【摘要】 基于SCADA/PMU混合量测的电力系统动态状态估计算法,目前主要是先进行量测变换再进行动态估计,尝试结合静态估计和动态估计的优点,提出一种新的方法。该方法首先对SCADA量测数据运用经典的加权最小二乘法(WLS)进行静态状态估计,估计结果和PMU量测中的电压相量共同形成量测数据集,再进行线性动态状态估计。WLS方法能保证状态估计的质量和算法的收敛性能,同时线性动态估计只选用PMU量测的电压相量,避免量测变换及其产生的误差,而且雅可比矩阵高度稀疏,计算时间较短。在IEEE14节点系统上的仿真结果表明,此方法具有较好的滤波和预测效果。更多还原

【Abstract】 At present,the dynamic state estimation algorithms for the power system,based on the multiple measurements(SCADA/PMU),largely follow two steps: measurements transformation and dynamic estimation.A new model that tries to combine the static and the dynamic estimation method is proposed.As to the SCADA-measured data,the traditional WLS method is taken for the static state estimation first.The results of this step,that is,the amplitude and phase of the node voltage,together with the voltage phasor measured by PMU,form the data for the linear dynamic state estimation.The quality and accuracy of the WLS method are ensured,meanwhile the constant Jacobian matrix is highly sparse and the calculating time is greatly reduced.Simulations on an IEEE 14-bus test system demonstrate that the method has a good validity in filtering and forecasting for the voltage phasor.更多还原