摘要
针对配电网首端量测准确度较高,而其余位置量测冗余度较低甚至没有量测量的特点,提出一种新的配电网DMS系统架构和适用于智能配电网的状态估计方法,利用准实时数据构造目标函数,依据历史记录设置不等式约束。与传统配电网方法不同,该方法可用于准实时量测在线率较低的配电网。因其是最优潮流意义下的状态估计,可以利用内点法求解。采用某市9节点配电网线路作为算例进行仿真,并对结果进行了详细讨论,同时以广泛使用的33节点配电网算例进一步验证。结果表明,所提方法计算速度快、收敛性好,可以实现智能配电网在线状态估计。该方法对于准实时量测在线率低的配电线路也有理想的估计效果,能较好地获得真实值,对线路电流的估计结果满足智能配电网高级应用的需求。
A novel distribution management system（ DMS） architecture combined with the data mining technology and the relevant state estimation for smart distribution networks is introduced due to the fact that the measurement in the root node is highly accurate while the measurement redundancies of the rest nodes are low,some of which even have no measurements. The method proposed in this paper takes use of the quasi real-time measurements to form the objective function. The historical load curves are adopted as the inequality constraints. Unlike the traditional distribution state estimation,the proposed method is suitable for the distribution network with few on-line quasi real-time measurements. This method is a kind of state estimation whose structure is similar to the optimal power flow. So it can be solved with the interior point method. The case study is carried out with a real 9-node distribution network and the results are discussed in detail. At the same time,a widely used 33-node distribution network is also used for further validation. Simulation results show that the calculating speed and the convergence of the proposed method can realize the online state estimation in the smart distribution network. The proposed method produces satisfactory estimations in the distribution networks with a few on-line quasi real-time measurements. Especially, the current estimation meets the requirement for advanced smart distribution power applications.
出处
《电工技术学报》
EI
CSCD
北大核心
2016年第1期34-44,共11页
Transactions of China Electrotechnical Society
基金
国家重点基础研究发展规划(973计划)(2013CB228205)
国家自然科学基金(51107011
51167001)资助项目
关键词
状态估计
智能配电网
数据挖掘
内点法
State estimation
smart distribution network
data mining
interior point method
