Metaheuristic approach to the Holt-Winters optimal short term load forecast


Autoria(s): Eusébio, Eduardo Adelino Mateus Nunes; Camus, Cristina Inês; Curvelo, Carolina
Data(s)

11/05/2015

11/05/2015

01/03/2015

Resumo

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Identificador

EUSÉBIO, Eduardo Adelino Mateus Nunes; CAMUS, Cristina Inês; CURVELO, Carolina - Metaheuristic approach to the Holt-Winters optimal short term load forecast. Renewable Energy & Power Quality Journal. ISSN 2172-038X. Vol. 13 (2014)

2172-038X

http://hdl.handle.net/10400.21/4525

Idioma(s)

eng

Publicador

European Association for the Development of Renewable Energy, Environment and Power Quality

Relação

http://www.icrepq.com/icrepq'15/460-15-eusebio.pdf

Direitos

restrictedAccess

Palavras-Chave #Electricity demand #Load forecast #Combinatorial optimization #Evolutionary algorithms
Tipo

article