A Comparison of Hour-Ahead Solar Irradiance Forecasting Models Based on LSTM Network

Huang Xiaoqiao; Zhang Chao; Li QiongTai YonghangGao BixuanShi Junsheng

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A Comparison of Hour-Ahead Solar Irradiance Forecasting Models Based on LSTM Network

机译：A Comparison of Hour-Ahead Solar Irradiance Forecasting Models Based on LSTM Network

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The intermittence and fluctuation character of solar irradiance places severe limitations on most of its applications. The precise forecast of solar irradiance is the critical factor in predicting the output power of a photovoltaic power generation system. In the present study, Model I-A and Model II-B based on traditional long short-term memory (LSTM) are discussed, and the effects of different parameters are investigated; meanwhile, Model II-AC, Model II-AD, Model II-BC, and Model II-BD based on a novel LSTM-MLP structure with two-branch input are proposed for hour-ahead solar irradiance prediction. Different lagging time parameters and different main input and auxiliary input parameters have been discussed and analyzed. The proposed method is verified on real data over 5 years. The experimental results demonstrate that Model II-BD shows the best performance because it considers the weather information of the next moment, the root mean square error (RMSE) is 62.1618 W/m(2), the normalized root mean square error (nRMSE) is 32.2702%, and the forecast skill (FS) is 0.4477. The proposed algorithm is 19.19% more accurate than the backpropagation neural network (BPNN) in terms of RMSE.

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《Mathematical Problems in Engineering: Theory, Methods and Applications》 |2020年第30期|4251517.1-4251517.15|共15页
作者
Huang Xiaoqiao; Zhang Chao; Li QiongTai YonghangGao BixuanShi Junsheng;
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Yunnan Normal Univ, Solar Energy Res Inst, Kunming 650500, Yunnan, Peoples R China|Yunnan Normal Univ, Sch Phys & Elect Informat, Kunming 650500, Yunnan, Peoples R China|Yunnan Key Lab Optoelect Informat Technol, Kunming 650500, Yunnan, Peoples R China;

Yunnan Normal Univ, Sch Phys & Elect Informat, Kunming 650500, Yunnan, Peoples R China|Yunnan Key Lab Optoelect Informat Technol, Kunming 650500, Yunnan, Peoples R China;

Yunnan Normal Univ, Solar Energy Res Inst, Kunming 650500, Yunnan, Peoples R ChinaYunnan Normal Univ, Sch Phys & Elect Informat, Kunming 650500, Yunnan, Peoples R China;

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A Comparison of Hour-Ahead Solar Irradiance Forecasting Models Based on LSTM Network

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