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A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting

Commerce; Costs; Electric power systems; Forecasting; Genetic algorithms; Optimization; Support vector machines; Accuracy; Electrical power system; Electricity price forecasting; Electricity prices; Least square support vector machines; Multi-stage optimization; Optimized parameter; Parameter select...

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Main Authors: Razak I.A.W.A., Abidin I.Z., Yap K.S., Abidin A.A.Z., Rahman T.K.A., Nasir M.N.M.
Other Authors: 56602467500
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-231842023-05-29T14:38:15Z A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting Razak I.A.W.A. Abidin I.Z. Yap K.S. Abidin A.A.Z. Rahman T.K.A. Nasir M.N.M. 56602467500 35606640500 24448864400 25824750400 8922419700 55658799800 Commerce; Costs; Electric power systems; Forecasting; Genetic algorithms; Optimization; Support vector machines; Accuracy; Electrical power system; Electricity price forecasting; Electricity prices; Least square support vector machines; Multi-stage optimization; Optimized parameter; Parameter selection; Power markets Predicting price has now become an important task in the operation of electrical power system. Day-ahead prediction provides forecast prices for a day ahead that is useful for daily operation and decision-making. The main challenge for day ahead price forecasting is the accuracy and efficiency. Lower accuracy is produced due to the nature of electricity price that is highly volatile compared to load series. Hence, some researchers have developed complex procedures to produce accurate forecast while considering significant features and optimum parameters. Therefore, a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features. So far, no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for day-ahead price prediction. All the models are examined on the Ontario power market; which is reported as among the most volatile market worldwide. A huge number of features are selected by two stages of optimization to avoid from missing any important features. The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models. � 2016 IEEE. Final 2023-05-29T06:38:15Z 2023-05-29T06:38:15Z 2017 Conference Paper 10.1109/PECON.2016.7951593 2-s2.0-85024382225 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85024382225&doi=10.1109%2fPECON.2016.7951593&partnerID=40&md5=1bd04f21d281e4dcd007d872da635aa9 https://irepository.uniten.edu.my/handle/123456789/23184 7951593 390 395 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Commerce; Costs; Electric power systems; Forecasting; Genetic algorithms; Optimization; Support vector machines; Accuracy; Electrical power system; Electricity price forecasting; Electricity prices; Least square support vector machines; Multi-stage optimization; Optimized parameter; Parameter selection; Power markets
author2 56602467500
author_facet 56602467500
Razak I.A.W.A.
Abidin I.Z.
Yap K.S.
Abidin A.A.Z.
Rahman T.K.A.
Nasir M.N.M.
format Conference Paper
author Razak I.A.W.A.
Abidin I.Z.
Yap K.S.
Abidin A.A.Z.
Rahman T.K.A.
Nasir M.N.M.
spellingShingle Razak I.A.W.A.
Abidin I.Z.
Yap K.S.
Abidin A.A.Z.
Rahman T.K.A.
Nasir M.N.M.
A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting
author_sort Razak I.A.W.A.
title A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting
title_short A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting
title_full A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting
title_fullStr A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting
title_full_unstemmed A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting
title_sort novel hybrid method of lssvm-ga with multiple stage optimization for electricity price forecasting
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806425632079347712
score 13.222552

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