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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 2 min 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. [ABSTRACT FROM AUTHOR]

This paper proposes a regularized robust recursive least squares (R3LS) method for online 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 nontypical data, which include outliers and missing data. A dynamic 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 nontypical measurement data. [ABSTRACT FROM AUTHOR]

The frequency and damping of electromechanical modes offer considerable insight into the dynamic stability properties of a power system. The performance properties of three mode-estimation block-processing algorithms from the perspective of near real-time automated stability assessment are demonstrated and examined. The algorithms are: the extended modified Yule Walker (YW); extended modified Yule Walker with Spectral analysis (YWS); and sub-space system identification (N4SID). The YW and N4SID have been introduced in previous publications while the YWS is introduced here. Issues addressed include: stability assessment requirements; automated subset selecting identified modes; using algorithms in an automated format; data assumptions and quality; and expected algorithm estimation performance. [ABSTRACT FROM AUTHOR]

Increasing levels of wind-turbine generation in modem power systems is initiating a need for accurate wind-generation transient stability models. Because many wind generators are often grouped together in wind parks, equivalence modeling of several wind generators is especially critical. In this paper, a reduced-order dynamic fixed-speed wind-generator model appropriate for transient stability simulation is presented. The model is derived using a model reduction technique of a high-order finite-element model. Then, an equivalencing approach is presented that demonstrates how several wind generators in a wind park can be combined into a single reduced-order model. Simulation cases are presented to demonstrate several unique properties of a power system containing wind generators. The results in this paper focus on horizontal-axis turbines using an induction machine directly connected to the grid as the generator. [ABSTRACT FROM AUTHOR]

Discusses the development of an autoregressive moving average (ARMA) block-processing technique to estimate low-frequency electromechanical modes from measured ambient power system. Importance of estimating electromechanical modes in power systems; Simulation methods for modes estimating; Nature of electromechanical oscillations in a power system.

This letter presents a method for tracking the damping contribution of a power system component in near real-time based upon oscillation energy dissipation. By transforming the energy flow into the frequency domain, the new derivation demonstrates a new theoretical basis and a wider applicability of using the energy-flow theory to analyze power system damping problems. The concept is demonstrated via a non-linear simulation and an actual-system data set. [ABSTRACT FROM PUBLISHER]