Real-time Synchrophasor Applications for Power System Control

Authors: Ken Martin, Neeraj Nayak, Iknoor Singh, Electric Power Group, CA, USA, and Ian Dobson, Iowa State University, USA

Acknowledgement:  
This article is based upon work supported by the Department of Energy (DOE) under Award Number DE-OE0000849. Opinions and claims expressed here are strictly the work of the authors and not that of DOE or any of its representatives.
EPG expresses appreciation to project advisors Prof. Anjan Bose (WSU) and Dejan Sobajic (GEng), and Utility leads Tony Faris (BPA) and Atena Darvishi (NYPA). EPG team members include Wenyun Ju, Simon Mo, and Uday Kothapa.
For references, please see “Real-time Synchrophasor Applications to Support Power System Operations” by Zhang, et al from Pac World Conference, Raleigh NC, August 2019.

Addressing these challenges calls for new technologies and solutions. The recent expansion of synchrophasor measurement systems can be used to serve these needs. Phasor Measurement Units (PMUs) are widely distributed across the electric power network. They provide a wide area view that is well suited to assessing power flows in any pattern. They provide complex bus voltages that can be used directly for computing the system state. Unlike traditional state estimation, phasors can provide power system state even in disconnected regions, such as when a system is islanded. Their high rate measurements enable the tracking of dynamics and an immediate real-time response.
Many synchrophasor based applications have been developed that take advantage of the time-stamped high-resolution PMU data. Most of these are for off-line analysis, and they have proven very useful for operation analysis, network assessment, and model validation. Acceptance of applications for real-time uses such as operation monitoring and automatic controls has been slow. This is due to several factors including limited need for additional information beyond what SCADA provides, few applications that provide critical information, and lack of confidence in synchrophasor data. In addition, there is limited PMU coverage, due to the high cost of installation and commissioning of PMU devices, communication bandwidth limits, and cyber security concerns. The applications described in this article are targeted to provide usable, actionable information to operators by addressing these problems.

The system described in Figure1 inputs synchrophasor data from PMUs and runs it through a Linear State Estimator (LSE). The LSE performs the same basic functions as a traditional state estimator (SE) except that by using synchrophasor data the problem can be reduced to a linear problem. This allows it to run at measurement speed (50-60 solutions/second) and it always solves. The LSE provides confidence in the data by noting discrepancies and rejecting clearly bad data. It also extends the measurement set by using the model to estimate values in some places that do not have a PMU. The output of the LSE is then sent to applications that perform analysis for operations. Three applications have been developed for this project. The first is a real-time contingency analysis (RTCA) application. This application uses the system solved case from the LSE to test for problems that could be caused by contingencies and provide alerts to the operators. The second is a voltage security index (VSI) that monitors voltage through a transmission corridor and quickly provides a warning if the voltage is risking collapse. The third application is an area angle monitor that compares the phase angle across an area of the power grid with angle limits that indicate overloaded conditions and warns the operator if there is a severe condition meriting quick action.

The work presented here is based on a US Department of Energy project titled “Real Time Applications Using Linear State Estimation Technology,” which develops real-time synchrophasor applications based on PMU measurements that have been processed and augmented by the LSE.

Synchrophasor Measurements and the LSE Enhancement
Synchrophasor measurement is provided by a PMU installed at a substation where it can access voltage and current quantities. A synchrophasor includes the magnitude and phase angle of the ac voltage or current waveform. The phase angle is referenced to universal time to allow comparing all the measured phase angles together. These measurements provide the complex voltages at all measured busses in the grid along with the associated branch currents. PMUs are usually distributed across the grid, so they provide a wide area view of voltages and currents across the area of the power grid. This wide area view can provide a good overall assessment of the voltage profiles and key power flows but is generally not comprehensive enough to provide a complete measurement of state since there are rarely enough PMU measurements to cover the entire grid. Eventually PMUs may cover the entire grid with enough measurements to provide direct state measurements, but this has not been the case so far.
To respond to the need for complete state solutions and redundancy to detect errors, the linear state estimator (LSE) has been developed. The LSE can provide a state solution in real-time at the same speed as the measurements since PMUs reduce state estimation to a linear problem. LSE can validate and improve the measurements as well as extend the measurement set over a wider-area of the grid.
The LSE provides more accurate data than the raw measurement by linking the measurements together with the system model. This allows detecting most error types, including those introduced by the PMU, data communication, and the PT/CT transformation. The LSE provides a consistent set of bus voltages (i.e., steady state of the system) which can be used to compute all parameters of interest including line currents, active and reactive power flows as well as active and reactive contributions from generating units and loads.

The LSE uses the same system model (Y matrix and associated topology) as a traditional EMS but has the key advantage of working with linear equations. LSE finds the system state that is the best least square fit to the PMU complex current and voltage measurements. The LSE also checks and corrects for data and topology errors.
In practice, the LSE system model has to be reduced to the PMU observable subset. The measurement data is applied to the model and the model is kept up to date by breaker status reports included with the PMU data or reported through an ICCP link with the EMS (Figure 2). Topology changes can also be inferred by looking at the branch current, but low current flows can give false readings.
 Due to the limited coverage of PMU devices, the LSE solution will be a partial set of buses out of the entire system. In most utility phasor measurement systems, these observable buses are usually at the highest voltage levels and represent the most important nodes of the system.
The LSE can extend PMU voltage estimates one bus away from the PMU using the voltage and current measurement with the branch line characteristics, but even this may leave a substantial number of busses and lines unsolved. This sparse measurement problem posed a major problem in implementing the applications in this project.

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