Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables
Forecasting the dynamic line rating allows to reach peaks of operational excellence upon electrical networks. Literature on dynamic rating has mainly addressed overhead lines, whereas lesser attention has been paid to buried cables. However, modeling the dynamics of the cable-soil system is quite a...
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doaj-600220c8b7774ce6863bb32816a1f8192021-03-29T22:09:24ZengIEEEIEEE Access2169-35362019-01-0174709472510.1109/ACCESS.2018.28885058580536Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried CablesAntonio Bracale0Pierluigi Caramia1Pasquale De Falco2https://orcid.org/0000-0002-1119-1151Andrea Michiorri3Angela Russo4Department of Engineering, University of Napoli Parthenope, Naples, ItalyDepartment of Engineering, University of Napoli Parthenope, Naples, ItalyDepartment of Engineering, University of Napoli Parthenope, Naples, ItalyCentre procédés, énergies renouvelables et systèmes énergétiques, Mines ParisTech, PSL University, Paris, FranceDepartment of Energy, Politecnico of Torino, Turin, ItalyForecasting the dynamic line rating allows to reach peaks of operational excellence upon electrical networks. Literature on dynamic rating has mainly addressed overhead lines, whereas lesser attention has been paid to buried cables. However, modeling the dynamics of the cable-soil system is quite a challenge, especially when both the day-ahead and intraday forecasting scenarios have to be considered in order to suit the usual operating tasks on electrical grids. This paper aims at providing a comparison among different forecasting methods, specially developed for such lead times. In particular, this paper: 1) develops a new physical-statistical method for intra-day forecasting scenarios; and 2) verifies the suitability of a data-driven method, which is an adaption of the state-of-the-art approach for dynamic overhead-line rating to the case of dynamic buried-cable rating, for both intraday and day-ahead scenarios. Numerical applications based on actual data are presented to validate the comparative study, and the forecasting results are compared with a naïve benchmark based on the persistence method.https://ieeexplore.ieee.org/document/8580536/Forecastingpower distribution linesregression analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Antonio Bracale Pierluigi Caramia Pasquale De Falco Andrea Michiorri Angela Russo |
spellingShingle |
Antonio Bracale Pierluigi Caramia Pasquale De Falco Andrea Michiorri Angela Russo Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables IEEE Access Forecasting power distribution lines regression analysis |
author_facet |
Antonio Bracale Pierluigi Caramia Pasquale De Falco Andrea Michiorri Angela Russo |
author_sort |
Antonio Bracale |
title |
Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables |
title_short |
Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables |
title_full |
Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables |
title_fullStr |
Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables |
title_full_unstemmed |
Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables |
title_sort |
day-ahead and intraday forecasts of the dynamic line rating for buried cables |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
Forecasting the dynamic line rating allows to reach peaks of operational excellence upon electrical networks. Literature on dynamic rating has mainly addressed overhead lines, whereas lesser attention has been paid to buried cables. However, modeling the dynamics of the cable-soil system is quite a challenge, especially when both the day-ahead and intraday forecasting scenarios have to be considered in order to suit the usual operating tasks on electrical grids. This paper aims at providing a comparison among different forecasting methods, specially developed for such lead times. In particular, this paper: 1) develops a new physical-statistical method for intra-day forecasting scenarios; and 2) verifies the suitability of a data-driven method, which is an adaption of the state-of-the-art approach for dynamic overhead-line rating to the case of dynamic buried-cable rating, for both intraday and day-ahead scenarios. Numerical applications based on actual data are presented to validate the comparative study, and the forecasting results are compared with a naïve benchmark based on the persistence method. |
topic |
Forecasting power distribution lines regression analysis |
url |
https://ieeexplore.ieee.org/document/8580536/ |
work_keys_str_mv |
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