Energy Forecasting: A Review and Outlook
By Tao Hong, Pierre Pinson, Yi Wang, Rafal Weron, Dazhi Yang, H. Zareipour. IEEE Open Access Journal of Power and Energy, 2020
505 citations recorded by the source corpus.
Forecasting has been an essential part of the power and energy industry. Researchers and practitioners have contributed thousands of papers on forecasting electricity demand and prices, and renewable generation (e.g., wind and solar power). This article offers a brief review of influential energy forecasting papers; summarizes research trends; discusses importance of reproducible research and points out six valuable open data sources; makes recommendations about publishing high-quality research papers; and offers an outlook into the future of energy forecasting.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/311a9cb9693ef163de67decc2dff0d5ff97ea8b0
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In Artificial Intelligence
In Electrical and Electronic Engineering
- Grzegorz Marcjasz
- B. Schutter
- Jesus Lago
- .. Nahid-Al-Masood
- Danica Vukadinović Greetham
- Siddharth Arora
- Stephen A. Haben
- Shohana Rahman Deeba
Citations in the corpus
- Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark (2020, result): “In particular, as concluded by all major review publications, comparisons between EPF methods are very difficult since studies use different datasets, different software implementations, and different error measures; the lack of statistical rigor complicates these analyses even further [5–8].”
- A Short-Term Load Forecasting Method Using Integrated CNN and LSTM Network (2021, methodology): “To mitigate this issue, machine learning based strategies are evolved and extensively used in STLF [9] These methods encompass clustering method [10], support vector machine (SVR) [11], fuzzy logic framework [12], artificial neural network (ANN) [13]–[16], radial basis functional network (RBFN) [17]…”
- Review of low voltage load forecasting: Methods, applications, and recommendations (2021, methodology): “As with most reviews in other areas, both [102] and [221] use a Scopus search to identify the number of published papers and major journals that publish forecasting and smart meter research.”