资源科学 ›› 2017, Vol. 39 ›› Issue (3): 482-489.doi: 10.18402/resci.2017.03.10

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基于LEAP模型的长沙市能源需求预测及对策研究

陈睿(), 饶政华, 刘继雄, 谌盈盈, 廖胜明()   

  1. 中南大学能源科学与工程学院,长沙 410083
  • 收稿日期:2016-08-01 修回日期:2016-11-25 出版日期:2017-03-20 发布日期:2017-03-20
  • 作者简介:

    作者简介:陈睿,女,内蒙古海拉尔人,博士生,研究方向为能源系统工程。E-mail:378853914@qq.com

  • 基金资助:
    长沙市政府项目(CSCG-201505040005)

Prediction of energy demand and policy analysis of Changsha based on LEAP Model

Rui CHEN(), Zhenghua RAO, Jixiong LIU, Yingying CHEN, Shengming LIAO()   

  1. Central South University,School of Energy Science and Engineering,Changsha 410083,China
  • Received:2016-08-01 Revised:2016-11-25 Online:2017-03-20 Published:2017-03-20

摘要:

能源是城市运行和可持续发展的重要因素,根据城市特点及其实际发展需要进行能源需求预测具有重要意义。本文采用LEAP模型预测了不同情景下湖南长沙市2015-2020年的能源需求,讨论了GDP增速、产业结构和节能目标对未来能源需求的影响。研究结果表明,GDP增速对能源消费总量和能源强度影响显著,对分部门能源消费结构影响较小;产业结构对分部门能源消费结构影响较显著,对能源消费总量和能源强度影响较小。节能情景(单位GDP能耗2020年较2015年降低15%)下,全市能源消费总量达4014万tce,较基础情景减少317万tce。该情景预测了工业、建筑、交通及居民生活部门实施节能政策的效果,其中第三产业相对节能率最高为13.4%;工业部门其次为6.2%,交通和居民生活部门相对节能率也均超过4%。

关键词: 能流图, 能源需求预测, LEAP模型, 情景分析, 能源政策, 长沙市

Abstract:

Because energy plays an important role in ensuring the safe operation and sustainable development of cities,it is crucial to forecast energy demands according to actual urban development needs and characteristics. Here,we used LEAP model to predict the total amount of energy demand in Changsha from 2015 to 2020 based on historical economic development and energy consumption data. We used scenario analysis to design five types of scenarios to discuss the impact of GDP growth rate,industrial structure and energy-saving object on future energy demand. These scenarios included baseline scenario,different GDP growth rate scenario,different industrial structure scenario,energy saving scenario and comprehensive scenario. The results showed a significant influence of GDP growth rate on total amount of energy consumption and energy intensity and non-significant effect on the energy consumption structure of sectors. Industrial structure had an impact on the energy consumption structure of sectors and not on the total amount of energy consumption and energy intensity. Under an energy saving scenario (a goal of energy intensity reduction by 15% in 2020 compared to 2015), energy consumption reached 40 140 thousand ton coal equivalent (tce)and less 3170 thousand tce than the baseline scenario. This scenario also predicted the effect of energy-saving policies implemented in the industry,building,transportation and residential sectors. When compared with the baseline scenario,the tertiary industry accounted for the largest proportion of energy-saving with a relative energy-saving rate of 13.4% and industry had a lower energy-saving proportion with a relative energy-saving rate of 6.2%. At the same time,the energy-saving proportion of transportation and residential sector also exceeded 4%.

Key words: energy flow diagram, energy demand prediction, LEAP model, scenario analysis, energy policy, Changsha City