Privacy preserving ultra-short-term prediction in clustered wind farms with encrypted data sharing: A secure multi-party computation approach

Hang Fan, Xiaoyu Fan, Wei Wei, Tianyi Hao, Kun Chen, Guosai Wang, Wei Xu

Abstract: Highlights•First secret share protocol application in wind power prediction.•Introduced pwXGBoost, a distributed prediction method using SMPC.•Developed an MMD-based approach to select participant wind farms.•Using real data to demonstrate improved accuracy and efficiency.•Spatial–temporal correlations significantly enhances prediction precision.