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 b...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-05-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2025.1533778/full |
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| author | Michael Lehning Michael Lehning Jérôme Dujardin Albin Cintas |
| author_facet | Michael Lehning Michael Lehning Jérôme Dujardin Albin Cintas |
| author_sort | Michael Lehning |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-2cb454e73c744e3f9c5dc932c32b627d |
| institution | Kabale University |
| issn | 2296-598X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj-art-2cb454e73c744e3f9c5dc932c32b627d2025-08-20T03:51:58ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2025-05-011310.3389/fenrg.2025.15337781533778The value of weather forecasts for optimally placed wind and solar electricity generatorsMichael Lehning0Michael Lehning1Jérôme Dujardin2Albin Cintas3CRYOS, School of Architecture, Civil and Environmental Engineering, EPFL Alpole, Sion, SwitzerlandWSL Institute for Snow and Avalanche Research SLF, Davos, SwitzerlandWSL Institute for Snow and Avalanche Research SLF, Davos, SwitzerlandCRYOS, School of Architecture, Civil and Environmental Engineering, EPFL Alpole, Sion, SwitzerlandAs 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.https://www.frontiersin.org/articles/10.3389/fenrg.2025.1533778/fulldecentralized energyload balancingelectricity importgrid constraintshydropowerSwitzerland |
| spellingShingle | Michael Lehning Michael Lehning Jérôme Dujardin Albin Cintas The value of weather forecasts for optimally placed wind and solar electricity generators Frontiers in Energy Research decentralized energy load balancing electricity import grid constraints hydropower Switzerland |
| title | The value of weather forecasts for optimally placed wind and solar electricity generators |
| title_full | The value of weather forecasts for optimally placed wind and solar electricity generators |
| title_fullStr | The value of weather forecasts for optimally placed wind and solar electricity generators |
| title_full_unstemmed | The value of weather forecasts for optimally placed wind and solar electricity generators |
| title_short | The value of weather forecasts for optimally placed wind and solar electricity generators |
| title_sort | value of weather forecasts for optimally placed wind and solar electricity generators |
| topic | decentralized energy load balancing electricity import grid constraints hydropower Switzerland |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2025.1533778/full |
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