Towards Highly Efficient State Estimation With Nonlinear Measurements in Distribution Systems
Towards Highly Efficient State Estimation With Nonlinear Measurements in Distribution Systems
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DOI：
10.1109/tpwrs.2020.2967173
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发表时间：
2020-01
影响因子：
6.6
通讯作者：
Ying Zhang;Jianhui Wang
中科院分区：
文献类型：
--
作者：
Ying Zhang;Jianhui Wang
提出了一种新颖高效的配电网状态估计(DSSE)方法，该方法考虑了监控和数据采集(SCADA)系统的非线性测量。传统的基于加权最小二乘(WLS)准则的DSSE需要多次蒙特卡罗模拟来进行整体精度评估，而且由于非线性迭代过程，计算成本较高。该方法利用电压的泰勒级数建立区间形式的线性DSSE模型，然后用区间算法求解该模型。该方法通过对测量值的一次随机抽样获得准确和稳健的估计，并且计算效率很高。在IEEE 34节点配电网中的对比分析表明，相对于基于非线性WLS的方法，估计结果有所改善。
This letter proposes a novel and highly efficient distribution system state estimation (DSSE) method with nonlinear measurements from supervisory control and data acquisition (SCADA) systems. Conventional DSSE based on the weighted least square (WLS) criterion requires multiple Monte Carlo simulations for overall accuracy evaluation and high calculation cost due to a nonlinear iterative process. The proposed method uses the Taylor series of voltages for constructing a linear DSSE model in the interval form and then solves this model by interval arithmetic. This method obtains accurate and robust estimates via a single random sampling of measurements and is computationally efficient. The comparative analysis in the IEEE 34-bus distribution system points to improved estimation results relative to the nonlinear WLS-based method.