Spatio-Temporal Data Analytics for Wind Energy Integration

This SpringerBrief presents spatio-temporal data analytics for wind energy integration using stochastic modeling and optimization methods. It explores techniques for efficiently integrating renewable energy generation into bulk power grids. The operational challenges of wind, and its variability are...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Yang, Lei (Autor), He, Miao (Autor), Zhang, Junshan (Autor), Vittal, Vijay (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:SpringerBriefs in Electrical and Computer Engineering,
Temas:
Renewable energy sources.
Data mining.
Energy policy.
Energy and state.
Electric power production.
Renewable Energy.
Data Mining and Knowledge Discovery.
Energy Policy, Economics and Management.
Electrical Power Engineering.
Mechanical Power Engineering.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction
  • A Spatio-Temporal Analysis Approach for Short-Term Forecast of Wind Farm Generation
  • Support Vector Machine Enhanced Markov Model for Short-Term Wind Power Forecast
  • Stochastic Optimization based Economic Dispatch and Interruptible Load Management
  • Conclusions and Future Works.

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