Hybrid LEAP modeling method for long-term energy demand forecasting of regions with limited statistical data

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.

Policy Options for Sustainable Development in Urban Transport:Analysis of Energy Consumption and Environmental Benefit Influenced by Different Transport Policies in Beijing

Transportation is a sector with high energy consumption as well as high emissions.Generally speaking,economic growth will inevitably lead to the increase of travel demand and vehicle population,which in turn results into the augmentation of environmental and social costs.For metropolis like Beijing under rapid development,there exist various possibilities and options for transport development policy instruments.But there is no guarantee that they will be suitable for Beijing,although they are effective in their local places.This article assesses what kind of policy can most effectively improve the traffic conditions in Beijing in the future.After literature reviews on the practices of foreign policy and we established several feasible scenarios.Then,we used the Long Range Energy Alternatives Planning System(LREAP) analyzed their corresponding results of reduced energy consumption and emissions.Finally,by simulating and computing the realistic Beijing transportation scenarios,this paper scientifically assesses what kind of policy can most effectively improve the traffic condition in Beijing in the coming decade.

Assessment of energy consumption,environmental effects and fuel costs of the bus rapid transit system in Bogotá(Colombia)

Colombia aims to boost the utilization of mass transportation systems in its major cities while simultaneously reducing greenhouse gas emissions by 20%,in alignment with the commitments of the COP21 agreement.In 2020,the transport sector in Colombia accounted for 34.4%of the country’s energy demand and was responsible for~49%of its total CO_(2) emissions.This article presents an assessment of energy consumption,environmental effects and the fuel costs of Bogotá’s bus rapid transit system based on the Activity,Share,Intensity,Fuel methodology.A long-term analysis spanning from 2021 to 2040 was developed using the long-range energy alternatives planning platform.To conduct this assessment,the tool was calibrated using data from 2019 and 2020.Four distinct scenarios based on energy policies implemented in Bogotáwere examined:Business as Usual,Fast Transition,High Growth and Low Growth.Regarding energy consumption and environmental effects,the results underscore the pivotal role of diversifying energy sources and reducing reliance on fossil fuels such as oil.Consequently,the analysis emphasizes the urgent need to accelerate the transition to alternative energy sources such as natural gas and electricity.