考虑电动汽车接入的区域配电网供用电区间预测技术

Interval Prediction Technology for Power Supply and Consumption of Regional Distribution Network Considering Electric Vehicle Access

随着新的服务和业务模式与配电网越来越紧密关联,将负载不确定性纳入预测计算中变得越来越重要。本文提出了一种有效的基于广义多项式混沌和随机测试的不确定性潮流分析方法,针对住宅负荷和电动汽车充电2种不同使用模型,研究了基于实际数据的区域配电网供用电区间预测问题,并给出了如何通过后处理计算来推导出影响服务质量的一些相关信息。利用一个典型的低压电网的基准情景对提出的方法进行测试,考虑到了居民负荷和电动汽车充电模式的变化,并将结果与通过蒙特卡洛方法进行的相同模拟进行对比分析,通过研究发现所提方法具有更快的计算速度,实现效果更好。分析过程中所做的考虑将有助于阐明该方法的应用,有助于理解负荷变化对电网特征量的影响,也有助于研究负载变化和电荷分布的组合作用对配电网优化方面的改善意义。

As new services and business models become more closely linked to the distribution network,it becomes increasingly important to incorporate load uncertainty into forecasting calculations.This paper describes an effective method which is based on generalized polynomial chaos and random test methods for uncertain power flow analysis.It describes how to implement the method under two different usage models(residential load and electric vehicle charging)to solve the interval prediction problem about the regional power distribution network supply and demand based on The actual data,and proposes how to use post-processing calculations to derive some relevant information affecting service quality.This paper uses a typical European low-voltage grid benchmark scenario to test the proposed method,taking changes in residential load and electric vehicle charging mode into account,and comparing the results with the same simulations performed by Monte Carlo method,illustrating the method proposed in this paper has faster calculation speed and better implementation effect..The considerations made in the analysis of this paper will help clarify the application of this method,help understand the impact of load changes on the characteristics of the power grid,and help study the combined effect of load changes and charge distributions on the optimization of the distribution network.