Spatio-Temporal Data Analytics for Wind Energy Integration Book Reviews
Spatio-Temporal Data Analytics for Wind Energy Integration by Lei Yang, Miao He, Junshan Zhang & Vijay Vittal Book Summary
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.
Book Name | Spatio-Temporal Data Analytics for Wind Energy Integration |
Genre | Power Resources |
Author | Lei Yang, Miao He, Junshan Zhang & Vijay Vittal |
Published | 14 November 2014, Friday |
Language | English |
E-Book Size | 2.11 MB |
Spatio-Temporal Data Analytics for Wind Energy Integration (Lei Yang, Miao He, Junshan Zhang & Vijay Vittal) Book Reviews 2024
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Spatio-Temporal Data Analytics for Wind Energy Integration E-book (PDF, PUB, KINDLE) Download
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Summary of Spatio-Temporal Data Analytics for Wind Energy Integration by Lei Yang, Miao He, Junshan Zhang & Vijay Vittal
The Spatio-Temporal Data Analytics for Wind Energy Integration book written by Lei Yang, Miao He, Junshan Zhang & Vijay Vittal was published on 14 November 2014, Friday in the Power Resources category. A total of 160 readers of the book gave the book 0 points out of 5.
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