Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives

dc.contributor.authorLucey, Brian
dc.contributor.authorChai , Shanglei
dc.contributor.authorAbedin, Mohammad
dc.contributor.authorLi, Qiang
dc.date.accessioned2024-09-16T06:31:48Z
dc.date.available2024-09-16T06:31:48Z
dc.date.issued2024
dc.description.abstractAccurate electricity price forecasting (EPF) is crucial to participants and decision-makers within the electricity market. This paper reviews 62 screened literature works on EPF during 2012–2022 in terms of model structure and determinants of electricity price and discusses the evaluation process, model type, research sample, and prediction horizon. From the above efforts, we find that (1) data preprocessing and model optimization are often used to improve forecasting model accuracy; while performance evaluation is essential, extensive performance evaluation benchmarking is still missing; (2) considering electricity price determinants can significantly improve forecasting model accuracy, but there is disagreement over how many and which determinants should be accounted for; (3) while most existing research focuses on point forecasting, interval and density forecasting are more responsive to the range and uncertainty of electricity price changes. Keywords Determinants of electricity price, Dual decomposition method, Electricity price forecasting, Model optimization, Model structure
dc.identifier.citationChai, S., Li, Q., Abedin, M. Z., & Lucey, B. M. (2023). Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives. Research in International Business and Finance, 102132.
dc.identifier.doihttps://doi.org/10.1016/j.ribaf.2023.102132
dc.identifier.urihttps://repository.adu.ac.ae/handle/1/6464
dc.language.isoen
dc.publisherElsevier Ltd
dc.titleForecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives
dc.typeOther

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