The challenges of power grid stability
Pacific Northwest National Laboratory is involved in a broad range of grid stability research, including voltage stability, transient stability analysis and small signal stability.
Voltage stability is a phenomenon that causes the electric power grid to fail due to a collapsing (decreasing) voltage which propagates across the grid. Voltage stability is well understood yet challenges remain, including devising ways to best manage the electric power grid to prevent such an event, or to stop it quickly and effectively should one occur.
Pacific Northwest National Laboratory additionally performs research in transient stability analysis--evaluating the immediate effects of the grid following a large disturbance and determining how major disturbances propagate throughout the grid.
Click for a larger image.
We also perform work in one of the most complex areas of electric power grid stability--small signal stability. Problems of this type often occur without the knowledge of grid operators. Minor disturbances in the grid can grow into very large grid events. For example, on August 10, 1996, power oscillations between two groups of generators, one in Canada and another in Southern California, began oscillating with each other at an uncontrolled rate. At that time, technology did not permit the power oscillations to be observable by the grid operators, and the result was the largest blackout in the history of the Western power grid. The blackout caused 30,000 megawatts of load to be lost, and the entire western interconnection was broken into five separate pieces. To put this in perspective, the amount of power that was lost was equivalent to 30 cities roughly the size of Seattle.
Learn more about the August 1996 and the August 2003 blackouts.
Monitoring grid stability in real-time
Pacific Northwest National Laboratory is conducting research that will help grid operators understand the status of grid stability in real-time, allowing them the opportunity to improve the situation before the consequences are realized.
This graphic shows a tool developed by PNNL that runs in PNNL's Electricity Integrated Operations Center (EIOC) on real-time streaming synchrophasor data. Click for a larger image.
In collaboration with the University of Wyoming, Montana Tech of the University of Montana, Bonneville Power Administration and Electric Power Group, Pacific Northwest National Laboratory is developing mathematical algorithms to detect the stability of the grid at any moment in time. These algorithms use synchrophasor data that is acquired from across the western grid without delay. The image to the right shows a tool developed at Pacific Northwest National Laboratory that identifies modes of oscillation and their respective damping. This type of analysis is typically referred to as "system identification" since the incoming phasor data are used to define the characteristics of the power grid system from moment to moment. Current research is moving forward on developing a tool that will quickly provide corrective actions to the grid operators should an instability exist.
If you would like this technology in your control room, or would like to participate in its development, please let us know.
See how this technology could have helped operators during the August 10, 1996, blackout of the Western Interconnection. The mode with a red circle around it (0.25 Hz North-South mode) went unstable during this event. Operators had about 5 minutes to respond after observing that this mode was moving toward a lower and lower damping ratio. Video.
The top chart of the video shows synchrophasor data of real power imported into California from the Pacific Northwest (California-Oregon Intertie) in the time domain. The bottom left signal is a Fast Fourier Transform of the same data showing the energy content in each major inter-area oscillatory mode on the Western Interconnection. The bottom right chart is the S-Plane showing lines of constant damping ratio for each of these modes. As each dot moves toward the right side of the chart, it represents an increasingly unstable condition. Movement of these modes is due to two factors: 1) changing grid conditions, and 2) the continuous re-calculation using streaming synchrophasor data.