Yingnan Zhao*, Yuyuan Ruan, Zhen Peng
CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 549-566, 2024, DOI:10.32604/cmc.2024.056240
- 15 October 2024
Abstract As the penetration ratio of wind power in active distribution networks continues to increase, the system exhibits some characteristics such as randomness and volatility. Fast and accurate short-term wind power prediction is essential for algorithms like scheduling and optimization control. Based on the spatio-temporal features of Numerical Weather Prediction (NWP) data, it proposes the WVMD_DSN (Whale Optimization Algorithm, Variational Mode Decomposition, Dual Stream Network) model. The model first applies Pearson correlation coefficient (PCC) to choose some NWP features with strong correlation to wind power to form the feature set. Then, it decomposes the feature set More >
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