You might also like

More about Spatio-Temporal Data Analytics for Wind Energy Integration

• Book details
• Synopsis
• Trending among others

You get 125 loyalty points

Book synopsis

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 details

Book category Books in English Technology, engineering, agriculture Energy technology & engineering Alternative & renewable energy sources & technology

• Full title: Spatio-Temporal Data Analytics for Wind Energy Integration
• Author: Lei Yang, Miao He, Junshan Zhang, Vijay Vittal
• Language: English
• Binding: Paperback
• Number of pages: 80
• EAN: 9783319123189
• ISBN: 3319123181
• ID: 06841837
• Publisher: Springer International Publishing AG
• Weight: 1474 g
• Dimensions: 235 × 155 × 235 mm
• Date of publishing: 15. November 2014

Trending among others

---

---

---