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Forecasting short-term solar energy generation in Asia Pacific using a nonlinear grey Bernoulli model with time power term

Author

Listed:
  • Wenqing Wu
  • Xin Ma
  • Bo Zeng
  • Yuanyuan Zhang
  • Wanpeng Li

Abstract

Solar energy as one type of renewable energy is the cleanest and most abundant energy source available. It is mainly used for photovoltaics, solar heating and cooling, and solar power generation. With the crisis of energy and environment, the solar energy generation is becoming a research hotspot in clean energy production. In this paper, the solar energy generation in Asia Pacific including Australia, South Korea, China, Japan and India are studied by a new nonlinear univariate grey Bernoulli model with time power term. Analytical solution of the model is derived by the grey technique, the theory of ordinary differential equations and the two-point Gauss quadrature rule of integration. And the nonlinear parameters are determined by the grey wolf optimizer and the linearized form of the new model. According to historical data from 2011 to 2018 stated by British Petroleum, forecasting models are built to calculate the solar energy generation of the five countries from 2019 to 2023.

Suggested Citation

  • Wenqing Wu & Xin Ma & Bo Zeng & Yuanyuan Zhang & Wanpeng Li, 2021. "Forecasting short-term solar energy generation in Asia Pacific using a nonlinear grey Bernoulli model with time power term," Energy & Environment, , vol. 32(5), pages 759-783, August.
  • Handle: RePEc:sae:engenv:v:32:y:2021:i:5:p:759-783
    DOI: 10.1177/0958305X20960700
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    References listed on IDEAS

    as
    1. Bo Zeng & Xin Ma & Juanjuan Shi, 2020. "Modeling Method of the Grey GM(1,1) Model with Interval Grey Action Quantity and Its Application," Complexity, Hindawi, vol. 2020, pages 1-10, January.
    2. Ling-Ling Pei & Qin Li, 2019. "Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model," Sustainability, MDPI, vol. 11(5), pages 1-15, February.
    3. Wang, Zheng-Xin & He, Ling-Yang & Zheng, Hong-Hao, 2019. "Forecasting the residential solar energy consumption of the United States," Energy, Elsevier, vol. 178(C), pages 610-623.
    4. Liu, Xiaomei & Xie, Naiming, 2019. "A nonlinear grey forecasting model with double shape parameters and its application," Applied Mathematics and Computation, Elsevier, vol. 360(C), pages 203-212.
    5. Fan, Junliang & Wu, Lifeng & Ma, Xin & Zhou, Hanmi & Zhang, Fucang, 2020. "Hybrid support vector machines with heuristic algorithms for prediction of daily diffuse solar radiation in air-polluted regions," Renewable Energy, Elsevier, vol. 145(C), pages 2034-2045.
    6. Peng-Yu Chen & Hong-Ming Yu, 2014. "Foundation Settlement Prediction Based on a Novel NGM Model," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-8, March.
    7. Bahrami, Arian & Okoye, Chiemeka Onyeka, 2018. "The performance and ranking pattern of PV systems incorporated with solar trackers in the northern hemisphere," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 138-151.
    8. Bahrami, Arian & Okoye, Chiemeka Onyeka & Atikol, Ugur, 2016. "The effect of latitude on the performance of different solar trackers in Europe and Africa," Applied Energy, Elsevier, vol. 177(C), pages 896-906.
    9. Kannan, Nadarajah & Vakeesan, Divagar, 2016. "Solar energy for future world: - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1092-1105.
    10. Ali Jallal, Mohammed & Chabaa, Samira & Zeroual, Abdelouhab, 2020. "A novel deep neural network based on randomly occurring distributed delayed PSO algorithm for monitoring the energy produced by four dual-axis solar trackers," Renewable Energy, Elsevier, vol. 149(C), pages 1182-1196.
    11. Bahrami, Arian & Okoye, Chiemeka Onyeka & Atikol, Ugur, 2017. "Technical and economic assessment of fixed, single and dual-axis tracking PV panels in low latitude countries," Renewable Energy, Elsevier, vol. 113(C), pages 563-579.
    12. Wu, Wenqing & Ma, Xin & Zeng, Bo & Wang, Yong & Cai, Wei, 2019. "Forecasting short-term renewable energy consumption of China using a novel fractional nonlinear grey Bernoulli model," Renewable Energy, Elsevier, vol. 140(C), pages 70-87.
    13. Ma, Xin & Mei, Xie & Wu, Wenqing & Wu, Xinxing & Zeng, Bo, 2019. "A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China," Energy, Elsevier, vol. 178(C), pages 487-507.
    14. Meng Zhou & Bo Zeng & Wenhao Zhou, 2020. "A Hybrid Grey Prediction Model for Small Oscillation Sequence Based on Information Decomposition," Complexity, Hindawi, vol. 2020, pages 1-13, January.
    15. Mohanty, Sthitapragyan & Patra, Prashanta K. & Sahoo, Sudhansu S. & Mohanty, Asit, 2017. "Forecasting of solar energy with application for a growing economy like India: Survey and implication," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 539-553.
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