Title :
Forecasting next-day electricity prices with Hidden Markov Models
Author :
Zhang, Jianhua ; Wang, Jingyue ; Wang, Rui ; Hou, Guolian
Author_Institution :
Beijing Key Lab. of Ind. Process Meas. & Control New Technol. & Syst., North China Electr. Power Univ., NCEPU, Beijing, China
Abstract :
Next-day electricity prices forecasting is essential to consumers and producers. Due to the stochastic characteristics of the electricity price time series, a novel model of electricity price forecasting is presented based on the Hidden Markov Model (HMM). The factors impacting the electricity price forecasting are discussed. The proposed approach is utilized in an electricity market, the results show the effectiveness.
Keywords :
hidden Markov models; power markets; pricing; electricity market; electricity price forecasting; hidden Markov model; stochastic characteristic; Economic forecasting; Energy consumption; Hidden Markov models; Laboratories; Power markets; Predictive models; Probability distribution; Stochastic processes; Support vector machines; Technology forecasting; Hidden Markov Model; electricity price forecasting; power market;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-5045-9
Electronic_ISBN :
978-1-4244-5046-6
DOI :
10.1109/ICIEA.2010.5515281
