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SpringerBriefs in Electrical and Computer Engineering

Spatio-Temporal Data Analytics for Wind Energy Integration

Authors: Yang, L., He, M., Zhang, J., Vittal, V.

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  • ISBN 978-3-319-12319-6
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About this book

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 carefully examined. A spatio-temporal analysis approach enables the authors to develop Markov-chain-based short-term forecasts of wind farm power generation. To deal with the wind ramp dynamics, a support vector machine enhanced Markov model is introduced. The stochastic optimization of economic dispatch (ED) and interruptible load management are investigated as well. Spatio-Temporal Data Analytics for Wind Energy Integration is valuable for researchers and professionals working towards renewable energy integration. Advanced-level students studying electrical, computer and energy engineering should also find the content useful.

Table of contents (5 chapters)

Table of contents (5 chapters)

Buy this book

eBook 46,00 €
price for Spain (gross)
  • ISBN 978-3-319-12319-6
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 57,19 €
price for Spain (gross)
  • ISBN 978-3-319-12318-9
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Spatio-Temporal Data Analytics for Wind Energy Integration
Authors
Series Title
SpringerBriefs in Electrical and Computer Engineering
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
The Author(s)
eBook ISBN
978-3-319-12319-6
DOI
10.1007/978-3-319-12319-6
Softcover ISBN
978-3-319-12318-9
Series ISSN
2191-8112
Edition Number
1
Number of Pages
VIII, 80
Number of Illustrations
34 b/w illustrations
Topics

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