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- Title
Recent developments in multivariate wind and solar power forecasting.
- Authors
Sørensen, Mikkel L.; Nystrup, Peter; Bjerregård, Mathias B.; Møller, Jan K.; Bacher, Peder; Madsen, Henrik
- Abstract
The intermittency of renewable energy sources, such as wind and solar, means that they require reliable and accurate forecasts to integrate properly into energy systems. This review introduces and examines a selection of state‐of‐the‐art methods that are applied for multivariate forecasting of wind and solar power production. Methods such as conditional parametric and combined forecasting already see wide use in practice, both commercially and scientifically. In the context of multivariate forecasting, it is vital to model the dependence between forecasts correctly. In recent years, reconciliation of forecasts to ensure coherency across spatial and temporal aggregation levels has shown great promise in increasing the accuracy of renewable energy forecasts. We introduce the methodology used for forecast reconciliation and review some recent applications for wind and solar power forecasting. Many forecasters are beginning to see the benefit of the greater information provided by probabilistic forecasts. We highlight stochastic differential equations as a method for probabilistic forecasting, which can also model the dependence structure. Lastly, we discuss forecast evaluation and how choosing a proper approach to evaluation is vital to avoid misrepresenting forecasts. This article is categorized under:Climate and Environment > Net Zero Planning and DecarbonizationSustainable Energy > Solar EnergySustainable Energy > Wind Energy
- Subjects
WIND power; SOLAR energy; RENEWABLE energy sources; STOCHASTIC differential equations; WIND forecasting; FORECASTING methodology
- Publication
WIREs: Energy & Environment, 2023, Vol 12, Issue 2, p1
- ISSN
2041-8396
- Publication type
Article
- DOI
10.1002/wene.465