Stefan Wermter

Fuchun Sun

Huaping Liu

Dewen Hu

Lei Yang

Bin Fang

This book constitutes the refereed post-conference proceedings of the 6th International Conference on Cognitive Systems and Signal Processing, ICCSIP 2021, held in Suzhou, China, in November 2021. The 41 revised papers presented were carefully reviewed and selected from 105 submissions. The papers are organized in topical sections on algorithm; vision; and robotics and application.

6th International Conference, ICCSIP 2021, Suzhou, China, November 20–21, 2021, Revised Selected Papers

Cognitive Systems and Information Processing

Vijay Vittal

Miao He

Junshan Zhang

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.

Spatio-Temporal Data Analytics for Wind Energy Integration

Lei Yang

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