Modelling and Analysis of Phasor Measurement Units for Wams Applications

Abstract

Wide Area Measurement Systems (WAMS) which cover an extensive geo- graphical area help in better monitoring, control and protection of power sys- tems. Hence, the conventional Supervisory Control and Data Acquisition Sys- tem (SCADA) is being replaced or augmented by WAMS across all modern power grids. The time-stamped WAMS data obtained at high sampling fre- quencies provides information related to both the static and dynamic behaviour of the power systems, in contrast to the SCADA systems which provide data at a very low frame rate. The primary measuring device in the WAMS archi- tecture is the Phasor Measurement Unit (PMU) which outputs synchrophasors, frequency and rate-of-change of frequency (ROCOF). The estimation capabil- ities of PMU algorithms are verified using test signals recommended by the IEEE standard for synchrophasor measurements in power systems. Over the last two decades, PMU algorithms and the application of PMUs in WAMS have been a focal point of research for power system engineers. In this regard, a de- tailed discussion with respect to the standard based PMU testing is provided using a DFT-based PMU in a tutorial manner. Various methods to time-tag phasors are demonstrated in order to show the importance of the placement of the phasor sample at different points in an observation window. Varieties of static and dynamic models-based PMU algorithms are imple- mented and tested in an integrated PMU architecture environment. This archi- tecture provides both causal and non-causal outputs in a single module which can be used for different power system applications. Various phase-angle com- pensation schemes have been suggested for a causal-PMU to show the supe- riority of the bus voltage-signal frequency against the line current-signal fre- quency as the input for compensation. A power system stabilizer (PSS) is designed based on the Phase Angle Difference (PAD) signals to illustrate the influence of causal and non-causal PMUs on the small-signal stability of a power system. A single-phase frequency estimation technique which involves signal-reconstruction process is proposed. From the reconstructed time-domain signals, the fre- quency is obtained using the Convolution Average Filter (CAF) and a single- phase demodulation technique employing Hilbert filter (HF). The proposed 9method provides an M-class compliant frequency estimator when augmented with a conventional P-class algorithm. Accuracy of the reconstruction-based approach is verified through test signals recommended by the IEEE standard, as well as by using signals obtained from the ISO-New England (ISO-NE) power system and simulation based studies. The use of ROCOF as a poten- tial candidate signal in addition to frequency signal for mode identification is explored. It is also noted through a lab experimentation that an accurate frequency estimation during an out-of-step (OOS) condition is not straightfor- ward. Further, an event detection and localization tool is developed to illustrate an application of WAMS signals. Events in power system signals are detected using the wavelet transform and the standard deviation based methods. The ef- fectiveness of these methods is demonstrated using practical signals from the ISO-NE power system as well as signals obtained from a simulation based 4- machine, 10-bus power system. A new event localization algorithm based on the number of PMUs involved in the event detection stage is also presented. Ef- fect of threshold computation methods on the event detection and localization results is explored. As a part of the event analysis, a scheme to detect an OOS condition, is developed using PAD signals obtained from across transmission lines. This is found to enable the supervisory Power Swing Blocking (PSB) function for a relay during OOS condition to avoid unintentional tripping of lines.