The development of software models of Phasor Measurement Units (PMUs) within Real-Time Simulators (RTSs) represents a promising tool for the design and validation of monitoring and control applications in electrical power networks. In this sense, it is necessary to find an optimal trade-off between computational complexity and estimation accuracy. In this paper, we present the design and implementation of two new PMU models within the Opal-RT eMEGAsim RTS. The synchrophasor estimation algorithm relies on a Compressive Sensing Taylor-Fourier Model (CS-TFM) approach, and enables us to extract the dynamic phasor associated to the signal fundamental component. The estimation accuracy of the proposed models is characterized with respect to the compliance tests of the IEEE Std. C37.118.1.

In this paper, we present a processing technique to determine the statistical distribution of additive measurement noise in real-world acquisitions, with specific reference to Phasor Measurement Unit (PMU) applications in Active Distribution Networks (ADNs). The proposed approach identifies the power signal fundamental component, as well as harmonic and interharmonic interferences, and models the measurement noise as a Gaussian random variable. First, we describe the algorithm main stages and the criteria for the most suitable parameter setting. Then, we carry out a numerical validation inspired by IEEE Std. C37.118.1 test conditions. Finally, we validate the proposed approach on real-world measurements acquired by a PMU in the distribution network of EPFL campus.