计及电动汽车充电站接入的配电网网架规划优化研究
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摘要
电动汽车充电站大规模的接入电网,将会对当地配电网造成显著影响。因此,对配电网进行科学合理的规划应当充分考虑电动汽车充电站的接入问题。首先,考虑电动汽车充电站的选址和规模,从成本最小化的角度出发,建立配电网网架规划的目标函数。其中成本最小化要计及配电网投资成本、充电站投资和运营成本及功率损耗成本。其次,提出了一种新的量子极限学习果蝇优化算法(QEFOA),以提高果蝇算法(FOA)的优化能力。最后,通过算例分析验证所提出的配电网规划方法以及QEFOA的有效性。结果表明,所提出的配电网规划方法能够有效降低规划成本;同时与FOA等传统算法相比,QEFOA的收敛速度更快,搜索能力更强。
The large-scale access of electric vehicle charging stations will have a significant impact on the local distribution network.Therefore,scie ntific and reasonable planning of distribution network should fully consider the access of electric vehicle charging station.First of all,considering the siting and sizing of electric vehicle charging station,the objective function of distri bution network planning is established from the view of cost minimization.The cost minimization should consider the distribution network investment cost,charging station investment and operation cost and power loss cost.Seco ndly,a new quantum limit learning algorithm for fruit fly optimization(QEFOA)is proposed to improve the optimization ability of the fruit fly algorithm(FOA).Finally,two case studies are conducted to verify the effectiveness of the proposed distribution network planning method and QEFOA.Case study shows that the proposed distribution network planning method can effectively reduce the planning cost.And compared with FOA and other traditional algorithms,QEFO A has faster convergence speed and stronger search ability.
The large-scale access of electric vehicle charging stations will have a significant impact on the local distribution network.Therefore,scie ntific and reasonable planning of distribution network should fully consider the access of electric vehicle charging station.First of all,considering the siting and sizing of electric vehicle charging station,the objective function of distri bution network planning is established from the view of cost minimization.The cost minimization should consider the distribution network investment cost,charging station investment and operation cost and power loss cost.Seco ndly,a new quantum limit learning algorithm for fruit fly optimization(QEFOA)is proposed to improve the optimization ability of the fruit fly algorithm(FOA).Finally,two case studies are conducted to verify the effectiveness of the proposed distribution network planning method and QEFOA.Case study shows that the proposed distribution network planning method can effectively reduce the planning cost.And compared with FOA and other traditional algorithms,QEFO A has faster convergence speed and stronger search ability.
引文
[1]刘卓然,陈健,林凯,等.国内外电动汽车发展现状与趋势[J].电力建设,2015.36(7):25-32.LIU Zhuoran,CHEN Jian,LIN Kai,et al.Domestic and foreign present situationand the tendency of electric vehicles[J].Electric Power Construction,2015,36(7):25-32.
[2]连恒辉,万凌云,刘洪,等.电动汽车充放电对配电网规划的影响[J].电力建设,2015,36(7):33-39.LIAN Henghui,WAN Lingyun,LIU Hong,et al.The impact of electric vehicle charging and discharging on distribution network planning[J].Electric Power Construction,2015,36(7):33-39.
[3]化晨冰,黄振华,张刚.基于改进遗传算法的配电网网架结构优化规划[J].山东电力技术,2015,42(3):16-18.HUA Chenbing,HUANG Zhenhua,ZHANG Gang.Distribution network structure optimization planning based on improved genetic algorithm[J].Shandong Electric Power Technology,2015,42(3):16-18.
[4]李思,宋珺,沙立成.基于风险度评价和改进蚁群算法的配电网网架规划[J].中国电力,2009,42(11):52-56.LI Si,SONG Qiqi,SHA Licheng.Distribution network planning based on risk assessment and improved ant colony algorithm[J].China Electric Power,2009,42(11):52-56.
[5]苏海锋,张建华,梁志瑞,等.基于LCC和改进粒子群算法的配电网多阶段网架规划优化[J].中国电机工程学报,2013,33(4):118-125+16.SU Haifeng,ZHANG Jianhua,LIANG Zhirui,et al.Multi-stage grid planning optimization of distribution network based on LCC and improved particle swarm optimization[J].China Journal of Electrical Engineering,2013,33(4):118-125+16.
[6]NEJADFARD J S,RASHIDINEJAD M,ABDOLLAHI A.Multistage distribution network expansion planning under smart grids environment[J].International Journal of Electrical Power&Energy Systems,2015:71:222-230.
[7]SUN W,Ma T N.The power distribution network structure optimization based on improved ant colony algorithm[J].Journal of Intelligent and Fuzzy Systems,2014:26(6):2799-2804.
[8]ABBASI A R,SEIFI A R.Considering cost and reliability in electrical and thermal distribution networks reinforcement planning[J].Energy,2015:84:25-35.
[9]AGHAEI J,MUTTAQI K M,AZIZIVAHED A,et al.Distribution expansion planning considering reliability and security of energy using modified PSO(Particle Swarm Optimization)algorithm[J].Energy,2014:65:398-41 1.
[10]凡鹏飞,张粒子,熊浩清,等.基于改进BCC算法的含微电网的配电网网架规划[J].电力系统保护与控制,2012,40(10):12-18.FAN Pengfei,ZHANG Lizi,XIONG Haoqing,et al.Distribution network planning with microgrid based on improved BCC algorithm[J].Power System Protection and Control,2012,40(10):12-18.
[11]卢志刚,刘健,吴杰,等.人工鱼群算法在配电网网架规划中的应用[J].高电压技术,2008,34(3):565-568+602.LU Zhigang,LIU Jian,WU Jie,et al.Application of artificial fish swarm algorithms in distribution network planning[J].High Voltage Technology,2008,34(3):565-568+602.
[12]LIU Z,WEN F,LEDWICH G.Optimal planning of electric-vehicle charging stations in distribution systems[J].IEEE Transactions on Power Delivery,2013:28(1):102-110.
[13]LI Y,LI L,YONG J,et al.Layout planning of electrical vehicle charging stations based on genetic algorithm[M].Heidelberg:Springer,201 1.
[14]XU H,MI AO S,ZHANG C,et al.Optimal placement of charging infrastructures for large-scale integration of pure electric vehicles into grid[J].International Journal of Electrical Power&Energy Systems,2013:53:159-165.
[15]王汉华,陈永进.电动汽车充电设施接入配电网的最优布点规划[J].广东电力,2018,31(4):72-78.WANG Hanhua,CHEN Yongjin.Optimal stationing planning for electric vehicle charging facilities accessing to distribution network[J].Guangdong Electric Power,2018,31(4):72-78
[16]GE S,FENG L,LIU H.The planning of electric vehicle charging station based on grid partition method[C].Yichang:2011 International Conference on Electrical and Control Engineering(ICECE),IEEE,201 1:2726-2730.
[17]王林富,邱方驰,张斌,等.基于分布式电源的配电网多目标优化策略研究[J].智慧电力,2019,47(1):47-53,65.WANG Linfu,QIU Fangchi,ZHANG Bin,et al.Research on multi-objective optimal strategy for distribution network based on distributed generation[J].Smart Power,2019,47(1):47-53,65..
[18]吴翠玉,张美霞,陈海燕.电动汽车充电站规划研究[J].智慧电力,2016,44(11):31-37.WU Cuiyu,ZHANG Meixia,CHEN Haiyan.Electric vehicle charging station planning research[J].Smart Power,2016,44(11):31-37.
[19]万晓凤,郗瑞霞,胡海林,等.基于果蝇算法的电网不平衡时并网逆变器多目标优化控制研究[J].电网技术,2018,42(5):1628-1635.WAN Xiaofeng,XI Ruixia,HU Hailin,et al.Study on multi-objective optimal control of grid-connected inverters under unbalanced grid based on Drosophila algorithm[J].Power Grid Technology,2018,42(5):1628-1635.
[20]李俄收,吴文民.电动汽车蓄电池充电对电力系统的影响及对策[J].华东电力,2010,38(1):109-113.LI Eshou,WU Wenmin.Impact of battery charging on electric vehicle power system and countermeasures[J].East China Electric Power,2010,38(1):109-1 13.
[21]陈婷,卫志农,吴霜,等.考虑电动汽车充电站选址定容的配电网规划[J].电力系统及其自动化学报,2013,25(3):1-7.CHEN Ting,WEI Zhinong,WU Shuang,et al.Distribution network planning considering the location and capacity of charging stations for electric vehicles[J].Journal of Power Systems and Automation,2013,25(3):1-7.
[2]连恒辉,万凌云,刘洪,等.电动汽车充放电对配电网规划的影响[J].电力建设,2015,36(7):33-39.LIAN Henghui,WAN Lingyun,LIU Hong,et al.The impact of electric vehicle charging and discharging on distribution network planning[J].Electric Power Construction,2015,36(7):33-39.
[3]化晨冰,黄振华,张刚.基于改进遗传算法的配电网网架结构优化规划[J].山东电力技术,2015,42(3):16-18.HUA Chenbing,HUANG Zhenhua,ZHANG Gang.Distribution network structure optimization planning based on improved genetic algorithm[J].Shandong Electric Power Technology,2015,42(3):16-18.
[4]李思,宋珺,沙立成.基于风险度评价和改进蚁群算法的配电网网架规划[J].中国电力,2009,42(11):52-56.LI Si,SONG Qiqi,SHA Licheng.Distribution network planning based on risk assessment and improved ant colony algorithm[J].China Electric Power,2009,42(11):52-56.
[5]苏海锋,张建华,梁志瑞,等.基于LCC和改进粒子群算法的配电网多阶段网架规划优化[J].中国电机工程学报,2013,33(4):118-125+16.SU Haifeng,ZHANG Jianhua,LIANG Zhirui,et al.Multi-stage grid planning optimization of distribution network based on LCC and improved particle swarm optimization[J].China Journal of Electrical Engineering,2013,33(4):118-125+16.
[6]NEJADFARD J S,RASHIDINEJAD M,ABDOLLAHI A.Multistage distribution network expansion planning under smart grids environment[J].International Journal of Electrical Power&Energy Systems,2015:71:222-230.
[7]SUN W,Ma T N.The power distribution network structure optimization based on improved ant colony algorithm[J].Journal of Intelligent and Fuzzy Systems,2014:26(6):2799-2804.
[8]ABBASI A R,SEIFI A R.Considering cost and reliability in electrical and thermal distribution networks reinforcement planning[J].Energy,2015:84:25-35.
[9]AGHAEI J,MUTTAQI K M,AZIZIVAHED A,et al.Distribution expansion planning considering reliability and security of energy using modified PSO(Particle Swarm Optimization)algorithm[J].Energy,2014:65:398-41 1.
[10]凡鹏飞,张粒子,熊浩清,等.基于改进BCC算法的含微电网的配电网网架规划[J].电力系统保护与控制,2012,40(10):12-18.FAN Pengfei,ZHANG Lizi,XIONG Haoqing,et al.Distribution network planning with microgrid based on improved BCC algorithm[J].Power System Protection and Control,2012,40(10):12-18.
[11]卢志刚,刘健,吴杰,等.人工鱼群算法在配电网网架规划中的应用[J].高电压技术,2008,34(3):565-568+602.LU Zhigang,LIU Jian,WU Jie,et al.Application of artificial fish swarm algorithms in distribution network planning[J].High Voltage Technology,2008,34(3):565-568+602.
[12]LIU Z,WEN F,LEDWICH G.Optimal planning of electric-vehicle charging stations in distribution systems[J].IEEE Transactions on Power Delivery,2013:28(1):102-110.
[13]LI Y,LI L,YONG J,et al.Layout planning of electrical vehicle charging stations based on genetic algorithm[M].Heidelberg:Springer,201 1.
[14]XU H,MI AO S,ZHANG C,et al.Optimal placement of charging infrastructures for large-scale integration of pure electric vehicles into grid[J].International Journal of Electrical Power&Energy Systems,2013:53:159-165.
[15]王汉华,陈永进.电动汽车充电设施接入配电网的最优布点规划[J].广东电力,2018,31(4):72-78.WANG Hanhua,CHEN Yongjin.Optimal stationing planning for electric vehicle charging facilities accessing to distribution network[J].Guangdong Electric Power,2018,31(4):72-78
[16]GE S,FENG L,LIU H.The planning of electric vehicle charging station based on grid partition method[C].Yichang:2011 International Conference on Electrical and Control Engineering(ICECE),IEEE,201 1:2726-2730.
[17]王林富,邱方驰,张斌,等.基于分布式电源的配电网多目标优化策略研究[J].智慧电力,2019,47(1):47-53,65.WANG Linfu,QIU Fangchi,ZHANG Bin,et al.Research on multi-objective optimal strategy for distribution network based on distributed generation[J].Smart Power,2019,47(1):47-53,65..
[18]吴翠玉,张美霞,陈海燕.电动汽车充电站规划研究[J].智慧电力,2016,44(11):31-37.WU Cuiyu,ZHANG Meixia,CHEN Haiyan.Electric vehicle charging station planning research[J].Smart Power,2016,44(11):31-37.
[19]万晓凤,郗瑞霞,胡海林,等.基于果蝇算法的电网不平衡时并网逆变器多目标优化控制研究[J].电网技术,2018,42(5):1628-1635.WAN Xiaofeng,XI Ruixia,HU Hailin,et al.Study on multi-objective optimal control of grid-connected inverters under unbalanced grid based on Drosophila algorithm[J].Power Grid Technology,2018,42(5):1628-1635.
[20]李俄收,吴文民.电动汽车蓄电池充电对电力系统的影响及对策[J].华东电力,2010,38(1):109-113.LI Eshou,WU Wenmin.Impact of battery charging on electric vehicle power system and countermeasures[J].East China Electric Power,2010,38(1):109-1 13.
[21]陈婷,卫志农,吴霜,等.考虑电动汽车充电站选址定容的配电网规划[J].电力系统及其自动化学报,2013,25(3):1-7.CHEN Ting,WEI Zhinong,WU Shuang,et al.Distribution network planning considering the location and capacity of charging stations for electric vehicles[J].Journal of Power Systems and Automation,2013,25(3):1-7.