基于最优能量状态调节的电动汽车需求响应及其对配电网的影响
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摘要
随着电动汽车数量的与日俱增,其充电负荷对配电网的影响变得越来越不可忽视。电动汽车作为一种可延迟负荷,需求响应(demand response,DR)潜力巨大,对其进行合理控制可以辅助配电网安全经济运行。文章建立了单台电动汽车的迟滞充电负荷模型,基于配电网分层控制架构,引入集群电动汽车参与需求响应的最优能量状态调节量控制策略(optimal energy status regulation control strategy,OESRCS),该策略通过对电动汽车能量状态设定点施加最优调节量,实现对集群电动汽车充电过程的实时控制。在此基础上,制定了配电网电压变化百分比和网络损耗百分比这2个指标对需求响应效果进行评估。仿真结果表明,利用OESRCS策略,电动汽车可以精确地跟踪目标功率,同时配电网电压波动和网络损耗均有所减小。
With the increasing number of electric vehicles,the impact of charging load on the distribution network cannot be ignored. As deferrable loads,the electric vehicles have great potential for demand response(DR). Rational control on them can assist the safe and economic operation of distribution network. This paper establishes the hysteresis charging load model of a single electric vehicle. Based on the hierarchical control structure of distribution network,the paper introduces the optimal energy status regulation control strategy( OESRCS) for the participation of cluster electric vehicles in demand response,which can realize the real-time control of the charging process of the cluster electric vehicles by applying the optimal adjustment amount to the energy state set point of electric vehicle. On this basis,two indicators named percentage of distribution-voltage change and percentage of network losses are formulated to evaluate the effect of demand response. Simulation results show that by using OESRCS strategy,the electric vehicles can accurately track the target power,and the voltage fluctuation and netw ork loss of the distribution network are reduced at the same time.
With the increasing number of electric vehicles,the impact of charging load on the distribution network cannot be ignored. As deferrable loads,the electric vehicles have great potential for demand response(DR). Rational control on them can assist the safe and economic operation of distribution network. This paper establishes the hysteresis charging load model of a single electric vehicle. Based on the hierarchical control structure of distribution network,the paper introduces the optimal energy status regulation control strategy( OESRCS) for the participation of cluster electric vehicles in demand response,which can realize the real-time control of the charging process of the cluster electric vehicles by applying the optimal adjustment amount to the energy state set point of electric vehicle. On this basis,two indicators named percentage of distribution-voltage change and percentage of network losses are formulated to evaluate the effect of demand response. Simulation results show that by using OESRCS strategy,the electric vehicles can accurately track the target power,and the voltage fluctuation and netw ork loss of the distribution network are reduced at the same time.
引文
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[19]PARKINSON S,WANG D,CRAWFORD C,et al.Wind integration in self-regulating electric load distributions[J].Energy Systems,2012,3(4):341-377.
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[21]田立亭,史双龙,贾卓.电动汽车充电功率需求的统计学建模方法[J].电网技术,2010,34(11):126-130.TIAN Liting,SHI Shuanglong,JIA Zhuo.A statistical model for charging pow er demand of electric vehicles[J].Pow er System Technology,2010,34(11):126-130.
[22]LU N.An evaluation of the HVAC load potential for providing load balancing service[J].IEEE Transactions on Smart Grid,2012,3(3):1263-1270.
[2]新能源汽车杂谈.2016年全球新能源汽车市场总结[EB/OL].(2017-02-06)[2018-01-03].http://www.vccoo.com/v/90q72v.
[3]中商情报网.2016年全球新能源汽车市场产销数据分析[EB/OL].(2017-02-18)[2018-01-03].http://w ww.askci.com/new s/chanye/20170218/12281490920.shtml.
[4]US Department of Energy.Benefits of demand response in electricity markets and recommendations for achieving them:a report to the united state congress pursuant to section 1252 of the energy policy act of 2005[R/OL].(2008-02-21)[2018-01-03].http://w ww.oe.energy,gov/Document M edia/congress_1252d.pdf.
[5]Federal Energy Regulatory Commission.Assessment of demand response and advanced metering:2006 staff report[R/OL].(2008-08-21)[2018-01-03].http://w ww.ferc.gov/legal/staff-reports/demand-reaponse.pdf.
[6]Federal Energy Regulatory Commission.Assessment of demand response and advanced metering:2007 staff report[R/OL].(2008-09-13)[2018-01-03].http://w ww.ferc.gov/legal/staff-reports/09-07-demand-reaponse.pdf.
[7]张钦,王锡凡,王建学,等.电力市场下需求响应研究综述[J].电力系统自动化,2008,32(3):97-107.ZHANG Qin,WANG Xifan,WANG Jianxue,et al.Survey of demand response research in deregulated electricity markets[J].Automation of Electric Pow er Systems,2008,32(3):97-107.
[8]NOLAN S,O’MALLEY M.Challenges and barriers to demand response deployment and evaluation[J].Applied Energy,2015,152:1-10.
[9]WANG J,BLOYD C N,HU Z,et al.Demand response in China[J].Energy,2010,35(4):1592-1597.
[10]潘樟惠,高赐威.基于需求响应的电动汽车经济调度[J].电力建设,2015,36(7):139-145.PAN Zhanghui,GAO Ciw ei.Economic dispatch of electric vehicles based on demand response[J].Electric Pow er Construction,2015,36(7):139-145.
[11]PAVIC I,CAPUDER T,KUZLE I.Value of flexible electric vehicles in providing spinning reserve services[J].Applied Energy,2015,157:60-74.
[12]YAO E,WONG V W S,SCHOBER R.Robust frequency regulation capacity scheduling algorithm for electric vehicles[J].IEEE Transactions on Smart Grid,2017,8(2):984-997.
[13]MA Z,CALLAWAY D S,HISKENS I A.Decentralized charging control of large populations of plug-in electric vehicles[J].IEEE Transactions on Control Systems Technology,2013,21(1):67-78.
[14]KUMAR K N,SIVANEASAN B,SO P L.Impact of priority criteria on electric vehicle charge scheduling[J].IEEE Transactions on Transportation Electrification,2015,1(3):200-210.
[15]KUMAR K N,TSENG K J.Impact of demand response management on chargeability of electric vehicles[J].Energy,2016,111:190-196.
[16]孙强,许方园,唐佳,等.基于需求响应的电动汽车集群充电负荷建模及容量边界控制策略[J].电网技术,2016,40(9):2638-2645.SUN Qiang,XU Fangyuan,TANG Jia,et al.Study on modeling of aggregated charging load of electric vehicles and control strategy by adjusting capacity boundaries based on demand response[J].Pow er System Technology,2016,40(9):2638-2645.
[17]WANG D,ZHOU Y,JIA H,et al.An energy-constrained state priority list model using deferrable electrolyzers as a load management mechanism[J].Applied energy,2016,167:201-210.
[18]高赐威,李倩玉,李慧星,等.基于负荷聚合商业务的需求响应资源整合方法与运营机制[J].电力系统自动化,2013,37(17):78-86.GAO Ciw ei,LI Qianyu,LI Huixing,et al.M ethodology and operation mechanism of demand response resources integration based on load aggregator[J].Automation of Electric Pow er Systems,2013,37(17):78-86.
[19]PARKINSON S,WANG D,CRAWFORD C,et al.Wind integration in self-regulating electric load distributions[J].Energy Systems,2012,3(4):341-377.
[20]KASHYAP A,CALLAWAY D.Controlling distributed energy constrained resources for pow er system ancillary services[C]//2010IEEE 11th International Conference on Probabilistic M ethods Applied to Pow er Systems(PM APS).IEEE,2010:407-412.
[21]田立亭,史双龙,贾卓.电动汽车充电功率需求的统计学建模方法[J].电网技术,2010,34(11):126-130.TIAN Liting,SHI Shuanglong,JIA Zhuo.A statistical model for charging pow er demand of electric vehicles[J].Pow er System Technology,2010,34(11):126-130.
[22]LU N.An evaluation of the HVAC load potential for providing load balancing service[J].IEEE Transactions on Smart Grid,2012,3(3):1263-1270.