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This article deals with the parameters’ measurement of interarea oscillations, which are low-frequency damped oscillations that affect the high-voltage transmission lines when an unbalance between the power demand and the generated power occurs. The authors propose a method that processes the samples provided by the phasor measurement unit (PMU) and performs the online estimation of the parameters that characterize the interarea oscillations. The method takes advantage of the speed of a heuristic algorithm, such as the particle swarm optimization (PSO), but performs an enhancement on the results to increase the reliability. The tests carried out for the method assessment prove that the proposed method is characterized by a fast response, high accuracy, and excellent reliability, regardless of the type of oscillation that is considered.

The paper deals with a novel version of the DMD algorithm to estimate the parameters of inter-area oscillations. In particular, the algorithm is called DMD with dynamic order, in opposition with the classical algorithm, that is known as static order DMD. The tests of static order algorithm with simulated signals have reveal some disadvantages, mainly related to the poor ability of the method to adapt to the input signal. The dynamic order allows, instead, to identify only the oscillatory modes actually present in the signal, on the basis of a preset energy threshold. The selection of the proper threshold is, therefore, a crucial stage. In the paper the assessment performed in order to select the optimal threshold is presented. Experimental tests involved both simulated signal and real frequency signals registered in a real WAMS.

The paper deals with a novel method for the analysis of low-frequency inter-area oscillations, a harmful phenomenon that can be more and more frequent in electrical power systems due to the expansion of interconnected power grid. In particular, inter-area oscillations are electromechanical oscillations involving groups of generators geographically far from each other; correctly and timely estimating their parameters is a fundamental task to preserve the stability of the electrical power system. Phasor Measurement Unit (PMU) technology has become the key element in Monitoring and Control systems of Transmission System Operators offering new opportunities for improving their situational awareness. Proposed method processes measures provided by the PMUs to extract the oscillating components and, for each of them, estimates characteristic parameters such as frequency and damping. To this aim, the method exploits a combination of the Hilbert Transform and some optimization algorithms, thus gaining the following improvements: (a) enhanced capability of separating oscillatory components, thanks to a new strategy for the choice of bisecting frequency, (b) possibility of separating components characterized by frequency difference lower than the spectral resolution, (c) remarkable accuracy associated with the damping estimates of each oscillation and (d) robustness to the noise affecting the input signal. Results obtained in tests involving either synthesized signals or simulated electrical systems finally assessed the promising performance of the proposed method.

The paper deals with the analysis of inter-area oscillations. that originates from power transients occurred in high extension grids. The research activity is focused on the implementation of a method capable to provide the manager of the national transmission grid with a tool for real time and accurate monitoring of the power system stability. In particular, the authors present a signal-based algorithm which, starting from the values estimated by the Phasor Measurement Units (PMUs) on the grid, allows the online monitor of the parameters (damping and frequency) characterizing the inter-area oscillations. The proposed algorithm is based on the Particles Swarm Optimization (PSO) method, but the traditional PSO has been enhanced through the use of a Continuous Weighted Average (CWA) which, at each iteration step, filters the PSO outputs assuring the reliability of the estimates.

The paper deals with a novel method to measure inter-area oscillations, i.e., electromechanical oscillations involving groups of generators geographically distant from one another and ranging within the frequency interval from 0.1 Hz up to 1 Hz. The estimation of the parameters characterizing inter-area oscillations is a crucial objective in order to take the necessary actions to avoid the instability of the transmission electrical system. The proposed approach is a signal-based method, which uses samples of electrical signals acquired by the phasor measurement unit (PMU) and processes them to extract the individual oscillations and, for each of them, determine their characteristic parameters such as frequency and damping. The method is based on Hilbert transformations, but it is optimized through further algorithms aiming at (i) improving the ability to separate different oscillatory components, even at frequencies very close to each other, (ii) enhancing the accuracy associated with the damping estimates of each oscillation, and (iii) increasing the robustness to the noise affecting the acquired signal. Results obtained in the presence of signals involving the composition of two oscillations, whose damping and frequency have been varied, are presented. Tests were conducted with signals either synthesized in simulated experiment or generated and acquired with actual laboratory instrumentation.