RESEARCH ON JOINT FORECASTING OF WIND AND SOLAR POWER CONSIDERING COMPLEMENTARITY

Yue Qian; Ren Guorui; Wang Wei

doi:10.19912/j.0254-0096.tynxb.2025-0614

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Acta Energiae Solaris Sinica ›› 2026, Vol. 47 ›› Issue (8) : 773-780. DOI: 10.19912/j.0254-0096.tynxb.2025-0614

RESEARCH ON JOINT FORECASTING OF WIND AND SOLAR POWER CONSIDERING COMPLEMENTARITY

Yue Qian, Ren Guorui, Wang Wei

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Abstract

Based on the complementary characteristics of wind and solar energy resources in time and space distribution, this paper proposes a joint forecasting strategy of wind and solar power considering complementarity. Based on the bidirectional long short-term memory neural network, a basic forecasting model is established, and a sorting comparison optimization algorithm is further proposed to optimize the parameters of the forecasting model. On this basis, the joint forecasting of wind and solar power is carried out for wind and solar stations with significant complementarity. The prediction experiments show that compared with the single prediction of wind power and photovoltaic power, the proposed joint prediction method of wind power and photovoltaic power considering complementarity can significantly improve the accuracy of prediction, and the more significant the complementarity is, the higher the accuracy of joint prediction of wind power and photovoltaic power is.

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renewable energy / forecasting / neural network / wind-solar hybrid system / sorting and comparative optimization algorithm

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Yue Qian, Ren Guorui, Wang Wei. RESEARCH ON JOINT FORECASTING OF WIND AND SOLAR POWER CONSIDERING COMPLEMENTARITY[J]. Acta Energiae Solaris Sinica. 2026, 47(8): 773-780 https://doi.org/10.19912/j.0254-0096.tynxb.2025-0614

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