基于粒子群算法的微电网电动汽车接入经济-环境效益分析
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摘要
大规模的电动汽车合理有序充放电是降低电网负荷的峰谷差、解决能源危机和保障电能质量的一个重要手段.具有剩余电量的电动汽车有随机移动式储能特性,但在实践中电动汽车较少被考虑到微电网运行模式规划中.本文在以经济-环境最优为目标的微电网运行模式基础上构建模型,在算例中运用蒙特卡洛法模拟出大规模电动汽车充电行为符合正态分布,得到未来一天规模化EVs总体负荷曲线与微电网发电量;运用实现方便、收敛速度快的粒子群优化(Particle Swarm Optimization,POS)算法,以EVs的特征量(充电开始时刻、连接时长和充电电量)作为控制变量进行全局搜索得到最低系统成本和各分布式能源每小时最优出力,通过对比实验,验证了模型的有效性.结果表明,电动汽车的并入不仅能降低对环境的污染,还可以提升微电网运行的经济效益.
Reasonable and orderly charging and discharging of large-scale electric vehicles is an important means to reduce the peak-to-valley difference of power grid load,solve energy crisis and ensure power quality.Electric vehicles with remaining power have stochastic mobile energy storage characteristics;but in practice electric vehicles are less considered in the microgrid operating mode planning.This paper builds a model based on the microgrid operation mode with the economic-environment as the optimization.In the example,Monte Carlo simulation is used to simulate the large-scale electric vehicle charging behavior in accordance with the normal distribution,and the overall load curve of large-scale electric vehicles(EVs)in the future will be obtained.And for the microgrid power generation,using the particle swarm optimization(POS)algorithm with convenient implementation and fast convergence,the global search of the EVs feature quantity(charging start time,connection duration and charging power)as the control variable is the lowest.The systemcost and the optimal output per hour of distributed energy are verified by comparison experiments.It is concluded that the integration of EVs not only reduces environmental pollution,but also enhances the economic benefits of microgrid operation.
Reasonable and orderly charging and discharging of large-scale electric vehicles is an important means to reduce the peak-to-valley difference of power grid load,solve energy crisis and ensure power quality.Electric vehicles with remaining power have stochastic mobile energy storage characteristics;but in practice electric vehicles are less considered in the microgrid operating mode planning.This paper builds a model based on the microgrid operation mode with the economic-environment as the optimization.In the example,Monte Carlo simulation is used to simulate the large-scale electric vehicle charging behavior in accordance with the normal distribution,and the overall load curve of large-scale electric vehicles(EVs)in the future will be obtained.And for the microgrid power generation,using the particle swarm optimization(POS)algorithm with convenient implementation and fast convergence,the global search of the EVs feature quantity(charging start time,connection duration and charging power)as the control variable is the lowest.The systemcost and the optimal output per hour of distributed energy are verified by comparison experiments.It is concluded that the integration of EVs not only reduces environmental pollution,but also enhances the economic benefits of microgrid operation.
引文
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[2]苏小林,张艳娟,武中,等.规模化电动汽车充电负荷的预测及其对电网的影响[J].现代电力,2018,35(1):45-54.
[3]毛玉荣.电动汽车充放电与微电网运行的协调优化[D].长沙:湖南大学,2016.
[4]查理,马钧.电动汽车接入微电网模式研究[J].上海汽车,2014,21(3):7-9,14.
[5]邵艾博.可再生能源和电动汽车一体化管理对多模微电网稳定性的影响分析[D].武汉:华中科技大学,2015.
[6]杨新法,苏剑,吕志鹏,等.微电网技术综述[J].中国电机工程学报,2014,34(1):57-70.
[7]牟聿强,王秀丽,别朝红,等.风电场风速随机性及容量系数分析[J].电力系统保护与控制,2009,37(1):65-70.
[8]Farret F.Integration of Alternative Sources of Energy[M].John Wiley&Sons,Inc.2006.
[9]Aluisio B,Conserva A,Dicorato M,et al.Optimal operation planning of V2G-equipped Microgrid in the presence of EV aggregator[J].Electric Power Systems Research,2017,152:295-305.
[10]王璟,王利利,郭勇,等.计及电动汽车的微电网经济调度方法[J].电力系统保护与控制,2016,44(17):111-117.
[11]吉培荣,黄巍松,胡翔勇.电网负荷预测的无偏灰色预测模型[J].三峡大学学报(自然科学版),2001,23(1):59-62.
[12]李博彤,唐锴.计及电动汽车储能特性的微电网规划模型与算法[J].电力建设,2017,38(2):60-65.