Time-Varying PI Controller Gains for Guaranteed PQ Response Trajectory
The Problem
Tuning PI controller fixed gains is time-consuming and application-specific. Model-based methods for tuning time-varying PI gains do not permit control of inverter response shape and are influenced by parameter uncertainties. Data-based methods for tuning time-varying PI gains are time- consuming and susceptible to measurement errors and noise.
The Solution
Researchers at the University of Tennessee have developed a hybrid model- and data-driven method for tuning time-varying PI controller gains. This method guarantees an exponential PQ output response with a specified time constant, allowing for PQ trajectory matching. The effects of measurement error and noise are minimized, reducing the required tuning time.
Benefits
| Benefit |
|---|
| Freely design inverter PQ output trajectory with specified time constant |
| Control PQ response that exactly follows input disturbances |
| Minimize effects of measurement error and noise, as well as uncertainty and unavailability of model parameters |
| Decrease tuning time |
More Information
- Gregory Sechrist, JD
- Technology Manager, Multi Campus Office
- 865-974-1882 | gsechris@tennessee.edu
- UTRF Reference ID: 22117
- Patent Status: Patent Pending
Innovators
Dr. Fangxing (Fran) Li
James W. McConnell Professor in the Department of Electrical Engineering and Computer Science (EECS) at The University of Tennessee Knoxville. He is also an adjunct researcher at the Oak Ridge National Laboratory (ORNL).
Dr. Fangxing (Fran) Li received his PhD from Virginia Tech University in 2001. His research interests include renewable energy integration, distributed energy resources, and power system computational methods. He is an adjunct researcher at Oak Ridge National Laboratory and the campus director of Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (CURENT).
Read more about Dr. Fangxing (Fran) LiDr. Rui Bo
Assistant Professor, Department of Electrical and Computer Engineering, Missouri S&T
Dr. Rui Bo received his PhD from the University of Tennessee, Knoxville, in 2009. His research interests include computation, optimization and economics in power system operation and planning, high performance computing and its application in power systems, electricity market simulation, and evaluation and design.
Read more about Dr. Rui Bo