On post-processing day-ahead NWP forecasts using Kalman filtering


Abstract:

Kalman filtering is an important concept in engineering and statistics. In the field of solar forecasting, it is well known as a numerical weather prediction (NWP) post-processing technique. However, it appears that this acknowledged post-processing technique needs some revisit. Since Kalman filtering is a sequential procedure, i.e., actual measurement from t is required to filter the forecast made for time t+1, it changes the forecast horizon of NWP from day-ahead to hour-ahead. Hence, the previously claimed improvements over NWP forecasts are not interpretable. Two simple remedies are proposed, which address the forecast horizon problem, but the effectiveness of the remedies is thought to be minimal.

Año de publicación:

2019

Keywords:

  • NWP
  • Post-processing
  • solar forecasting
  • Kalman filter

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Análisis de datos
  • Optimización matemática
  • Estadísticas

Áreas temáticas de Dewey:

  • Ciencias de la computación
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 7: Energía asequible y no contaminante
  • ODS 13: Acción por el clima
  • ODS 9: Industria, innovación e infraestructura
Procesado con IAProcesado con IA

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