Poster: Forced Oscillations in the Western Interconnection with the Pacific DC Intertie Wide Area Damping Controller.
Abstract not provided.
Engineering topics
Publications and source records attributed to Trudnowski, Daniel J.
Abstract not provided.
Abstract not provided.
Small signal stability is an inherent characteristic of dynamic systems such as power systems. Pole positioning through power system stabilizers (PSS) is often used for improving damping in power systems. A well-designed PSS can be very effective in damping oscillations, especially local oscillations. However, designing PSSs for inter-area oscillations has been a very challenging task due to time-varying operating conditions affecting the characteristics of inter-area oscillations. This paper explores the sensitivity relationship between oscillations and operating conditions and employs the relationship to derive recommendations for operator’s actions to adjust operating conditions so as to improve damping. Low damping is usually considered to be a result of heavy power transfer in long distance. Studies in this paper show that this generally holds true while locations have significant impact on damping of oscillations. Therefore it is important to consider locations in deriving recommendations. This paper proposes the concept of relative modal sensitivity and presents the application of relative modal sensitivity to derive recommendations for operator’s action in damping control.
Small signal stability problems are one of the major threats to grid stability and reliability in the U.S. power grid. An undamped mode can cause large-amplitude oscillations and may result in system breakups and large-scale blackouts. There have been several incidents of system-wide oscillations. Of those incidents, the most notable is the August 10, 1996 western system breakup, a result of undamped system-wide oscillations. Significant efforts have been devoted to monitoring system oscillatory behaviors from measurements in the past 20 years. The deployment of phasor measurement units (PMU) provides high-precision, time-synchronized data needed for detecting oscillation modes. Measurement-based modal analysis, also known as ModeMeter, uses real-time phasor measurements to identify system oscillation modes and their damping. Low damping indicates potential system stability issues. Modal analysis has been demonstrated with phasor measurements to have the capability of estimating system modes from both oscillation signals and ambient data. With more and more phasor measurements available and ModeMeter techniques maturing, there is yet a need for methods to bring modal analysis from monitoring to actions. The methods should be able to associate low damping with grid operating conditions, so operators or automated operation schemes can respond when low damping is observed. The work presented in this report aims to develop such a method and establish a Modal Analysis for Grid Operation (MANGO) procedure to aid grid operation decision making to increase inter-area modal damping. The procedure can provide operation suggestions (such as increasing generation or decreasing load) for mitigating inter-area oscillations.
ModeMeter techniques for real-time small signal stability monitoring continue to mature, and more and more phasor measurements are available in power systems. It has come to the stage to bring modal information into real-time power system operation. This paper proposes to establish a procedure for Modal Analysis for Grid Operations (MANGO). Complementary to PSS’s and other traditional modulation-based control, MANGO aims to provide suggestions such as increasing generation or decreasing load for operators to mitigate low-frequency oscillations. Different from modulation-based control, the MANGO procedure proactively maintains adequate damping for all time, instead of reacting to disturbances when they occur. Effect of operating points on small signal stability is presented in this paper. Implementation with existing operating procedures is discussed. Several approaches for modal sensitivity estimation are investigated to associate modal damping and operating parameters. The effectiveness of the MANGO procedure is confirmed through simulation studies of several test systems.
This paper investigates the design of effective input signals for low-level probing of power systems. In 2005, 2006, and 2008 the Western Electricity Coordinating Council (WECC) conducted four large-scale system wide tests of the western interconnected power system where probing signals were injected by modulating the control signal at the Celilo end of the Pacific DC intertie. A major objective of these tests is the accurate estimation of the inter-area electromechanical modes. A key aspect of any such test is the design of an effective probing signal that leads to measured outputs rich in information about the modes. This paper specifically studies low-level probing signal design for power-system identification. The paper describes the design methodology and the advantages of this new probing signal which was successfully applied during these tests. This probing input is a multi-sine signal with its frequency content focused in the range of the inter-area modes. The period of the signal is over two minutes providing high-frequency resolution. Up to 15 cycles of the signal are injected resulting in a processing gain of 15. The resulting system response is studied in the time and frequency domains. Because of the new probing signal characteristics, these results show significant improvement in the output SNR compared to previous tests.
This paper proposes a regularized robust recursive least squares (R3LS) method for on-line estimation of power-system electromechanical modes based on synchronized phasor measurement unit (PMU) data. The proposed method utilizes an autoregressive moving average exogenous (ARMAX) model to account for typical measurement data, which includes low-level pseudo-random probing, ambient, and ringdown data. A robust objective function is utilized to reduce the negative influence from non-typical data, which include outliers and missing data. A dy-namic regularization method is introduced to help include a priori knowledge about the system and reduce the influence of under-determined problems. Based on a 17-machine simulation model, it is shown through the Monte-Carlo method that the proposed R3LS method can estimate and track electromechanical modes by effectively using combined typical and non-typical measurement data.