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
This study aimed to investigate the cost impact of meeting the increase in freight demand by doubling the truck weight （AS 1 ）, doubling the traffic volume （AS2）, or legalizing a new-proposed-truck of 97-kip weigh...This study aimed to investigate the cost impact of meeting the increase in freight demand by doubling the truck weight （AS 1 ）, doubling the traffic volume （AS2）, or legalizing a new-proposed-truck of 97-kip weight instead of the currently legal 80-kip truck （AS3）. The State of Michigan＇s average daily traffic database of year 2001 has been used as a case study. The study was applied only on the very common US Bridge with RC （reinforced concrete） deck over steel girder. Sampling criteria also includes the age of the bridges. The study covered the four-cost-impact categories provided by the NCHRP （National Cooperative Research Program）. The current truck weight and double traffic volume （AS2） show the best scenario to meet the increase in freight demand. However, doubling the truck weight with the current traffic volume （AS 1） was the worst scenario. The use of the proposed 97-kip truck with the current traffic volume （AS3） compromises both, meeting the increase in freight demand and the cost impact.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.
基金authors gratefully acknowledge funding and support provided by NSF （National Science Foundation） （CMMI- 1100742） and NCTSPM （National Centre for Transportation Systems Productivity and Management）.
文摘This study aimed to investigate the cost impact of meeting the increase in freight demand by doubling the truck weight （AS 1 ）, doubling the traffic volume （AS2）, or legalizing a new-proposed-truck of 97-kip weight instead of the currently legal 80-kip truck （AS3）. The State of Michigan＇s average daily traffic database of year 2001 has been used as a case study. The study was applied only on the very common US Bridge with RC （reinforced concrete） deck over steel girder. Sampling criteria also includes the age of the bridges. The study covered the four-cost-impact categories provided by the NCHRP （National Cooperative Research Program）. The current truck weight and double traffic volume （AS2） show the best scenario to meet the increase in freight demand. However, doubling the truck weight with the current traffic volume （AS 1） was the worst scenario. The use of the proposed 97-kip truck with the current traffic volume （AS3） compromises both, meeting the increase in freight demand and the cost impact.
