Short-Term Solar Power Forecasting via General Regression Neural Network with Grey Wolf Optimization

Chia-Sheng Tu, Wen-Chang Tsai, Chih-Ming Hong () and Whei-Min Lin
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Chia-Sheng Tu: School of Mechanical and Electrical Engineering, Xiamen University Tan Kah Kee College, Zhangzhou 363105, China
Wen-Chang Tsai: School of Mechanical and Electrical Engineering, Xiamen University Tan Kah Kee College, Zhangzhou 363105, China
Chih-Ming Hong: Department of Electronic Communication Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 811213, Taiwan
Whei-Min Lin: School of Mechanical and Electrical Engineering, Xiamen University Tan Kah Kee College, Zhangzhou 363105, China

Energies, 2022, vol. 15, issue 18, 1-20

Abstract: With the increasing awareness of environmental protection and the support of national policy, as well as the maturing of solar power generation technology, solar power generation has become one of the most promising renewable energies. However, due to changes in external factors such as season, time, weather, cloud cover, etc., solar radiation is uncertain, and it is difficult to predict energy output, even for the next hour. This inherent instability is a particularly difficult issue for the prediction of energy output in the effective operation of solar power systems. This paper proposes a grey wolf optimization (GWO)-based general regression neural network (GRNN), which is expected to provide more accurate predictions with shorter computational times. Therefore, a self-organizing map (SOM) is utilized to realize the weather clustering and the training of the GRNN with a GWO model. The performance of the proposed model is investigated using short-term and ultra-short-term forecasting in different seasons. It is very important to accurately predict the PV power output. Moreover, the numerical results demonstrate that the proposed approach can significantly enhance the prediction accuracy of PV systems.

Keywords: solar power forecasting; general regression neural network; grey wolf optimization; power generation system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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