No Cover Image

Journal article 116 views 79 downloads

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

Shanglei Chai, Qiang Li, Abedin Abedin, Brian M. Lucey

Research in International Business and Finance, Volume: 67, Start page: 102132

Swansea University Author: Abedin Abedin

  • 64760.AAM.pdf

    PDF | Accepted Manuscript

    Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy.

    Download (2.08MB)

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, m...

Full description

Published in: Research in International Business and Finance
ISSN: 0275-5319 1878-3384
Published: Elsevier BV 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa64760
Tags: Add Tag
No Tags, Be the first to tag this record!
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
College: Faculty of Humanities and Social Sciences
Funders: This work was supported by the National Social Science Foundation of China (No. 20BJL058).
Start Page: 102132