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Cited by 1,646Energy Load and Power ForecastingForecasting Techniques and ApplicationsStock Market Forecasting Methods

Electricity price forecasting: A review of the state-of-the-art with a look into the future

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Weron, Rafał·2014·International Journal of Forecasting
DOI 10.1016/j.ijforecast.2014.08.008
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Abstract

A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the last 15 years, with varying degrees of success. This review article aims to explain the complexity of available solutions, their strengths and weaknesses, and the opportunities and threats that the forecasting tools offer or that may be encountered. The paper also looks ahead and speculates on the directions EPF will or should take in the next decade or so. In particular, it postulates the need for objective comparative EPF studies involving (i) the same datasets, (ii) the same robust error evaluation procedures, and (iii) statistical testing of the significance of one model’s outperformance of another.

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  • ML can help control batteries located at solar and wind farms to increase these farms' profits, for instance by storing their electricity when prices are low and then selling it when prices are high.

    “ML can also help control batteries located at solar and wind farms to increase these farms' profits, for instance by storing their electricity when prices are low and then selling it when prices are high; prior work has used ML to forecast electricity prices [460,838] or RL to control batteries based on current and historical prices [825].”

    From Tackling climate change with machine learning (2023) · cites this paper as [838]

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Authors
Weron, R.
Affiliations
Wrocław University of Science and Technology (PL)
Corresponding author
Weron, Rafał
ORCID
Weron, Rafał
Venue
International Journal of Forecasting
Publisher
Elsevier BV
Published
2014-10
Volume
30
Issue
4
Pages
1030-1081
ISSN
0169-2070 (ISSN-L)
DOI
10.1016/j.ijforecast.2014.08.008
OpenAlex
W1568559004
Cited by
1,646
References
316
Citations by year
2026: 188 · 2025: 150 · 2024: 128 · 2023: 121 · 2022: 148 · 2021: 158 · 2020: 176 · 2019: 159 · 2018: 153 · 2017: 110 · 2016: 97 · 2015: 49 · 2014: 7 · 2013: 1
FWCI
46.59
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Forecasting (publishedVersion, cc-by-nc-nd)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
National Science Centre (NCN, Poland) (2011/01/B/HS4/01077)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Energy Load and Power Forecasting
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
Keywords
electricity price forecasting, forecasting methods, forecast evaluation, model comparison, significance testing, future research directions

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