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

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.

[1]  Yong Wang,et al.  Dynamic Analysis of a Fractured Vertical Well in a Triple Media Carbonate Reservoir , 2019, Chemistry and Technology of Fuels and Oils.

[2]  Wenqing Wu,et al.  Application of the novel fractional grey model FAGMO(1,1,k) to predict China's nuclear energy consumption , 2018, Energy.

[3]  Yimin Zhou,et al.  Random Network Transmission and Countermeasures in Containing Global Spread of COVID-19-Alike Pandemic: A Hybrid Modelling Approach , 2020, Complex..

[4]  Xinping Xiao,et al.  A new grey model for traffic flow mechanics , 2020, Eng. Appl. Artif. Intell..

[5]  Xin Ma,et al.  Carbon-dioxide mitigation in the residential building sector: A household scale-based assessment , 2019, Energy Conversion and Management.

[6]  W. Cai,et al.  Carbon dioxide intensity and income level in the Chinese megacities' residential building sector: Decomposition and decoupling analyses. , 2019, The Science of the total environment.

[7]  Akash Kumar Shukla,et al.  Review on sun tracking technology in solar PV system , 2020 .

[8]  Lei Yan,et al.  Walking Gait Phase Detection Based on Acceleration Signals Using Voting-Weighted Integrated Neural Network , 2020, Complex..

[9]  Baozhen Yao,et al.  Application of Discrete Mathematics in Urban Transportation System Analysis , 2014 .

[10]  Chaoqing Yuan,et al.  On novel grey forecasting model based on non-homogeneous index sequence , 2013 .

[11]  Deng Ju-Long,et al.  Control problems of grey systems , 1982 .

[12]  H. El-Ghetany,et al.  Comprehensive Design Tool for Sizing Solar Water Pumping System in Egypt , 2020 .

[13]  Lifeng Wu,et al.  Hybrid support vector machines with heuristic algorithms for prediction of daily diffuse solar radiation in air-polluted regions , 2020 .

[14]  Xin Ma,et al.  Predicting primary energy consumption using NDGM(1,1,k,c) model with Simpson formula , 2019, Scientia Iranica.

[15]  R. Saidur,et al.  Application of support vector machine models for forecasting solar and wind energy resources: A review , 2018, Journal of Cleaner Production.

[16]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[17]  Yong Wang,et al.  Analysis of novel FAGM(1, 1, tα) model to forecast health expenditure of China , 2019, Grey Syst. Theory Appl..

[18]  Zheng-xin Wang,et al.  Forecasting the residential solar energy consumption of the United States , 2019, Energy.

[19]  Wenqing Wu,et al.  Improved GM(1,1) model based on Simpson formula and its applications. , 2019, 1908.03493.

[20]  Qin Li,et al.  Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model , 2019, Sustainability.

[21]  Yong Wang,et al.  A novel conformable fractional non-homogeneous grey model for forecasting carbon dioxide emissions of BRICS countries. , 2019, The Science of the total environment.

[22]  Peng-Yu Chen,et al.  Foundation Settlement Prediction Based on a Novel NGM Model , 2014 .

[23]  Provas Kumar Roy,et al.  Oppositional based grey wolf optimization algorithm for economic dispatch problem of power system , 2017, Ain Shams Engineering Journal.

[24]  Weijie Zhou,et al.  The grey generalized Verhulst model and its application for forecasting Chinese pig price index , 2020, Soft Comput..

[25]  Xin Ma,et al.  A novel Grey Bernoulli model for short-term natural gas consumption forecasting , 2020 .

[26]  Wenqing Wu,et al.  Forecasting short-term renewable energy consumption of China using a novel fractional nonlinear grey Bernoulli model , 2019, Renewable Energy.

[27]  Minda Ma,et al.  Decoupling or delusion? Mapping carbon emission per capita based on the human development index in Southwest China. , 2020, The Science of the total environment.

[28]  Nima Amjady,et al.  Solar energy forecasting based on hybrid neural network and improved metaheuristic algorithm , 2018, Comput. Intell..

[29]  Bo Zeng,et al.  A Hybrid Grey Prediction Model for Small Oscillation Sequence Based on Information Decomposition , 2020, Complex..

[30]  Wenqing Wu,et al.  The conformable fractional grey system model. , 2018, ISA transactions.

[31]  Li-Chang Hsu,et al.  A genetic algorithm based nonlinear grey Bernoulli model for output forecasting in integrated circuit industry , 2010, Expert Syst. Appl..

[32]  Bo Zeng,et al.  A new-structure grey Verhulst model: Development and performance comparison , 2020 .

[33]  Zheng-Xin Wang,et al.  Modelling the nonlinear relationship between CO2 emissions and economic growth using a PSO algorithm-based grey Verhulst model , 2019, Journal of Cleaner Production.

[34]  Lifeng Wu,et al.  Predicting daily diffuse horizontal solar radiation in various climatic regions of China using support vector machine and tree-based soft computing models with local and extrinsic climatic data , 2020 .

[35]  Prashanta Kumar Patra,et al.  Forecasting of solar energy with application for a growing economy like India: Survey and implication , 2017 .

[36]  O. Mahian,et al.  A comprehensive study of techno-economic and environmental features of different solar tracking systems for residential photovoltaic installations , 2020 .

[37]  Naiming Xie,et al.  A nonlinear grey forecasting model with double shape parameters and its application , 2019, Appl. Math. Comput..

[38]  Jie Xia,et al.  Application of a new information priority accumulated grey model with time power to predict short-term wind turbine capacity , 2019, Journal of Cleaner Production.

[39]  Ugur Atikol,et al.  The effect of latitude on the performance of different solar trackers in Europe and Africa , 2016 .

[40]  Arian Bahrami,et al.  The performance and ranking pattern of PV systems incorporated with solar trackers in the northern hemisphere , 2018, Renewable and Sustainable Energy Reviews.

[41]  Bo Zeng,et al.  Modeling Method of the Grey GM(1, 1) Model with Interval Grey Action Quantity and Its Application , 2020, Complex..

[42]  C. O. Okoye,et al.  Technical and economic assessment of fixed, single and dual-axis tracking PV panels in low latitude countries , 2017 .

[43]  Nadarajah Kannan,et al.  Solar energy for future world: - A review , 2016 .

[44]  Yong Wang,et al.  Application of a novel nonlinear multivariate grey Bernoulli model to predict the tourist income of China , 2019, J. Comput. Appl. Math..

[45]  Shuo-Pei Chen,et al.  Forecasting of foreign exchange rates of Taiwan’s major trading partners by novel nonlinear Grey Bernoulli model NGBM(1, 1) , 2008 .

[46]  Lingcun Kong,et al.  Comparison study on the nonlinear parameter optimization of nonlinear grey Bernoulli model (NGBM(1, 1)) between intelligent optimizers , 2018, Grey Syst. Theory Appl..

[47]  Yong Wang,et al.  Research on a novel fractional GM(α, n) model and its applications , 2019, Grey Syst. Theory Appl..

[48]  Lifeng Wu,et al.  Potential of kernel-based nonlinear extension of Arps decline model and gradient boosting with categorical features support for predicting daily global solar radiation in humid regions , 2019, Energy Conversion and Management.

[49]  Xin Ma,et al.  A brief introduction to the Grey Machine Learning , 2018, ArXiv.

[50]  Bo Zeng,et al.  Application of a new grey prediction model and grey average weakening buffer operator to forecast China’s shale gas output , 2020 .

[51]  Ki-Hyun Kim,et al.  Solar energy: Potential and future prospects , 2018 .

[52]  Xin Ma,et al.  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 , 2019, Energy.

[53]  Mohammadamin Azimi,et al.  Carbon trading volume and price forecasting in China using multiple machine learning models , 2020 .

[54]  Huiming Duan,et al.  A novel car-following inertia gray model and its application in forecasting short-term traffic flow , 2020 .

[55]  Mohammed Ali Jallal,et al.  A novel deep neural network based on randomly occurring distributed delayed PSO algorithm for monitoring the energy produced by four dual-axis solar trackers , 2020 .