The value of weather forecasts for optimally placed wind and solar electricity generators

As many societies transition to renewable wind and solar energy, the challenge of managing the high volatility of these generators becomes increasingly important. Given the spatiotemporal variability of weather—and thus energy production—the optimal placement of new installations can be determined based on average weather (or climate) patterns to enhance demand matching within a grid environment. At the same time, as weather forecasts improve in accuracy, it becomes increasingly feasible to predict wind and solar production in advance, offering valuable planning insights for both electricity consumers and producers within a specific market. This study uses a hypothetical 2050 Swiss electricity system, in which demand is predominantly met by existing hydropower alongside wind and solar PV systems, to demonstrate the value of integrating weather forecasts into system-wide dispatchable hydropower operations. By constructing a scenario in which the upcoming weather conditions are unknown and comparing it to one with a perfect weekly forecast, we use the OREES optimal power flow model to show that weather knowledge significantly reduces the need for electricity imports. The incorporation of weather forecasts results in a 36% reduction in electricity import costs and contributes to a more stable and less volatile grid operation, with reduced energy transfers even at the regional level.

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Publication Details

Journal
Frontiers in Energy Research
Published
2025-05-02
DOI
https://doi.org/10.3389/fenrg.2025.1533778
Citations
1
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
4.99
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article

The value of weather forecasts for optimally placed wind and solar electricity generators

Michael Lehning, Jérôme Dujardin, Albin Cintas
1 citations
Frontiers in Energy Research
Wind Energy Research and Development
4.99
article

The value of weather forecasts for optimally placed wind and solar electricity generators

Michael Lehning, Jérôme Dujardin, Albin Cintas
article en
1 citations

Abstract

As many societies transition to renewable wind and solar energy, the challenge of managing the high volatility of these generators becomes increasingly important. Given the spatiotemporal variability of weather—and thus energy production—the optimal placement of new installations can be determined based on average weather (or climate) patterns to enhance demand matching within a grid environment. At the same time, as weather forecasts improve in accuracy, it becomes increasingly feasible to predict wind and solar production in advance, offering valuable planning insights for both electricity consumers and producers within a specific market. This study uses a hypothetical 2050 Swiss electricity system, in which demand is predominantly met by existing hydropower alongside wind and solar PV systems, to demonstrate the value of integrating weather forecasts into system-wide dispatchable hydropower operations. By constructing a scenario in which the upcoming weather conditions are unknown and comparing it to one with a perfect weekly forecast, we use the OREES optimal power flow model to show that weather knowledge significantly reduces the need for electricity imports. The incorporation of weather forecasts results in a 36% reduction in electricity import costs and contributes to a more stable and less volatile grid operation, with reduced energy transfers even at the regional level.

Frontiers in Energy ResearchVol. 13
Association Fribourgeoise des Psychologues (CH), École Polytechnique Fédérale de Lausanne (CH)
Openalex Percentile: Top 6%
Wind Energy Research and Development
4.99
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The value of weather forecasts for optimally placed wind and solar electricity generators — Michael Lehning, Jérôme Dujardin, et al. · Frontiers in Energy Research (2025) | TGRS Research Map | TGRS