Xun Shen

Linfei Yin

Lorenzo Ferrari

Hui Hwang Goh

Unai Fernandez-Gamiz

Lefeng Cheng

David Carvalho

Under the net-zero carbon goal, building a novel power system with renewable energy as the mainstay has become the core strategic task of the current power system transformation. However, the random and intermittent shocks generated by large-scale wind farms will significantly affect the safe and stable operation of the power system. In addition, the difference between onshore and offshore topography will affect the output power fluctuation characteristics. Therefore, it is necessary to research complex terrain's impact on wind power output and the mechanism of prediction accuracy improvement. Research on the influence of complex landscapes on wind power output; analysis on the method of improving the accuracy of wind power prediction model under complex landscapes. Research a more scientific and reasonable prediction error assessment index system adapted to novel power systems, support more accurate prediction technology for wind farms covering complex terrain, and develop a high-precision power prediction algorithm for onshore wind farms covering complex terrain to support safe grid connection and consumption of large-scale new energy. Supports, but is not limited to, the following topics: • Model or data-driven approaches to accurately forecast wind power • Mechanism analysis of wind power output prediction • Comprehensive evaluation framework for wind power forecasting results • Methods to improve the accuracy of wind farm output forecasting • Optimization methods for individual wind turbine operating parameters • Economic dispatching method considering wind power fluctuation

David Carvalho

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