电动汽车发展的社会综合效益分析  被引量:30

A preliminary investigation on the overall profit assessment of electric vehicle development to the society

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作  者:张晨曦[1] 文福拴[1] 薛禹胜[2] 袁军[3] 李波[3] 汪宏华[3] 

机构地区:[1]浙江大学电气工程学院,浙江杭州310027 [2]国网电力科学研究院南京南瑞集团公司,江苏南京210003 [3]国网浙江省电力公司电动汽车服务分公司,浙江杭州310007

出  处:《华北电力大学学报(自然科学版)》2014年第3期55-63,共9页Journal of North China Electric Power University:Natural Science Edition

基  金:国家重点基础研究发展规划(973计划)资助项目(2013CB228202);国家自然科学基金委员会(NSFC)与英国工程与自然研究理事会(EPSRC)合作研究资助项目(51361130153;51361130152);国网浙江省电力公司科技资助项目(5211DF13500M)

摘  要:在国内外电动汽车发展受到普遍重视的背景下,有必要对电动汽车发展可以给社会带来的综合效益做系统的分析,对此问题做了探索,试图形成初步的分析方法框架。首先给出了电动汽车与传统汽车的百km能耗和CO2排放量计算公式,据此评估电动汽车相对于传统汽车的节能效益和CO2减排效益。之后,在考虑了电动汽车电池的荷电状态约束、最大充放电功率约束等的情况下,基于电动汽车停驶概率分布和初始荷电量概率分布,构造了确定电动汽车参与平抑风电和常规负荷波动情况下系统所节约的旋转备用成本的优化模型,并采用粒子群算法求解;通过比较无电动汽车参与下系统平抑风电和常规负荷波动所需的备用成本计算出电动汽车提供旋转备用的效益。最后,基于2020年我国电动汽车发展规模预测和电源结构水平计算了2020年我国电动汽车行业可能实现的全社会综合效益。Under the pressure of energy security, energy saving, and emission mitigation, many countries around the globe have established supporting policies to encourage the development of electric vehicles (EVs). Given this background, it is necessary to examine the overall profit of the development of EVs to the society, and is the objective of this work. Specifically, the overall profit of EVs is evaluated based on aspects of energy saving, carbon dioxide emission reduction and EVs' potential contributions to avoided ancillary service costs of the power system concerned. Analytical methods to caculate EVs' potential profits of energy saving and emission reduction compared with traditional vehicles with internal combustion engines (ICE) are proposed. Considering EVs' constraints of the state of charge (SOC) , as well as the maximum charging/discharging power, an optimization model is presented to investigate the contribution of EVs' participation in reducing the ancillary service costs in the power system with wind power by mitigating the fluctuations of wind power outputs and load changes, and the well-established particle swarm optimization (PSO) algorithm is employed to solve the optimization model. To derive the expectation of the EVs' capability in reducing wind power and load fluctuation, the Monte Carlo simulation is utilized to simulate the probability distribution of EVs' driving/parking as well as their initial states of charge. The average level of the reduced wind power and load fluctuation can be used to calculate EVs' ancillary service profits, A scenario for the year 2020 in China is served for deminstrating the proposed method. This work is jointly supported by National Basic Research Program (973 Program) (No. 2013CB228202) , National Natural Science Foundation of China (No. 51361130153, No. 51361130152) , and a project from State Grid Zhejiang Electric Power Company (5211DF13500M).

关 键 词:电动汽车 节能效益 CO2减排 辅助服务 旋转备用 

分 类 号:TP316.2[自动化与计算机技术—计算机软件与理论] TM72[自动化与计算机技术—计算机科学与技术]

 

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