Spatio-Temporal Data Analytics for Wind Energy Integration

(Part of the SpringerBriefs in Electrical and Computer Engineering Series)

by Vijay Vittal, Junshan Zhang, Miao He, et al.

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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...

Format:Paperback

Language:English

ISBN:3319123181

ISBN13:9783319123189

Release Date:December 2014

Publisher:Springer

Length:80 Pages

Weight:0.30 lbs.

Dimensions:0.2" x 6.1" x 9.2"

Related Subjects

Business Business & Investing Computers Computers & Technology Science Science & Math Science & Scientists Science & Technology

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Spatio-Temporal Data Analytics for Wind Energy Integration

(Part of the SpringerBriefs in Electrical and Computer Engineering Series)

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