PV Power Prediction via Residual Correction and Hierarchical Multiple Buildings Energy Management
Author:
Affiliation:
1. Graduate School of Science and Engineering, Keio University
Publisher
The Society of Instrument and Control Engineers
Link
https://www.jstage.jst.go.jp/article/sicetr/56/4/56_208/_pdf
Reference10 articles.
1. 3) P. Xiaosheng, W. Bo, Y. Fan, F. Gaofeng, W. Zheng and C. Kai: A Deep Learning Approach for Wind Power Prediction Based on Stacked Denoising Auto Encoders Optimized by Bat Algorithm, Proc. China International Conference on Electricity Distribution (CICED), 945/948 (2018)
2. 4) H.S. Jang, K.Y. Bae, H.-S. Park and D.K. Sung: Solar Power Prediction Based on Satellite Images and Support Vector Machine, IEEE Transactions on Sustainable Energy, 7-3, 1255/1263 (2016)
3. 5) A. Asrari, T.X. Wu and B. Ramos: A Hybrid Algorithm for Short-Term Solar Power Prediction-Sunshine State Case Study, IEEE Transactions on Sustainable Energy, 8-2, 582/591 (2017)
4. 6) C. Wan, J. Wang, J. Lin, Y. Song and Z.Y. Dong: Nonparametric Prediction Intervals of Wind Power via Linear Programming, IEEE Transactions on Power Systems, 33-1, 1074/1076 (2018)
5. 7) M.J. Sanjari and H.B. Gooi: Probabilistic Forecast of PV Power Generation Based on Higher Order Markov Chain, IEEE Transactions on Power Systems, 32-4, 2942/2952 (2017)
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