Dynamic Line Rating Forecasting and Evaluation
| Autor: | Romain Dupin, Andrea Michiorri, Georges Kariniotakis |
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| Přispěvatelé: | Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques ( PERSEE ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), European Wind Energy Association, Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques (PERSEE), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | EWEA Technology Workshop, Wind Power Forecasting 2015 EWEA Technology Workshop, Wind Power Forecasting 2015, Oct 2015, Leuven, Belgium HAL EWEA Technology Workshop, Wind Power Forecasting 2015, European Wind Energy Association, Oct 2015, Leuven, Belgium |
| Popis: | International audience; The Dynamic Line Rating (DLR) of overhead lines allows the increase of its ampacity, accordingly with the weather conditions. The dynamic ampacity can reach a value of 250% of the static rating. This can help solving congestion issues and brings several benefits for the grid operation: it improves the reliability of the grid, it allows economic savings and it facilitates the introduction of renewable energies. However, real-time rating is not sufficient to fully exploit DLR. For taking into account the DLR in the energy planning, day-ahead prediction must be developed. For security reasons, those predictions should have a high degree of reliability. The real ampacity of the line must be inferior to the predicted one during a limited time, in order to minimize risks which can be mortal. In this presentation is presented a methodology for probabilistic DLR forecasting and the evaluation of the models inspired from the existing practice developed for wind power prediction. The problem of DLR prediction can be briefly characterized as follows. Regarding the inputs of the problem, DLR depends on a series of meteorological parameters such as wind speed, wind direction, air temperature and solar radiation. Regarding the output, the ampacity of a conductor cannot be measured, being a limit seldom reached by the line, and must be estimated through a thermal models and/or thermal measurements on the conductor. The evaluation is based on three main characteristics of probabilistic forecasts: Reliability (the ability to inform about the probability of each event), Sharpness (the ability of the model to concentrate the information about the outcome) and Resolution (the ability to generate reliable forecasts depending on different forecast conditions). The three parameters are then used to allow the comparison of several models. |
| Databáze: | OpenAIRE |
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