Characterizing renewable energy compound events across Europe using a logistic regression‐based approach
Abstract The transition towards decarbonized power systems requires accounting for the impacts of the climate variability and climate change on renewable energy sources. With the growing share of wind and solar power in the European power system and their strong weather dependence, balancing the ene...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-09-01
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| Series: | Meteorological Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/met.2089 |
| _version_ | 1811197164716556288 |
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| author | Noelia Otero Olivia Martius Sam Allen Hannah Bloomfield Bettina Schaefli |
| author_facet | Noelia Otero Olivia Martius Sam Allen Hannah Bloomfield Bettina Schaefli |
| author_sort | Noelia Otero |
| collection | DOAJ |
| description | Abstract The transition towards decarbonized power systems requires accounting for the impacts of the climate variability and climate change on renewable energy sources. With the growing share of wind and solar power in the European power system and their strong weather dependence, balancing the energy demand and supply becomes a great challenge. We characterize energy compound events, defined as periods of simultaneous low renewable production of wind and solar power, and high electricity demand. Using a logistic regression approach, we examine the influence of meteorological and atmospheric drivers on energy compound events. Moreover, we assess the spatial coherence of energy compound events that pose a major challenge within an interconnected power grid, as they can affect multiple countries simultaneously. On average, European countries are exposed to winter energy compound events more than twice per year. The combination of extremely low temperatures and low wind speeds is associated with a higher probability of occurrence of energy compound events. Furthermore, we show that blocked weather regimes have a major influence on energy compound events. In particular, Greenland and European blocking lead to widespread energy compound events that affect multiple countries at the same time. Our results highlight the relevance of weather regimes resulting in synchronous spatial energy compound events, which might pose a greater risk within a potential fully interconnected European grid. |
| first_indexed | 2024-04-12T01:10:00Z |
| format | Article |
| id | doaj.art-7ea9b18765064c6f8667bc2cbb22a9ed |
| institution | Directory Open Access Journal |
| issn | 1350-4827 1469-8080 |
| language | English |
| last_indexed | 2024-04-12T01:10:00Z |
| publishDate | 2022-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Meteorological Applications |
| spelling | doaj.art-7ea9b18765064c6f8667bc2cbb22a9ed2022-12-22T03:54:08ZengWileyMeteorological Applications1350-48271469-80802022-09-01295n/an/a10.1002/met.2089Characterizing renewable energy compound events across Europe using a logistic regression‐based approachNoelia Otero0Olivia Martius1Sam Allen2Hannah Bloomfield3Bettina Schaefli4Department of Geography and Oeschger Centre for Climate Change Research University of Bern Bern SwitzerlandDepartment of Geography and Oeschger Centre for Climate Change Research University of Bern Bern SwitzerlandDepartment of Mathematical Statistics and Actuarial Science University of Bern Bern SwitzerlandDepartment of Meteorology University of Reading Reading UKDepartment of Geography and Oeschger Centre for Climate Change Research University of Bern Bern SwitzerlandAbstract The transition towards decarbonized power systems requires accounting for the impacts of the climate variability and climate change on renewable energy sources. With the growing share of wind and solar power in the European power system and their strong weather dependence, balancing the energy demand and supply becomes a great challenge. We characterize energy compound events, defined as periods of simultaneous low renewable production of wind and solar power, and high electricity demand. Using a logistic regression approach, we examine the influence of meteorological and atmospheric drivers on energy compound events. Moreover, we assess the spatial coherence of energy compound events that pose a major challenge within an interconnected power grid, as they can affect multiple countries simultaneously. On average, European countries are exposed to winter energy compound events more than twice per year. The combination of extremely low temperatures and low wind speeds is associated with a higher probability of occurrence of energy compound events. Furthermore, we show that blocked weather regimes have a major influence on energy compound events. In particular, Greenland and European blocking lead to widespread energy compound events that affect multiple countries at the same time. Our results highlight the relevance of weather regimes resulting in synchronous spatial energy compound events, which might pose a greater risk within a potential fully interconnected European grid.https://doi.org/10.1002/met.2089energy compound eventsextremesrenewable energiesweather regimes |
| spellingShingle | Noelia Otero Olivia Martius Sam Allen Hannah Bloomfield Bettina Schaefli Characterizing renewable energy compound events across Europe using a logistic regression‐based approach Meteorological Applications energy compound events extremes renewable energies weather regimes |
| title | Characterizing renewable energy compound events across Europe using a logistic regression‐based approach |
| title_full | Characterizing renewable energy compound events across Europe using a logistic regression‐based approach |
| title_fullStr | Characterizing renewable energy compound events across Europe using a logistic regression‐based approach |
| title_full_unstemmed | Characterizing renewable energy compound events across Europe using a logistic regression‐based approach |
| title_short | Characterizing renewable energy compound events across Europe using a logistic regression‐based approach |
| title_sort | characterizing renewable energy compound events across europe using a logistic regression based approach |
| topic | energy compound events extremes renewable energies weather regimes |
| url | https://doi.org/10.1002/met.2089 |
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