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

Shanglei Chai, Qiang Li, Mohammad Zoynul Abedin and Brian Lucey

Research in International Business and Finance, 2024, vol. 67, issue PA

Abstract: Accurate 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 (search for similar items in EconPapers)
JEL-codes: C5 C8 G1 H4 L9 Q4 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:67:y:2024:i:pa:s0275531923002581

DOI: 10.1016/j.ribaf.2023.102132

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