Research on power prediction of photovoltaic power station based on similar hour and LM-BP neural network

Qiang Zhang; Gang Liu; Xiangzhong Wei

doi:10.1051/e3sconf/202125201056

All issues

Volume 252 (2021)

E3S Web Conf., 252 (2021) 01056

References

Open Access

Issue		E3S Web Conf. Volume 252, 2021 2021 International Conference on Power Grid System and Green Energy (PGSGE 2021)


Article Number		01056
Number of page(s)		5
Section		Power Control Technology and Smart Grid Application
DOI		https://doi.org/10.1051/e3sconf/202125201056
Published online		23 April 2021

Du, E. (2018) The Role of Concentrating Solar Power Toward High Renewable Energy Penetrated Power Systems. J. IEEE Transactions on Power Systems, 33: 6630–6641. [Google Scholar]
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Chai, M., Xia, F., Hao, S. (2019) PV Power Prediction Based on LSTM With Adaptive Hyperparameter Adjustment. J. IEEE Access, 7: 115473–115486. [Google Scholar]
Sadamoto, T., Ishizaki, T., Koike, M. (2015) Spatiotemporally Multiresolutional Optimization Toward Supply-Demand-Storage Balancing Under PV Prediction Uncertainty. J. IEEE Transactions on Smart Grid, 6: 853–865. [Google Scholar]
Liu, J., Fang, W., Zhang, X. (2015) An Improved Photovoltaic Power Forecasting Model With the Assistance of Aerosol Index Data. J. Transactions on Sustainable Energy, 6: 434–442. [Google Scholar]
Lee, S., Jin, H., Vecchietti, L.F. (2020) Short-Term Predictive Power Management of PV-Powered Nanogrids. J. IEEE Access, 8: 147839–147857. [Google Scholar]
Wan, C. Lin, J., Song, Y. (2017) Probabilistic Forecasting of Photovoltaic Generation: An Efficient Statistical Approach. J. IEEE Transactions on Power Systems, 32: 2471–2472. [Google Scholar]
Sanjari, M.J., Gooi, H.B., Nair, N.C. (2020) Power Generation Forecast of Hybrid PV–Wind System. J. IEEE Transactions on Sustainable Energy, 11: 703–712. [Google Scholar]

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[1] Du, E. (2018) The Role of Concentrating Solar Power Toward High Renewable Energy Penetrated Power Systems. J. IEEE Transactions on Power Systems, 33: 6630–6641. [Google Scholar]

[2] Kou, G., Chen, L., VanSant, P. (2020) Fault Characteristics of Distributed Solar Generation. J. IEEE Transactions on Power Delivery, 35: 1062–1064. [Google Scholar]

[3] Chai, M., Xia, F., Hao, S. (2019) PV Power Prediction Based on LSTM With Adaptive Hyperparameter Adjustment. J. IEEE Access, 7: 115473–115486. [Google Scholar]

[4] Sadamoto, T., Ishizaki, T., Koike, M. (2015) Spatiotemporally Multiresolutional Optimization Toward Supply-Demand-Storage Balancing Under PV Prediction Uncertainty. J. IEEE Transactions on Smart Grid, 6: 853–865. [Google Scholar]

[5] Liu, J., Fang, W., Zhang, X. (2015) An Improved Photovoltaic Power Forecasting Model With the Assistance of Aerosol Index Data. J. Transactions on Sustainable Energy, 6: 434–442. [Google Scholar]

[6] Lee, S., Jin, H., Vecchietti, L.F. (2020) Short-Term Predictive Power Management of PV-Powered Nanogrids. J. IEEE Access, 8: 147839–147857. [Google Scholar]

[7] Wan, C. Lin, J., Song, Y. (2017) Probabilistic Forecasting of Photovoltaic Generation: An Efficient Statistical Approach. J. IEEE Transactions on Power Systems, 32: 2471–2472. [Google Scholar]

[8] Sanjari, M.J., Gooi, H.B., Nair, N.C. (2020) Power Generation Forecast of Hybrid PV–Wind System. J. IEEE Transactions on Sustainable Energy, 11: 703–712. [Google Scholar]