Introduction: Power systems are increasingly reliant on Synchrophasor-based methods for monitoring, protection, and control. Testing of such schemes is of critical importance before they can be accepted and deployed.
This paper describes a new platform for validating wide-area monitoring, protection, and control (WAMPAC) systems in real-time. The platform is an extension to an RTDS power system simulator, and uses the “GTFPGA” unit to generate 16 simultaneous streams of IEC 61850-9-2 Sampled Value (SV) data representing waveforms from the simulation. Each SV data stream contains three-phase voltage and current samples from four independent locations in the RTDS simulation. This is equivalent to representing data for 64 unique and distributed Phasor Measurement Units (PMUs). Each SV stream is connected to a quad-core ARM-based device (in this case, a Raspberry Pi 3 Model B+) to process the waveform data according to a software PMU signal processing algorithm – with each CPU core dedicated to implement one PMU. PMU output data is streamed from the ARM device according to the IEEE C37.118.2 standard.
High-Fidelity PMU Implementation: The PMU algorithm executed within each ARM processor core uses an adaptive filter window  and has been selected for to its state-of-the-art measurement performance. This platform therefore provides a convenient and cost effective method for emulating a large number of high-fidelity PMUs that are driven by power system simulation data. The component can readily be added to existing RTDS simulations to enable WAMPAC functions. Although an RTDS can also generate multiple
PMU data streams using GTNET cards, this approach is limited in the choice of PMU algorithm and the Synchrophasor dataset used (although using GTNET cards does have advantages such as greater convenience of integration within an RTDS simulation, guaranteed real-time performance, and support for other protocols).
An open source mapping of IEC 61850-7-2 to web services ,  has been used to automatically create an HTTP interface for monitoring and managing each PMU. A web interface has been created to allow the PMU type (P class or M class) and reporting rate to be dynamically modified, at run-time, for different types of experiments. There is also flexibility to entirely change the PMU algorithm if required.
The platform is designed to efficiently direct SV and IEEE C37.118.2 traffic to only the correct devices, and the processor allocation on the ARM processor is strictly controlled to ensure real-time operation.
Conclusions: This development provides a new way for emulating 64 high-fidelity PMUs in large-scale WAMPAC systems, particularly for validating novel visualisation, control, and data analytics methods. The platform has already been used for validating wide-area frequency control and backup transmission system protection applications.
Steven Blair, University of Strathclyde