摘要
随着电动汽车的规模化应用,电力系统正面临着经济及环境的双重考验,为了应对新的挑战,本文提出了一种V2G模式下考虑用户满意度的动态经济/排放调度模型。首先利用蒙特卡洛随机抽样方法分析了大规模EV无序充电对电网负荷的影响;其次,为了兼顾电网与用户双侧利益,在经济调度各时段内,以EV的充放电功率以及火电机组的出力作为决策变量,以负荷峰谷差、总的燃料费用以及污染物排放作为目标函数,充分考虑电力系统约束、EV约束以及用户满意度约束,动态优化电力系统经济性、环境效益和EV的充放电功率。考虑到该模型的多约束复杂性,本文采用双层优化调度策略,并分别利用粒子群优化算法以及多目标粒子群优化算法对模型进行求解。以修改的IEEE 6机30节点系统为例进行仿真分析,本文提出模型的合理性得到了有效验证。
With the large-scale application of electric vehicles,the power system is facing the dual test of economy and environment.In order to cope with the new challenges,this paper proposes a dynamic economic/emissions dispatch model that considers user satisfaction under the V2 G mode.First,the Monte Carlo random sampling method is used to analyze the impact of large-scale EV disorder charging on the grid load;second,in order to take into account the interests of both the power grid and the user,the charging and discharging power of the EV and the power of the thermal power unit are used in each period of economic dispatch.Taking load peak-to-valley difference,total fuel cost and pollutant emissions as objective functions,fully considering power system constraints,EV constraints and user satisfaction constraints,power system economy,environmental benefits and EV charging and discharging power are dynamically optimized.Considering the multi-constraint complexity of the model,this paper adopts a two-layer optimization scheduling strategy,and uses particle swarm optimization algorithm and multi-objective particle swarm optimization algorithm to solve the model respectively.Taking the modified IEEE 6-machine 30-node system as an example for simulation analysis,the rationality of the model proposed in this paper has been effectively verified.
作者
吴佳欣
郝正航
WU Jiaxin;HAO Zhenghang(College of Electrical Engineering,Guizhou University,Guiyang 550025,China)
出处
《智能计算机与应用》
2022年第6期88-96,共9页
Intelligent Computer and Applications
基金
贵州省科技计划项目([2018]5615)
第二批国家级新工科研究与实践项目(E-NYDQHGC20202227)
