含电动汽车的智能配电网优化调度研究综述
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摘要
常规的经济调度已不能满足可再生新能源和电动汽车随机接入所带来的挑战。为了解决接入配电网电动汽车数量逐渐增多和分布式电源并网问题。本文对含电动汽车的智能配电网优化调度进行了详细的分析。首先简要分析了电动汽车接入对电网造成的影响。其次本文从电动汽车接入电网的类型、电动汽车参与优化调度的目标、优化调度模型以及优化调度建模方法四个研究方面详细分析了电动汽车与智能配电网协调优化调度。从优化调度的结果分析可知,把电动汽车考虑进智能配电网的优化调度中能够有效的降低配电网的运行成本,使得车主的充电费用减少,并且提高了分布式电源的利用率。然后对大数据技术在智能配电网优化中的应用进行了简要的介绍。最后对电动汽车与智能配电网协调优化调度提出了展望。
Conventional economic dispatching has been unable to meet the challenges of random access to renewable new energy and electric vehicles. In order to solve the problem of increasing the number of electric vehicles connected to the distribution network and the problem of grid connection of distributed power sources. In this paper,a detailed analysis of the smart dispatching network with electric vehicles is carried out. Firstly,the impact of electric vehicle access on the power grid is briefly analyzed. Secondly,this paper analyzes in detail the coordinated optimization and dispatching of electric vehicles and smart distribution networks from four aspects,such as the types of electric vehicles connected to the grid,the goals of electric vehicles participating in optimal scheduling,the optimization scheduling model and the optimization scheduling modeling methods. From the analysis of the results of the optimized scheduling,it can be seen that considering the electric vehicle into the optimal dispatching of the intelligent distribution network can effectively reduce the operating cost of the distribution network,reduce the charging cost of the vehicle owner,and improve the utilization rate of the distributed power source. Then it briefly introduces the application of big data technology in intelligent distribution network optimization. Finally,the prospect of coordinated optimization and scheduling of electric vehicles and smart distribution networks is put forward.
Conventional economic dispatching has been unable to meet the challenges of random access to renewable new energy and electric vehicles. In order to solve the problem of increasing the number of electric vehicles connected to the distribution network and the problem of grid connection of distributed power sources. In this paper,a detailed analysis of the smart dispatching network with electric vehicles is carried out. Firstly,the impact of electric vehicle access on the power grid is briefly analyzed. Secondly,this paper analyzes in detail the coordinated optimization and dispatching of electric vehicles and smart distribution networks from four aspects,such as the types of electric vehicles connected to the grid,the goals of electric vehicles participating in optimal scheduling,the optimization scheduling model and the optimization scheduling modeling methods. From the analysis of the results of the optimized scheduling,it can be seen that considering the electric vehicle into the optimal dispatching of the intelligent distribution network can effectively reduce the operating cost of the distribution network,reduce the charging cost of the vehicle owner,and improve the utilization rate of the distributed power source. Then it briefly introduces the application of big data technology in intelligent distribution network optimization. Finally,the prospect of coordinated optimization and scheduling of electric vehicles and smart distribution networks is put forward.
引文
[1]钟臻,张楷旋,吴贞龙,等.基于改进的LDW粒子群算法的风-火电力系统联合优化调度策略[J].电力大数据,2017,20(10):50-55.ZHONG Zhen,ZHANG Kaixuan,WU Zhenlong,et al.Combined optimization dispatch strategy of wind-thermal power system based on improved LDW particle swarm algorithm[J].Power Systems and Big Data,2017,20(10):50-55.
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[8]赵琦玮,王昕,王鑫,等.含不同集群电动汽车的微电网优化调度[J].可再生能源,2019,37(03):379-385.ZHAO Qiwei,WANG Xin,WANG Xin,et al.Microgrid optimization dispatching with different clusters of electric vehicles[J].Renewable Energy Resources,2019,37(03):379-385.
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[11]A NISAR,M THOMAS.Comprehensive control for microgrid autonomous operation with demand response[J].IEEETransactions on Smart Grid,2017,8(05):2081-2089.
[12]王凌云,汪德夫,马奇伟,等.源、网、荷三方利益最优的电动汽车充放电双层优化调度[J].可再生能源,2018,36(05):713-718.WANG Lingyun,WANG Defu,Ma Qiwei,et al.Double level optimal scheduling of electric vehicle charging and dis-charging with the best benefit of power plant,network and load[J].Renewable Energy Resources,2018,36(05):713-718.
[13]A DUTTA,S DEBBARMA.Frequency regulation in deregulated market using vehicle-to-grid services in residential distribution network[J].IEEE Systems Journal,2018,12(03);2812-2820.
[14]K JANFESHAN,M MASOUM.Hierarchical supervisory control system for PEVs participating in frequency regulation of smart grids[J].IEEE Power and Energy Technology Systems Journal,2017,4(04):84-93.
[15]李宏玉,佘超,张廷军,等.基于SOC的电动汽车参与电网调频控制策略研究[J].重庆大学学报,2018,41(12):66-72.LI Hongyu,SHE Chao,ZGANG Tingjun,et al.Research on the strategy of electric vehicles participating in power system frequency control based on SOC[J].Journal of Chongqing University,2018,41(12):66-72.
[16]张涛,张东方,王凌云,等.计及电动汽车充电模式的主动配电网多目标优化重构[J].电力系统保护与控制,2018,46(08):1-9.ZHANG Tao,ZHANG Dongfang,WANG Lingyun,et al.Multiobjective optimization of active distribution network reconfiguration considering electric vehicle charging mode[J].Power System Protection and Control,2018,46(08):1-9.
[17]师景佳,袁铁江,Saeed Ahmed Khan,等.计及电动汽车可调度能力的风/车协同参与机组组合策略[J].高电压技术,2018,44(10):3433-3440.SHI Jingjia,YUAN Tiejiang,Saeed Ahmed Khan,et al.Unit commitment strategy considering cooperated dispatch of electric vehicles based on scheduling capacity and wind power generation[J].High Voltage Engineering,2018,44(10):3433-3440.
[18]葛晓琳,裴晨皓.考虑电动汽车随机特性的机组组合问题研究[J].电力自动化设备,2018,38(09):77-84.GE Xiaolin,PEI Chenhao.Study on unit commitment problem considering stochastic characteristics of electric vehicles[J].Electric Power Automation Equipment,2018,38(09):77-84.
[19]赵强,刘海勇,汪晋宽,等.计及风电和电动汽车的安全约束机组组合模型[J].华南理工大学学报(自然科学版),2017,45(10):78-86.ZHAO Qiang,LIU Haiyong,WANG Jinkuan,et al.Securityconstrained unit commitment model with wind power and electric vehicles[J].Journal of South China University of Technology(Natural Science Edition),2017,45(10):78-86.
[20]张晓花,谢俊,赵晋泉,等.考虑风电和电动汽车等不确定性负荷的电力系统节能减排调度[J].高电压技术,2015,41(07):2408-2414.ZHANG Xiaohua,XIE Jun,ZHAO Jinquan,et al.Energy-saving emission-reduction dispatching of electrical power system considering uncertainty of Load with wind power and plug-in hybrid electric vehicles[J].High Voltage Engineering,2015,41(07):2408-2414.
[21]K ROGERS,R KLUMP,H KHURANA,et al.An authenticated control framework for distributed voltage support on the smart grid[J].IEEE Transactions on Smart Grid,2010,1(01):40-47.
[22]孙丛丛,王致杰,江秀臣,等.分时电价环境下计及电动汽车充放电影响的微电网优化控制策略[J].可再生能源,2018,36(01):64-71.SUN Congcong,WANg Zhijie,JIANG Xiuchen,et al.Optimal control strategy for micro grid considering charging/discharging of electric vehicles under time-of-use tariffs[J].Renewable Energy Resources,2018,36(01):64-71.
[23]张明光,周灿.含电动汽车的微网的智能优化调度[J].电网与清洁能源,2016,32(12):100-105+113.ZHANG Mingguang,ZHOU Can.Intelligent optimal dispatch for the micro-grid containing plug-in electric vehicles[J].Power System and Clean Energy,2016,32(12):100-105+113.
[24]程杉,王贤宁,冯毅煁.电动汽车充电站有序充电调度的分散式优化[J].电力系统自动化,2018,42(01):39-46.CHENG Shan,WANG Xianning,FENG Yichen.Decentralized optimization of ordered charging scheduling in electric vehicle charging station[J].Automation of Electric Power Systems,2018,42(01):39-46.
[25]孙伟卿,叶磊,涂轶昀.基于GAMS的电力系统有功-无功综合优化[J].系统仿真学报,2018,30(08):3082-3091.SUN Weiqing,YE Lei,TU Yiyun.GAMS-based active power optimization with reactive power compensation[J].Journal of System Simulation,2018,30(08):3082-3091.
[26]朱鹰屏,张绪红,韩新莹.用于配电网网损优化的电动汽车智能充电调度[J].广东电力,2016,29(09):94-97+103.ZHU Yingping,ZHANG Xuhong,HAN Xinying.Intelligent charging scheduling for electric vehicle for optimization on network loss of power distribution network[J].Guangdong Electric Power,2016,29(09):94-97+103.
[27]王超,麻秀范.基于电动汽车用户电价响应的充电负荷优化模型建立[J].内蒙古电力技术,2017,35(01):1-7.WANG Chao,MA Xiufan.Charging load optimization model based on electric vehicle users’price response[J].Inner Mongolia Electric Power,2017,35(01):1-7.
[2]张沛,吴潇雨,和敬涵.大数据技术在主动配电网中的应用综述[J].电力建设,2015,36(01):52-59.ZHANG Pei,WU Xiaoyu,HE Jinghan.Review on big data technology applied in active distribution network[J].Electric Power Construction,2015,36(01):52-59.
[3]吴红斌,侯小凡,赵波,等.计及可入网电动汽车的微网系统经济调度[J].电力系统自动化,2014,38(09):77-84+99.WU Hongbin,HOU Xiaofan,ZHAO Bo,et al.Economical dispatch of microgrid considering plug-in electric vehicles[J].Automation of Electric Power Systems,2014,38(09):77-84+99.
[4]吕耀棠,管霖,赵琦,等.充电式电动汽车停车场的V2G模型及接入配电网方案优化研究[J].电力自动化设备,2018,38(11):1-7+14.LV Yaotang,GUAN Lin,ZHAO Qi,et al.Research on V2G model of EPVV and its optimal scheme accessing to distribution network[J].Electric Power Automation Equipment,2018,38(11):1-7+14.
[5]F BACCINO,S GRILLO,S MASSUCCO,et al.A two-stage marginbased algorithm for optimal plug-in electric vehicles scheduling[J].IEEE Transactions on Smart Grid,2015,6(02):759-766.
[6]LOPES P,SOARES J,ALMEIDA R.Integration of electric vehicles in the electric power system[J].Proceedings of the IEEE,2011,99(01):168-183.
[7]周天沛,孙伟.基于微网的电动汽车与电网互动技术[J].电力系统自动化,2018,42(03):98-104+117.ZHOU Tianpei,SUN Wei.Electric vehicle-to-grid technology based on microgrid[J].Automation of Electric Power Systems,2018,42(03):98-104+117.
[8]赵琦玮,王昕,王鑫,等.含不同集群电动汽车的微电网优化调度[J].可再生能源,2019,37(03):379-385.ZHAO Qiwei,WANG Xin,WANG Xin,et al.Microgrid optimization dispatching with different clusters of electric vehicles[J].Renewable Energy Resources,2019,37(03):379-385.
[9]M A MASRUR,A G SKOWRONSKA,JANIE HANCOCK,et al.Military-based vehicle-to-grid and vehicle-to-vehicle microgrid system architecture and implementation[J].IEEETransactions on Transportation Electrification,2018,4(01):157-171.
[10]H KO,S PACK,V LEUNG.Mobility-aware vehicle-to-grid control algorithm in microgrids[J].IEEE Transactions on Intelligent Transportation Systems,2018,19(07):2165-2174.
[11]A NISAR,M THOMAS.Comprehensive control for microgrid autonomous operation with demand response[J].IEEETransactions on Smart Grid,2017,8(05):2081-2089.
[12]王凌云,汪德夫,马奇伟,等.源、网、荷三方利益最优的电动汽车充放电双层优化调度[J].可再生能源,2018,36(05):713-718.WANG Lingyun,WANG Defu,Ma Qiwei,et al.Double level optimal scheduling of electric vehicle charging and dis-charging with the best benefit of power plant,network and load[J].Renewable Energy Resources,2018,36(05):713-718.
[13]A DUTTA,S DEBBARMA.Frequency regulation in deregulated market using vehicle-to-grid services in residential distribution network[J].IEEE Systems Journal,2018,12(03);2812-2820.
[14]K JANFESHAN,M MASOUM.Hierarchical supervisory control system for PEVs participating in frequency regulation of smart grids[J].IEEE Power and Energy Technology Systems Journal,2017,4(04):84-93.
[15]李宏玉,佘超,张廷军,等.基于SOC的电动汽车参与电网调频控制策略研究[J].重庆大学学报,2018,41(12):66-72.LI Hongyu,SHE Chao,ZGANG Tingjun,et al.Research on the strategy of electric vehicles participating in power system frequency control based on SOC[J].Journal of Chongqing University,2018,41(12):66-72.
[16]张涛,张东方,王凌云,等.计及电动汽车充电模式的主动配电网多目标优化重构[J].电力系统保护与控制,2018,46(08):1-9.ZHANG Tao,ZHANG Dongfang,WANG Lingyun,et al.Multiobjective optimization of active distribution network reconfiguration considering electric vehicle charging mode[J].Power System Protection and Control,2018,46(08):1-9.
[17]师景佳,袁铁江,Saeed Ahmed Khan,等.计及电动汽车可调度能力的风/车协同参与机组组合策略[J].高电压技术,2018,44(10):3433-3440.SHI Jingjia,YUAN Tiejiang,Saeed Ahmed Khan,et al.Unit commitment strategy considering cooperated dispatch of electric vehicles based on scheduling capacity and wind power generation[J].High Voltage Engineering,2018,44(10):3433-3440.
[18]葛晓琳,裴晨皓.考虑电动汽车随机特性的机组组合问题研究[J].电力自动化设备,2018,38(09):77-84.GE Xiaolin,PEI Chenhao.Study on unit commitment problem considering stochastic characteristics of electric vehicles[J].Electric Power Automation Equipment,2018,38(09):77-84.
[19]赵强,刘海勇,汪晋宽,等.计及风电和电动汽车的安全约束机组组合模型[J].华南理工大学学报(自然科学版),2017,45(10):78-86.ZHAO Qiang,LIU Haiyong,WANG Jinkuan,et al.Securityconstrained unit commitment model with wind power and electric vehicles[J].Journal of South China University of Technology(Natural Science Edition),2017,45(10):78-86.
[20]张晓花,谢俊,赵晋泉,等.考虑风电和电动汽车等不确定性负荷的电力系统节能减排调度[J].高电压技术,2015,41(07):2408-2414.ZHANG Xiaohua,XIE Jun,ZHAO Jinquan,et al.Energy-saving emission-reduction dispatching of electrical power system considering uncertainty of Load with wind power and plug-in hybrid electric vehicles[J].High Voltage Engineering,2015,41(07):2408-2414.
[21]K ROGERS,R KLUMP,H KHURANA,et al.An authenticated control framework for distributed voltage support on the smart grid[J].IEEE Transactions on Smart Grid,2010,1(01):40-47.
[22]孙丛丛,王致杰,江秀臣,等.分时电价环境下计及电动汽车充放电影响的微电网优化控制策略[J].可再生能源,2018,36(01):64-71.SUN Congcong,WANg Zhijie,JIANG Xiuchen,et al.Optimal control strategy for micro grid considering charging/discharging of electric vehicles under time-of-use tariffs[J].Renewable Energy Resources,2018,36(01):64-71.
[23]张明光,周灿.含电动汽车的微网的智能优化调度[J].电网与清洁能源,2016,32(12):100-105+113.ZHANG Mingguang,ZHOU Can.Intelligent optimal dispatch for the micro-grid containing plug-in electric vehicles[J].Power System and Clean Energy,2016,32(12):100-105+113.
[24]程杉,王贤宁,冯毅煁.电动汽车充电站有序充电调度的分散式优化[J].电力系统自动化,2018,42(01):39-46.CHENG Shan,WANG Xianning,FENG Yichen.Decentralized optimization of ordered charging scheduling in electric vehicle charging station[J].Automation of Electric Power Systems,2018,42(01):39-46.
[25]孙伟卿,叶磊,涂轶昀.基于GAMS的电力系统有功-无功综合优化[J].系统仿真学报,2018,30(08):3082-3091.SUN Weiqing,YE Lei,TU Yiyun.GAMS-based active power optimization with reactive power compensation[J].Journal of System Simulation,2018,30(08):3082-3091.
[26]朱鹰屏,张绪红,韩新莹.用于配电网网损优化的电动汽车智能充电调度[J].广东电力,2016,29(09):94-97+103.ZHU Yingping,ZHANG Xuhong,HAN Xinying.Intelligent charging scheduling for electric vehicle for optimization on network loss of power distribution network[J].Guangdong Electric Power,2016,29(09):94-97+103.
[27]王超,麻秀范.基于电动汽车用户电价响应的充电负荷优化模型建立[J].内蒙古电力技术,2017,35(01):1-7.WANG Chao,MA Xiufan.Charging load optimization model based on electric vehicle users’price response[J].Inner Mongolia Electric Power,2017,35(01):1-7.
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