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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]

This paper focuses on the use of quadratic time-frequency distributions (QTFDs) to characterize the temporal variation of low-frequency electromechanical oscillations (LFEOs) using ringdown data. A refined Margenau-Hill distribution (MHD) and a procedure to extract the instantaneous frequencies and damping factors as well as initial phase angles of system low-frequency modes when the analyzed signal is multi-component are proposed. The refinement process enjoys a fast-converging iterative algorithm and without loss of generality it can be applied to other QTFDs for using in other applications. A non-stationary synthetic signal as well as simulated ringdown data of a 5-area, 16-machine power system and real measured data of Western Systems Coordinating Council (WSCC) system are used to demonstrate the efficiency of the proposed method in the presence of measurement noise. [ABSTRACT FROM AUTHOR]

• Calculating sensitivity factors of electromechanical modes, generators reactive power, transmission lines apparent power and bus voltage magnitudes by a systematic method. • Determine cost-effective proactive remedial actions to damp critical oscillatory modes considering security constraints. • Proposing an iterative MINLP optimization model to determine the best set of remedial actions. • Specifying the effective generators to change voltage set point and active power by the proposed damping ratio sensitivity index. This paper proposes a comprehensive analytic method for applying various optimal remedial actions to improve critical electromechanical modes damping without jeopardizing damping of non-critical modes and violating security constraints of power system. Generators and reactive power sources redisptach, demand side management and the generators voltage reference tuning are remedial actions that are considered here. Dynamic equations of the flux-decay dynamic model of generators, standard dynamic models of excitation system and power system stabilizer and algebraic equations of active and reactive powers balance are formulated in the quadratic eigenvalue problem framework. With simultaneous use of system parameters and online measured data, sensitivity factors of electromechanical modes, generators reactive power, transmission lines apparent power and the buses voltage amplitude with respect to the mentioned remedial actions are calculated. Consumers, generators and reactive power sources are independent agents that offer their price bid to contribute in remedial action schemes. Finally, using sensitivity factors, the best remedial action is determined by mixed-integer nonlinear optimization subject to the minimum required damping ratio and security constraints of transmission lines congestion, generators reactive power capability and buses voltage amplitude. The proposed method is demonstrated on the IEEE 39-bus power system and the results highlight its efficacy. [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]