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Online monitoring of inter-area oscillations is a vital need for secure operation of large-scale power systems. This paper aims at online estimation of inter-area modes by a novel stabilized fast transversal recursive least squares (SFTRLS) filter running on ambient power system data received from phasor measurement units. The SFTRLS filter is a fast finite-impulse response adaptive filter that is widely used in communication applications, such as noise and echo cancelation. It has the lowest computational complexity among least-squares filters and directly calculates coefficients of the parametric model selected for identifying a system under study. In the proposed method, the SFTRLS filter along with digital band-pass Butterworth filter and down-sampling blocks are implemented in online manner for identification of an autoregressive model that describes the measured power system ambient signal. Applicability and accuracy of the proposed method are evaluated using real measurement data of western systems coordinating council (WSCC) breakup on August 10, 1996, as well as simulated ambient data of the IEEE 16-machine, 5-area test system excited by white noise random load modulations. Its performance is investigated under different conditions of load modulations, measurement noises, sudden change in damping ratio, and occurrence of three-phase faults. The simulation results verify efficient and robust performance of the proposed method for modal estimation of real large-scale power systems. [ABSTRACT FROM AUTHOR]

This paper proposes a novel error-feedback lattice recursive least-squares (EF-LRLS) filter for online estimation of power system oscillatory modes. The EF-LRLS filter is applied to ambient data provided by phasor measurement units to identify the autoregressive (AR) model parameters. This filter has a modular structure; accordingly, if the length of the filter equals $N$ , it identifies AR(1) to ${\rm{AR(}}N)$ models concurrently. In the proposed method, removing very low and high frequencies and resampling steps are fulfilled in an online fashion. This adaptive filter has less computational complexity than standard RLS filter, making it an appropriate choice for online system identification. The proposed algorithm is tested using simulated ambient data of the 16-machine, 68-bus test system, as well as real measurement data of the WSCC system breakup on Aug. 10, 1996. Performance of the proposed algorithm is examined under different conditions with different amplitudes of variation and signal-to-noise ratio. The results prove accuracy, robustness, and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• Developing a model-based method for generation redispatch to damp oscillatory modes. • Calculation of oscillatory mode sensitivity factors in a systematic manner. • Determining the effective generators by the proposed damping ratio sensitivity index. This paper presents a model-based method for applying online proactive generators redispatch to improve damping of the critical electromechanical oscillations of power system. The proposed method comprises two stages: 1) monitoring modal characteristics of oscillatory modes in ambient condition, and 2) applying generators redispatch based on sensitivities of the critical mode to the generators active power changes using a new analytic method. An online identification method such as error feedback lattice recursive least square adaptive filter is applied for online estimation of the oscillatory modes. Then, whenever the damping ratio of an identified mode is less than a preset threshold, its sensitivities to the generators active power changes are calculated in terms of power system model parameters and power flow variables, which can be obtained via state estimation or measured directly by phasor measurement units. The formulae for calculating these sensitivity factors are developed considering 3 rd order dynamic model of synchronous generators along with excitation system and power system stabilizer, and ZIP model of loads. The resultant equations are organized as a quadratic eigenvalue problem and the sensitivity factors are calculated in a systematic manner. Nextly, the candidate generators are ranked online by a new index based on sensitivity factors. Finally, using the proposed index, the most effective generators are proactively redispatched to improve the critical mode damping before occurrence of any fault that jeopardizes the system stability. Applicability and accuracy of the proposed formulae are investigated in the IEEE 39-bus New England power system. Effectiveness of the proposed method is also confirmed with time-domain simulation and state space analysis. [ABSTRACT FROM AUTHOR]