基于灰色模型的能源状况评价与分析
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摘要
针对美国加利福尼亚州、亚利桑那州、新墨西哥州和德克萨斯州的能源状况进行数据分析,建立模型对化石燃料、可再生能源、生物质能源、木材和废料这四大品种能量剖面进行描述,并确定四个州中哪一个在2009年具有"最佳"的使用清洁、可再生能源的配置文件。经过对四个州过去十年经济系数的分析,预测出未来十年的可再生能源系数。最后利用灰色预测模型和回归模型对不同类型的预测模型进行比较,研究能量预测问题。结果表明,该模型能有效地揭示能量剖面和可再生能源消耗状况。
This paper analyses the energy status of California, Arizona, New Mexico and Texas States, and sets up a model to describe the four major energy profiles of fossil fuels, renewable energy, biomass energy, wood and waste. And determines which of the four countries has the "best" profile of clean and renewable energy in 2009. After analyzing the economic coefficients of the four states over the past ten years, we can predict the coefficient of renewable energy in the next ten years. Finally, the different types of prediction models are compared by gray prediction model and regression model, and the energy prediction problem is studied. The results show that the model can effectively reveal the energy profile and the consumption of renewable energy.
This paper analyses the energy status of California, Arizona, New Mexico and Texas States, and sets up a model to describe the four major energy profiles of fossil fuels, renewable energy, biomass energy, wood and waste. And determines which of the four countries has the "best" profile of clean and renewable energy in 2009. After analyzing the economic coefficients of the four states over the past ten years, we can predict the coefficient of renewable energy in the next ten years. Finally, the different types of prediction models are compared by gray prediction model and regression model, and the energy prediction problem is studied. The results show that the model can effectively reveal the energy profile and the consumption of renewable energy.
引文
[1] 张丽峰.中国能源供求预测模型及发展对策研究[D].北京:首都经济贸易大学,2006.
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[4] Nai-ming Xie,Chao-qing Yuan,Ying-jie Yang.Forecasting China’s energy demand and self-sufficiency rate by grey forecasting model and Markov model[J].International Journal of Electrical Power and Energy Systems,2015,66,1-8.
[5] Jie Cui,Si-feng Liu,Bo Zeng,Nai-ming Xie.A novel grey forecasting model and its optimization[J].Applied Mathematical Modelling.2013,37(6),4399-4406.
[6] Luca Massidda,Marino Marrocu.Use of Multilinear Adaptive Regression Splines and numerical weather prediction to forecast the power output of a PV plant in Borkum,Germany[J].Solar Energy,2017,146,141-149.
[7] Luka Lugaric,Slavko Krajcar.Transforming cities towards sustainable low-carbon energy systems using emergy synthesis for support in decision making[J].Energy Policy,2016,98,471-482.
[8] Chaoqing Yuan,Dejin Song,Benhai Guo,Naiming Xie.Prediction of China’s energy consumption structure[J].Kybernetes.2012,41(5/6),559-567.
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[10] 徐华锋,李玲玲,方志耕.灰色双矩阵博弈模型及其均衡解[J].数学的实践与认识.2012,42(10),174-179.
[11] 徐华锋,刘思锋,方志耕.GM(1,1)模型灰色作用量的优化[J].数学的实践与认识.2010,40(2),26-32.
[2] Ram M.Shrestha,Sunil Malla,Migara H.Liyanage.Scenario-based analyses of energy system development and its environmental implications in Thailand[J].Energy Policy,2007,35(6),3179-3193.
[3] Naiming Xie,Alan D.Pearman.Forecasting energy consumption in China following instigation of an energy-saving policy[J].Natural Hazards.2014,74(2),639-659.
[4] Nai-ming Xie,Chao-qing Yuan,Ying-jie Yang.Forecasting China’s energy demand and self-sufficiency rate by grey forecasting model and Markov model[J].International Journal of Electrical Power and Energy Systems,2015,66,1-8.
[5] Jie Cui,Si-feng Liu,Bo Zeng,Nai-ming Xie.A novel grey forecasting model and its optimization[J].Applied Mathematical Modelling.2013,37(6),4399-4406.
[6] Luca Massidda,Marino Marrocu.Use of Multilinear Adaptive Regression Splines and numerical weather prediction to forecast the power output of a PV plant in Borkum,Germany[J].Solar Energy,2017,146,141-149.
[7] Luka Lugaric,Slavko Krajcar.Transforming cities towards sustainable low-carbon energy systems using emergy synthesis for support in decision making[J].Energy Policy,2016,98,471-482.
[8] Chaoqing Yuan,Dejin Song,Benhai Guo,Naiming Xie.Prediction of China’s energy consumption structure[J].Kybernetes.2012,41(5/6),559-567.
[9] 徐华锋,方志耕.优化白化方程的GM(1,1)模型[J].数学的实践与认识,2011,41(7),163-167.
[10] 徐华锋,李玲玲,方志耕.灰色双矩阵博弈模型及其均衡解[J].数学的实践与认识.2012,42(10),174-179.
[11] 徐华锋,刘思锋,方志耕.GM(1,1)模型灰色作用量的优化[J].数学的实践与认识.2010,40(2),26-32.