Fuzzy prediction interval models for forecasting renewable resources and loads in microgrids

Doris Sáez, Fernand Ávila, Daniel Olivares, Claudio Cañizares, Luis Marín

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

161 Citas (Scopus)

Resumen

An energy management system (EMS) determines the dispatching of generation units based on an optimizer that requires the forecasting of both renewable resources and loads. The forecasting system discussed in this paper includes a representation of the uncertainties associated with renewable resources and loads. The proposed modeling generates fuzzy prediction interval models that incorporate an uncertainty representation of future predictions. The model is demonstrated using solar and wind generation and local load data from a real microgrid in Huatacondo, Chile, for one-day ahead forecasts to obtain the expected values together with fuzzy prediction intervals to represent future measurement bounds with a certain coverage probability. The proposed prediction interval models would help to enable the development of robust microgrid EMS.

Idioma originalInglés
Número de artículo6994295
Páginas (desde-hasta)548-556
Número de páginas9
PublicaciónIEEE Transactions on Smart Grid
Volumen6
N.º2
DOI
EstadoPublicada - 1 mar. 2015
Publicado de forma externa

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