EAN: 9783319123189

SPRINGERBRIEFS IN ELECTRICAL AND COMPUTER ENGIN...

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.

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