Título
Hybrid Transformer Prognostics Framework for Enhanced Probabilistic Predictions in Renewable Energy ApplicationsOtras instituciones
OrmazabalUniversity of Strathclyde
Versión
Postprint
Derechos
© 2022 IEEEAcceso
Acceso embargadoVersión del editor
https://doi.org/10.1109/TPWRD.2022.3203873Publicado en
IEEE Transactions on Power Delivery September, 2022Editor
IEEEPalabras clave
Probabilistic logic
Power transformer insulation
Predictive model
uncertainty ... [+]
Power transformer insulation
Predictive model
uncertainty ... [+]
Probabilistic logic
Power transformer insulation
Predictive model
uncertainty
Forecasting
Estimation
Transient analysis [-]
Power transformer insulation
Predictive model
uncertainty
Forecasting
Estimation
Transient analysis [-]
Resumen
The intermittent nature of renewable energy sources (RESs) hamper their integration to the grid. The stochastic and rapid-changing operation of RES technologies impact on power equipment reliability. ... [+]
The intermittent nature of renewable energy sources (RESs) hamper their integration to the grid. The stochastic and rapid-changing operation of RES technologies impact on power equipment reliability. Transformers are key integrative assets of the power grid and it is crucial to monitor their health for the reliable integration of RESs. Existing models to transformer lifetime estimation are based on point forecasts or steady-state models. In this context, this paper presents a novel hybrid transformer prognostics framework for enhanced probabilistic predictions in RES applications. To this end, physics-based transient thermal models and probabilistic forecasting models are integrated using an error-correction configuration. The thermal prediction model is then embedded within a probabilistic prognostics framework to integrate forecasting estimates within the lifetime model, propagate associated uncertainties and predict the transformer remaining useful life with prediction intervals. Prediction intervals vary for each prediction according to the propagated uncertainty and they inform about the confidence of the model in the predictions. The proposed approach is tested and validated with a floating solar power plant case study. Results show that, from the insulation degradation perspective, there may be room to extend the transformer useful life beyond initial lifetime assumptions. [-]
Sponsorship
Gobierno de EspañaID Proyecto
info:eu-repo/grantAgreement/GE/Convocatoria 2019. Plan Estatal de I+D+I 2017-2020. Subprograma Estatal de Formación y en el Subprograma Estatal de Incorporación, del Programa Estatal de Promoción del Talento y su Empleabilidad. Ayudas Juan de la Cierva-incorporación/IJC2019-039183-I/ES/Colecciones
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