Spatio-Temporal Data Analytics for Wind Energy Integration (e-bog) af Vittal, Vijay
Vittal, Vijay (forfatter)

Spatio-Temporal Data Analytics for Wind Energy Integration e-bog

436,85 DKK (inkl. moms 546,06 DKK)
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...
E-bog 436,85 DKK
Forfattere Vittal, Vijay (forfatter)
Forlag Springer
Udgivet 14 november 2014
Genrer The environment
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9783319123196
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.