In this paper it is shown that M class PMU (Phasor Measurement Unit) reference model for phasor estimation recommended by the IEEE Standard C37.118.1 with the Amendment 1 is not compliant with the Standard. The reference filter preserves only the limits for TVE (total vector error), and exceeds FE (frequency error) and RFE (rate of frequency error) limits. As a remedy we propose new filters for phasor estimation for M class PMU that are fully compliant with the Standard requirements. The proposed filters are designed: 1) by the window method; 2) as flat-top windows; or as 3) optimal min-max filters. The results for all Standard compliance tests are presented, confirming good performance of the proposed filters. The proposed filters are fixed at the nominal frequency, i.e. frequency tracking and adaptive filter tuning are not required, therefore they are well suited for application in lowcost popular PMUs.
Both the growing number of dispersed generation plants and storage systems and the new roles and functions on the demand side (e.g. demand side management) are making the operation (monitoring and control) of electrical grids more complex, especially in distribution. This paper demonstrates how to integrate phasor measurements so that state estimation in a distribution grid profits optimally from the high accuracy of PMUs. Different measurement configurations consisting of conventional and synchronous mea- surement units, each with different fault tolerances for the quality of the calculated system state achieved, are analyzed and compared. Weighted least squares (WLS) algorithms for conventional, linear and hybrid state estimation provide the mathematical method used in this paper. A case study of an 18-bus test grid with real measured PMU data from a 110 kV distribution grid demonstrates the improving of the system’s state variable’s quality by using synchrophasors. The increased requirements, which are the prerequisite for the use of PMUs in the distribution grid, are identified by extensively analyzing the inaccuracy of measurement and subsequently employed to weight the measured quantities.