Error Location Analysis of Wind Power Prediction Based on EMD-LSTM

Author:

Sun Jieyi,Shen Yangwu,Jin Heping,Wu Hong,Li Shuaihu

Publisher

Springer Nature Singapore

Reference14 articles.

1. Li, S., Yu, J., Wang, H.: Damages detection of aeroengine blades via deep learning algorithms. IEEE Trans. Instrum. Meas. 72, 1–11 (2023)

2. Zhu, K., Fu, Q.: Short-term photovoltaic power prediction based on EEMD-Kmeans-ALO-LSTM. Chin. J. Power Sources 47(01), 103–107 (2023). (in chinese)

3. Tascikaraoglu, A., Uzunoglu, M.: A review of combined approaches for prediction of short-term wind speed and power. Renew. Sustain. Energy Rev. 34(6), 243–254 (2014)

4. Zhou, N., Liao, J.Q., Wang, Q.G., et al.: Analysis and prospect of deep learning application in smart grid. Automat. Electric Power Syst. 43(4), 180–191 (2019). (in chinese)

5. Liu, Y., Liu, L.Q.: Wind power prediction based on LSTM-CNN opti-mization. Sci. J. Intell. Syst. Res. 3(4), 277–285 (2021)

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