非全测量信息的配电网概率潮流算法研究

Probabilistic Load Flow Arithmetic with Incomplete Measuring Data in Distribution Systems

确定性潮流计算在反映配电网运行时的波动情况时存在着缺陷,引入了概率潮流计算理论进行配电网潮流分析。目前我国配电网自动化程度不高,量测装置配置不足,导致概率潮流计算时能获得的负荷数据严重不足。针对确定性潮流计算不能对整个配电网做出较为准确和全面的评判以及配电网中测量数据不足问题提出了一种基于伪测量数据获取的非全测量信息配电网概率潮流算法,该算法利用配电网中有限的实测量数据,采用某种负荷分配算法来估算伪测量数据;并基于各个节点负荷相互独立,负荷功率分布呈正态分布的假设,根据辐射型配电网的特点,提出了适合辐射型配电网的线性化概率潮流算法,得到了配网各节点电压的概率特性。最后通过计算实例验证了算法的有效性与正确性。

Because there is limitation in calculating load flow by using determinate method, this paper introduce probabilistic load flow （PLF） to analyze distribution system. At present, the distribution system＇s automatization is behind the times. So, in power distribution system, the availability of measuring data is limited, there are many pseudo measured data in calculating load flow in distribution system. In this paper, an appropriate method is presented to estimate circuit nodes＇ load demand base on the historical data acquired by the feeder terminal units （FTU） in distribution automation system （DAS）. It is assumed that the load in every node is independent each other and the loads are all distributed in normal. Some practical approximations are introduced to modify the general probabilistic load flow methodology, which is used primarily in the composite systems, for analysis of distribution systems. The distribution systems＇ radial operating structure is also utilized. These have resulted in significant simplification of the general methodology. Results of these methods are provided on an actual distribution circuit illustrating its feasibility.