An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited i...An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.展开更多
为了探讨交通运输部门的低碳发展方向,基于LEAP(longrange energy alternatives planning system)模型建立西安市道路交通运输部门运输能源与环境模型,模拟2021—2050年不同情景下交通运输部门的能源需求、CO_(2)和污染物排放变化趋势...为了探讨交通运输部门的低碳发展方向,基于LEAP(longrange energy alternatives planning system)模型建立西安市道路交通运输部门运输能源与环境模型,模拟2021—2050年不同情景下交通运输部门的能源需求、CO_(2)和污染物排放变化趋势以及减排潜力。结果表明,低碳情景(LC)下能源消耗和CO_(2)排放在2031年左右达到峰值,2050年相对基准情景(BAU)的削减率分别为32.62%、30.21%,对CO、NO_(x)、PM_(10)减排效果较好,相对BAU削减率分别为33.88%、36.27%、40.33%;各子情景中,运输结构调整情景(TSA)节能减排贡献最大,其次为绿色汽车情景(GC)和技术性节能情景(TES);要实现交通运输部门碳减排和污染物的排放控制,需调整交通结构,淘汰老旧车型和大力发展公共交通,并不断完善相应的基础设施,提高新能源汽车的市占率。展开更多
基金Project(51606225) supported by the National Natural Science Foundation of ChinaProject(2016JJ2144) supported by Hunan Provincial Natural Science Foundation of ChinaProject(502221703) supported by Graduate Independent Explorative Innovation Foundation of Central South University,China
文摘An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.
文摘为了探讨交通运输部门的低碳发展方向,基于LEAP(longrange energy alternatives planning system)模型建立西安市道路交通运输部门运输能源与环境模型,模拟2021—2050年不同情景下交通运输部门的能源需求、CO_(2)和污染物排放变化趋势以及减排潜力。结果表明,低碳情景(LC)下能源消耗和CO_(2)排放在2031年左右达到峰值,2050年相对基准情景(BAU)的削减率分别为32.62%、30.21%,对CO、NO_(x)、PM_(10)减排效果较好,相对BAU削减率分别为33.88%、36.27%、40.33%;各子情景中,运输结构调整情景(TSA)节能减排贡献最大,其次为绿色汽车情景(GC)和技术性节能情景(TES);要实现交通运输部门碳减排和污染物的排放控制,需调整交通结构,淘汰老旧车型和大力发展公共交通,并不断完善相应的基础设施,提高新能源汽车的市占率。
