Signal Processing Techniques for Determining Powerplant Characteristics
What mathematical/software tools can be used and/or developed to derive powerplant characteristics? More specifically, can common digital signal processing techniques, which are currently being used in other applications and arenas, be applied to generator control systems for better determining powerplant model structure and parameters? Also, can these signal processing techniques be used to verify performance of generator control systems?
Need and Benefit
The Bureau of Reclamation (Reclamation) operates hydroelectric generators connected to the western U.S. power system and must operate by North American Electric Reliability Council and Western Electricity Coordinating Council (WECC) guidelines to reliably and adequately supply electric power in a manner to support stewardship of Reclamation facilities for the American public. Developing new methods to determine how Reclamation generators affect power system stability and reliability will help us enhance system stability, reduce costs, and meet WECC requirements. This is a corporate-wide responsibility.
The research goal is to prevent blackouts and improve the safety margin of the power system to prevent the four "D" (death, disaster, dollars, disgrace). Preventing one regional blackout can result in avoided costs of over $1 billion. Reclamation does not want to be responsible for creating a blackout. Power system operation is based on limitations calculated by computer model simulations. Given increasing demand on energy supply and delivery in the western U.S., the system is operated closer to the point of instability than in the past. Therefore, improving the accuracy of computer models is of primary importance. Several recommendations in the final report of the US-Canada Power System Outage Task Force on the Aug. 14, 2003, blackout call for expanded research into and improved methods for system monitoring and modeling.
To achieve this goal, we plan to use proven signal processing techniques for identifying structure, dynamic parameters, and performance of generators and controllers (voltage regulators, power system stabilizers, speed governors) used in Reclamation powerplants. Obtaining this information every 5 years is required by WECC and soon may be required by the Federal Energy Regulatory Commission (FERC). The identification process presently requires engineers to travel to the generation site with specialized equipment, insert test signals, record responses, and interpret results. This is high risk, time consuming, labor intensive, and costly. Identification methods developed using signal processing techniques will be used to replace manual methods for verifying and maintaining controller performance.
Software will be developed using relevant signal processing techniques to identify generator and controller characteristics, dynamic parameters, their effects on the power system, and any unusual operation that may be occurring. We plan to use existing plant condition monitoring equipment at several Reclamation facilities for collecting continuous data, as well as using existing field data already collected during controller identification purposes. We will test our concepts in the laboratory with our real-time simulation computer running a single-machine-infinite-bus model, in software on a multimachine power system simulation program, and on several actual systems. New test and analysis methods based on data acquired during staged tests or via continuous monitoring will determine the impact of generator controllers on power system stability in a more efficient way while adding the ability to monitor impact of long-term power system operation on powerplant equipment life.
Benefits will improve commissioning and periodic field testing efficiency of generator controllers, result in less travel for engineers, and save up to 50 percent for each commissioning/field test (up to $200k annually for Reclamation). Efforts target all Reclamation power facilities. As other utilities use the same manual techniques for controller identification, potential for both Federal/non-Federal technology transfer exists. Additional benefits will be derived by accurately identifying and maintaining adequate stability margins and machine capability, which can save up to $100 million in avoided cost by eliminating the need for additional lines and helping prevent blackouts.
Contact the Principal Investigator for information about partners.
Bureau of Reclamation Review
The following documents were reviewed by experts in fields relating to this project's study and findings. The results were determined to be achieved using valid means.
Document ID 600: this document contains protected information and it cannot be freely downloaded from USBR.gov. Contact the Principal Investigator to request a copy of this document.
Signal to Noise: Analyzing Generator Performance and Reliability (final, PDF, 540KB)
By Kyle W. Clair,
Publication completed on September 30, 2014