Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation
This paper presents a study on dynamic line rating (DLR) forecasting procedure aimed at developing a new methodology able to forecast future ampacity values for rare and extreme events. This is motivated by the belief that to apply DLR network operators must be able to forecast their values and this...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/13/12/3090 |
| _version_ | 1797565249076854784 |
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| author | Romain Dupin Laura Cavalcante Ricardo J. Bessa Georges Kariniotakis Andrea Michiorri |
| author_facet | Romain Dupin Laura Cavalcante Ricardo J. Bessa Georges Kariniotakis Andrea Michiorri |
| author_sort | Romain Dupin |
| collection | DOAJ |
| description | This paper presents a study on dynamic line rating (DLR) forecasting procedure aimed at developing a new methodology able to forecast future ampacity values for rare and extreme events. This is motivated by the belief that to apply DLR network operators must be able to forecast their values and this must be based on conservative approaches able to guarantee the safe operation of the network. The proposed methodology can be summarised as follows: firstly, probabilistic forecasts of conductors’ ampacity are calculated with a non-parametric model, secondly, the lower part of the distribution is replaced with a new distribution calculated with a parametric model. The paper presents also an evaluation of the proposed methodology in network operation, suggesting an application method and highlighting the advantages. The proposed forecasting methodology delivers a high improvement of the lowest quantiles’ reliability, allowing perfect reliability for the 1% quantile and a reduction of roughly 75% in overconfidence for the 0.1% quantile. |
| first_indexed | 2024-03-10T19:09:27Z |
| format | Article |
| id | doaj.art-af8c2c0330a848c3a764413bc620eff7 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T19:09:27Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-af8c2c0330a848c3a764413bc620eff72023-11-20T03:55:07ZengMDPI AGEnergies1996-10732020-06-011312309010.3390/en13123090Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network OperationRomain Dupin0Laura Cavalcante1Ricardo J. Bessa2Georges Kariniotakis3Andrea Michiorri4MINES ParisTech, PSL University, Centre for Processes, Renewable Energies and Energy Systems (PERSEE), CS 10207 rue Claude Daunesse, Cedex, 06904 Sophia Antipolis, FranceINESC TEC, Centre for Power and Energy Systems, Campus da FEUP, Rua Dr Roberto Frias, 4200-465 Porto, PortugalINESC TEC, Centre for Power and Energy Systems, Campus da FEUP, Rua Dr Roberto Frias, 4200-465 Porto, PortugalMINES ParisTech, PSL University, Centre for Processes, Renewable Energies and Energy Systems (PERSEE), CS 10207 rue Claude Daunesse, Cedex, 06904 Sophia Antipolis, FranceMINES ParisTech, PSL University, Centre for Processes, Renewable Energies and Energy Systems (PERSEE), CS 10207 rue Claude Daunesse, Cedex, 06904 Sophia Antipolis, FranceThis paper presents a study on dynamic line rating (DLR) forecasting procedure aimed at developing a new methodology able to forecast future ampacity values for rare and extreme events. This is motivated by the belief that to apply DLR network operators must be able to forecast their values and this must be based on conservative approaches able to guarantee the safe operation of the network. The proposed methodology can be summarised as follows: firstly, probabilistic forecasts of conductors’ ampacity are calculated with a non-parametric model, secondly, the lower part of the distribution is replaced with a new distribution calculated with a parametric model. The paper presents also an evaluation of the proposed methodology in network operation, suggesting an application method and highlighting the advantages. The proposed forecasting methodology delivers a high improvement of the lowest quantiles’ reliability, allowing perfect reliability for the 1% quantile and a reduction of roughly 75% in overconfidence for the 0.1% quantile.https://www.mdpi.com/1996-1073/13/12/3090forecastingampacityoverhead lineselectric power systems |
| spellingShingle | Romain Dupin Laura Cavalcante Ricardo J. Bessa Georges Kariniotakis Andrea Michiorri Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation Energies forecasting ampacity overhead lines electric power systems |
| title | Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation |
| title_full | Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation |
| title_fullStr | Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation |
| title_full_unstemmed | Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation |
| title_short | Extreme Quantiles Dynamic Line Rating Forecasts and Application on Network Operation |
| title_sort | extreme quantiles dynamic line rating forecasts and application on network operation |
| topic | forecasting ampacity overhead lines electric power systems |
| url | https://www.mdpi.com/1996-1073/13/12/3090 |
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