Analysis of the French system imbalance paving the way for a novel operating reserve sizing approach
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866918088638726144 |
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| author | Dumas, Jonathan Finet, Sébastien Grisey, Nathalie Hamdane, Ibtissam Plessiez, Paul |
| author_facet | Dumas, Jonathan Finet, Sébastien Grisey, Nathalie Hamdane, Ibtissam Plessiez, Paul |
| contents | This paper examines the relationship between system imbalance and several explanatory variables within the French electricity system. The factors considered include lagged imbalance values, observations of renewable energy sources (RES) generation and consumption, and forecasts for RES generation and consumption. The study analyzes the distribution of system imbalance in relation to these variables. Additionally, an HGBR machine-learning model is employed to assess the predictability of imbalances and the explanatory power of the input variables studied.
The results indicate no clear correlation between RES generation or consumption and the observed imbalances. However, it is possible to predict the imbalance adequately using forecasts available a few hours before real-time, along with the lagged values of the imbalance. Predicting the imbalance a day in advance proves to be complex with the variables examined; however, the extreme quantiles of the imbalance used for reserve sizing and contracting can be predicted with sufficient accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_24240 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Analysis of the French system imbalance paving the way for a novel operating reserve sizing approach Dumas, Jonathan Finet, Sébastien Grisey, Nathalie Hamdane, Ibtissam Plessiez, Paul Systems and Control This paper examines the relationship between system imbalance and several explanatory variables within the French electricity system. The factors considered include lagged imbalance values, observations of renewable energy sources (RES) generation and consumption, and forecasts for RES generation and consumption. The study analyzes the distribution of system imbalance in relation to these variables. Additionally, an HGBR machine-learning model is employed to assess the predictability of imbalances and the explanatory power of the input variables studied. The results indicate no clear correlation between RES generation or consumption and the observed imbalances. However, it is possible to predict the imbalance adequately using forecasts available a few hours before real-time, along with the lagged values of the imbalance. Predicting the imbalance a day in advance proves to be complex with the variables examined; however, the extreme quantiles of the imbalance used for reserve sizing and contracting can be predicted with sufficient accuracy. |
| title | Analysis of the French system imbalance paving the way for a novel operating reserve sizing approach |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2503.24240 |