基于PMU量测的配电网稀疏估计

Sparse estimation of a distribution network based on PMU measurement

同步相量量测技术的应用为配电网估计如潮流雅可比矩阵估计和电压/相角-功率灵敏度估计提供了重要技术基础。针对潮流雅可比矩阵的相关性、稀疏性和对称性,提出了一种基于同步相量测量单元量测数据的潮流雅可比矩阵和灵敏度矩阵的稀疏估计方法,在较少量测下,有效估计了雅可比矩阵和灵敏度矩阵。进一步针对量测过程中出现的不良数据,引入鲁棒性更大的加权最小二乘法,提高了算法的鲁棒性。最后,通过IEEE33节点配电系统验证了方法的可行性。

The application of synchronous phasor measurement technology provides an important technical basis for distribution network estimation such as power flow Jacobian matrix estimation and voltage/phase angle-power sensitivity estimation.Considering the correlation,sparseness and symmetry of the power flow Jacobian matrix,a sparse estimation method of power flow Jacobian matrix and sensitivity matrix based on the measured data of a synchronous phasor measurement unit is proposed.It can effectively estimate the Jacobian matrix and the sensitivity matrix with less measurement.To tackle the problem of bad data appearing in the measurement process,a more robust weighted least squares method is introduced to improve the robustness of the algorithm.Finally,the feasibility of the method is verified on an IEEE33 node power distribution system.