Abstract
For wide-area measurement systems and smart grids, phasor measurement units (PMUs) have become key elements since they provide synchronized information related to the fundamental frequency components of voltages and currents. In recent years, some works have extended the concept of PMU to harmonic analysis due to the proliferation of nonlinear loads. In this work, as a first contribution, the reference model for P-class and M-class PMUs provided by the IEEE Standard C37.118.1 is expanded with the aim of obtaining the harmonic information and electric power quantities. Additionally, as a second contribution, the approach of global harmonic parameters (GHPs) for PMUs is proposed. Specifically, GHPs are introduced in this work as unified quantities regarding the overall harmonic content of voltages and currents signals. With the help of these parameters, the estimation of power quality indices (PQIs) according to the IEEE Standard 1459 can be carried out but with an important advantage, i.e., a reduced amount of data, which reduces the requirements of management, storage, and analysis. Finally, the mathematical formulations for PQIs using the proposal are also presented. It is important to mention that they are equivalent to classical formulations that use individual harmonic information; however, they exploit the advantage of PMUs that require a reduced amount of data. Several tests with synthetic and real signals are carried out to validate the proposal. Results demonstrate the effectiveness and usefulness of the proposed approach.
Highlights
In power systems, the use of phasor measurement units (PMUs) in wide-area measurement systems to perform measurement, monitoring, protection, and control tasks has increased considerably [1].They are considered as the basis for measurement infrastructure in smart transmission grids [2].phasor measurement unit unit (PMU) provide simultaneously synchronized measurements of voltages and currents at different points of the power system [3]
Other works using techniques such as the fast Fourier transform, parametric methods, Prony’s method, adaptive linear networks, Kalman filtering, phase-locked-loop method, and artificial neural networks have been proposed for harmonic analysis in power systems [17,18]; they could be used in a PMU context, some aspects, such as the complexity of the technique for real-time monitoring, the convergence time in adaptive algorithms, the possible measurement errors associated to the nonstationary features of the analyzed signals in the batch processing techniques, the amount of generated data, and the computational burden, among others, have to be taken into account
From this point of view and by considering all the abovementioned aspects, it is desirable to have a PMU scheme that provides fundamental and harmonic phasor information for the estimation of power quality indices (PQIs), but with a noticeable reduction of both data and computational burden without affecting the performance requirements stated in the standards
Summary
The use of phasor measurement units (PMUs) in wide-area measurement systems to perform measurement, monitoring, protection, and control tasks has increased considerably [1]. Other works using techniques such as the fast Fourier transform, parametric methods, Prony’s method, adaptive linear networks, Kalman filtering, phase-locked-loop method, and artificial neural networks have been proposed for harmonic analysis in power systems [17,18]; they could be used in a PMU context, some aspects, such as the complexity of the technique for real-time monitoring, the convergence time in adaptive algorithms, the possible measurement errors associated to the nonstationary features of the analyzed signals in the batch processing techniques, the amount of generated data, and the computational burden, among others, have to be taken into account. PMU is used in applications that require a high rejection of aliased signals From this point of view and by considering all the abovementioned aspects, it is desirable to have a PMU scheme that provides fundamental and harmonic phasor information for the estimation of power quality indices (PQIs), but with a noticeable reduction of both data and computational burden without affecting the performance requirements stated in the standards.
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