基于Monte Carlo随机模拟算法的电动汽车无序充电负荷计算模型
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引用本文:马国真1, 王云佳1, 王竹梅2, 杜文通3.基于Monte Carlo随机模拟算法的电动汽车无序充电负荷计算模型[J].计算技术与自动化,2024,(2):192-197
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作者单位
马国真1, 王云佳1, 王竹梅2, 杜文通3 (1. 国网河北省电力有限公司 经济技术研究院,河北 石家庄 050000
2. 石家庄职业技术学院
,河北 石家庄 0500733. 北京中能广联科技有限公司,北京 100034) 
中文摘要:为了有效降低电动汽车无序充电负荷对于电力系统稳定性的影响,研究了基于Monte Carlo随机模拟算法的计算模型。综合考虑用户充电行为各参数的概率密度,使得构建的模型更精确。分析了不同的充电策略对于充电负荷曲线的影响,并利用综合策略模型使得用户的充电成本更低,利用基于 Levy飞行策略的改进麻雀算法对综合充电策略的权重系数进行寻优计算,以使得用户的成本和电网稳定均能获得不错的效果。在此基础上,提出利用双层优化模型对模型进一步优化,综合考虑用户满意度和电力波动的情况,结果表明改进后的模型,可以节省充电成本15.9%,降低电力系统负荷峰谷差约10.1%。
中文关键词:蒙特卡洛  电动汽车  无序充电  电力波动
 
Calculation Model of Disorderly Charging Load of Electric Vehicle Based on Monte Carlo Stochastic Simulation Algorithm
Abstract:In order to effectively reduce the impact of disorderly charging load of electric vehicle on power system stability, this paper studies the calculation model based on Monte Carlo random simulation algorithm, comprehensively considering the probability density of various parameters of user charging behavior, so as to make the model more accurate. The improved algorithm based on Levy’s charging strategy and the user’s comprehensive charging strategy can be used to optimize the charging effect of the power grid. On this basis, a two-level optimization model is proposed to further optimize the model, comprehensively considering the situation of user satisfaction and power fluctuation. The results show that the improved model can save 15.9% of charging cost and reduce the peak valley difference of power system load by about 10.1%.
keywords:Monte Carlo  electric vehicle  disorderly charging  power fluctuation
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