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Inter-Hour Forecast of Solar Radiation Based on the Structural Equation Model and Ensemble Model

Author

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  • Tingting Zhu

    (College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China
    Key Laboratory of Measurement and Control of Complex Systems of Engineering (Southeast University), Ministry of Education, Nanjing 210096, China
    The two authors contributed equally to this work.)

  • Yiren Guo

    (College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China
    The two authors contributed equally to this work.)

  • Cong Wang

    (College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Chao Ni

    (College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China)

Abstract

Given the wide applications of photovoltaic (PV) power generation, the volatility in generation caused by solar radiation, which limits the capacity of the power grid, cannot be ignored. Therefore, much research has aimed to address this issue through the development of methods for accurately predicting inter-hour solar radiation and then estimating PV power. However, most forecasting methods focus on adjusting the model structure or model parameters to achieve prediction accuracy. There is little research discussing how different factors influence solar radiation and, thereby, the effectiveness of these data-driven methods regarding their prediction accuracy. In this work, the effects of several potential factors on solar radiation are estimated using correlation analysis and a structural equation model; an ensemble model is developed for predicting inter-hour solar radiation based on the interaction of those key factors. Several experiments are carried out based on an open database provided by the National Renewable Energy Laboratory. The results show that solar zenith angle, cloud cover, aerosols, and airmass have great effects on solar radiation. It is also shown that the selection of the key factor is more important than the model structure construction for predicting solar radiation precisely. The proposed ensemble model proves to outperform all sub-models and achieves about a 12% improvement over the persistent model based on the normalized root mean squared error statistic.

Suggested Citation

  • Tingting Zhu & Yiren Guo & Cong Wang & Chao Ni, 2020. "Inter-Hour Forecast of Solar Radiation Based on the Structural Equation Model and Ensemble Model," Energies, MDPI, vol. 13(17), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4534-:d:407463
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    References listed on IDEAS

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    Cited by:

    1. Aleksander Radovan & Viktor Šunde & Danijel Kučak & Željko Ban, 2021. "Solar Irradiance Forecast Based on Cloud Movement Prediction," Energies, MDPI, vol. 14(13), pages 1-25, June.
    2. Tingting Zhu & Yuanzhe Li & Zhenye Li & Yiren Guo & Chao Ni, 2022. "Inter-Hour Forecast of Solar Radiation Based on Long Short-Term Memory with Attention Mechanism and Genetic Algorithm," Energies, MDPI, vol. 15(3), pages 1-14, January.
    3. Hongbo Zhu & Bing Zhang & Weidong Song & Jiguang Dai & Xinmei Lan & Xinyue Chang, 2023. "Power-Weighted Prediction of Photovoltaic Power Generation in the Context of Structural Equation Modeling," Sustainability, MDPI, vol. 15(14), pages 1-18, July.

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