基于电价响应模型的电动汽车充电优化策略
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摘要
大量的电动汽车接入电网充电需要考虑经济效益和系统稳定性的影响,为了减少由于电动汽车的无序充电对配电网负荷引起的较大波动,提出了一种基于电价响应和电网激励的电动汽车有序充电优化策略。首先,在充分考虑用户的充电需求和电网安全运行的基础上,以负荷最小峰谷差为目标函数,采用遗传算法求取峰谷时段电动汽车充电数量最优解;其次,构建了电动汽车峰谷电价优化模型,建立了电动汽车充电数量与峰谷电价之间的关系,实现了电动汽车充电价格的最优定价机制;最后,考虑到充电站运营商实施分时电价前后的总收益不受损害,引入了电网公司为减少负荷峰谷差而给出的激励机制。通过对算例的分析,提出了基于电价引导的电动汽车有序充电策略,在降低了运营商的购电成本和用户充电成本的同时,实现了系统负荷削峰填谷的目的,验证了所提控制策略在节约能源方面具有有效性和合理性。
The charging of massive electric vehicles joined into the grid needs to consider the effects of economic benefits and system stability. In order to reduce the large fluctuations caused by the disordered charging of electric vehicles to the distribution network load,an electric vehicle based on electricity price response and grid excitation is proposed,which is an ordered charging optimization strategy. Firstly,on the basis of fully considering the user's charging demand and the safe operation of the powergrid,the minimum peak-to-valley difference is used as the objective function,and the genetic algorithm is used to obtain the optimal solution of the electric vehicle charging quantity in the peak-to-valley period. Secondly,the electric vehicle peak is constructed. The valley electricity price optimization model establishes the relationship between the quantity of electric vehicle charging and the peak-to-valley electricity price,and realizes the optimal pricing mechanism for the charging price of electric vehicles. Finally,considering that the charging station operators' total revenue before and after the implementation of the time-sharing electricity price is not damaged,the incentive mechanism given by the grid corporation to reduce the peak-to-valley difference is introduced. Based on the analysis of the example,the orderly charging strategy of electric vehicle based on electricity price guidance is proposed. At the same time,the operator's electricity purchase cost and user charging cost are reduced. The purpose of system load peaking and valley filling is realized,and the control strategy is verified,effective and reasonable.
The charging of massive electric vehicles joined into the grid needs to consider the effects of economic benefits and system stability. In order to reduce the large fluctuations caused by the disordered charging of electric vehicles to the distribution network load,an electric vehicle based on electricity price response and grid excitation is proposed,which is an ordered charging optimization strategy. Firstly,on the basis of fully considering the user's charging demand and the safe operation of the powergrid,the minimum peak-to-valley difference is used as the objective function,and the genetic algorithm is used to obtain the optimal solution of the electric vehicle charging quantity in the peak-to-valley period. Secondly,the electric vehicle peak is constructed. The valley electricity price optimization model establishes the relationship between the quantity of electric vehicle charging and the peak-to-valley electricity price,and realizes the optimal pricing mechanism for the charging price of electric vehicles. Finally,considering that the charging station operators' total revenue before and after the implementation of the time-sharing electricity price is not damaged,the incentive mechanism given by the grid corporation to reduce the peak-to-valley difference is introduced. Based on the analysis of the example,the orderly charging strategy of electric vehicle based on electricity price guidance is proposed. At the same time,the operator's electricity purchase cost and user charging cost are reduced. The purpose of system load peaking and valley filling is realized,and the control strategy is verified,effective and reasonable.
引文
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[13]张良,严正,冯冬涵,等.采用两阶段优化模型的电动汽车充电站内有序充电策略[J].电网技术,2014,38(4):967-973.
[14]徐智威,胡泽春,宋永华,等.基于动态分时电价的电动汽车充电站有序充电策略[J].中国电机工程学报,2014,34(22):3638-3646.
[15]杨健维,苟方杰,黄宇,等.基于不确定性测度的居民小区电动汽车充电分时电价制定策略[J].电网技术,2018,42(1):96-102.
[16]钟小强.居民区的规模化电动汽车有序充电控制策略研究[J].电测与仪表,2018,55(12):88-91,107.
[17]黄一诺,郭创新,王力成,等.考虑用户满意度的电动汽车分群调度策略[J].电力系统自动化,2015,39(17):183-191.
[18]孙波,王振兴,孙佳佳.电动汽车峰谷分时充放电价同步优化模型研究[J].电网与清洁能源,2017,33(2):130-136.
[2]朱成章.对我国发展纯电动汽车的质疑与思考[J].中外能源,2010,15(9):11-15.
[3]胡泽春,宋永华,徐智威,等.电动汽车接入电网的影响与利用[J].中国电机工程学报,2012,32(4):1-10.
[4]陈艳,孙振胜,陈超,等.智能电网下电动汽车直接负荷控制策略研究[J].电网与清洁能源,2017,33(10):116-123.
[5]黄润,周鑫,严正,等.计及电动汽车不确定性的有序充电调度策略[J].现代电力,2012,29(3):57-63.
[6]罗卓伟,胡泽春,宋永华,等.电动汽车充电负荷计算方法[J].电力系统自动化,2011,35(14):36-42.
[7]齐先军,李冬伟,纪姝彦.采用功率限制的住宅区电动汽车有序充电控制策略[J].电网技术,2016,40(12):3715-3721.
[8]孙晓明,王玮,苏粟,等.基于分时电价的电动汽车有序充电控制策略设计[J].电力系统自动化,2013,37(1):191-195.
[9]IKEGAMI T,YANO H,KUDO K,et al.Effectsof smart charging of multiple electric vehicles in reducing power generation fuel cost[J].IEEJ Transactions on Power and Energy,2013,133(6):562-574.
[10]苏粟,刘紫琦,王世丹,等.基于用户驾驶行为特性的电动汽车有序充电策略[J].电力自动化设备,2018,38(3):63-71.
[11]葛少云,黄镠,刘洪.电动汽车有序充电的峰谷电价时段优化[J].电力系统保护与控制,2012,40(10):1-5.
[12]苏海锋,梁志瑞.基于峰谷电价的家用电动汽车居民小区有序充电控制方法[J].电力自动化设备,2015,35(6):17-22.
[13]张良,严正,冯冬涵,等.采用两阶段优化模型的电动汽车充电站内有序充电策略[J].电网技术,2014,38(4):967-973.
[14]徐智威,胡泽春,宋永华,等.基于动态分时电价的电动汽车充电站有序充电策略[J].中国电机工程学报,2014,34(22):3638-3646.
[15]杨健维,苟方杰,黄宇,等.基于不确定性测度的居民小区电动汽车充电分时电价制定策略[J].电网技术,2018,42(1):96-102.
[16]钟小强.居民区的规模化电动汽车有序充电控制策略研究[J].电测与仪表,2018,55(12):88-91,107.
[17]黄一诺,郭创新,王力成,等.考虑用户满意度的电动汽车分群调度策略[J].电力系统自动化,2015,39(17):183-191.
[18]孙波,王振兴,孙佳佳.电动汽车峰谷分时充放电价同步优化模型研究[J].电网与清洁能源,2017,33(2):130-136.