.handle.net/11449/72448

10.1109/TDC-LA.2010.5762882

2-s2.0-79957564714

Idioma(s)

eng

Relação

2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, T and D-LA 2010

Direitos

closedAccess

Palavras-Chave #agent #distribution planning #knowledge extraction #land use #multi-agent systems #Spatial electric load forecasting #Demand propagation #Distribution systems #Expected loads #Knowledge extraction #Load levels #Local effects #Propagation pattern #Reactive agent #Real distribution #Real number #Spatial load forecasting #Electric load distribution #Electric loads #Forecasting #Intelligent agents #Local area networks #Multi agent systems #Electric load forecasting
Tipo

info:eu-repo/semantics/conferencePaper