A PSO-MMA Method for the Parameters Estimation of Interarea Oscillations in Electrical Grids

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

An Optimized HT-Based Method for the Analysis of Inter-Area Oscillations on Electrical Systems

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

Detection and Analysis of Inter-Area Oscillations Through a Dynamic-Order {DMD} Approach

This article deals with a novel method for detecting and analyzing inter-area oscillations on electric power transmission networks. The method starts from the modal analysis performed by the dynamic mode decomposition (DMD) algorithm, which is able to exploit the synchronized acquisitions of various measurement instruments to detect the mode of a dynamic system. Compared with the classical algorithm, the proposed method presents a fundamental improvement, which ensures its reliability even without having prior information on the type of input signal. In particular, the order of the DMD, i.e., the number of modes characterizing the acquired signal, is dynamically updated according to its energy content. The method has been tested with simulated signals, considering both single-oscillation signals and two-oscillation signals, varying the amplitude, frequency, and damping of the oscillatory components. In this way, the improvement with respect to the classical DMD was highlighted and the performance in terms of deviation between the estimated and nominal parameters was evaluated. Furthermore, the assessment on real life acquired signals has been performed; the results confirmed the reliability and accuracy of the measurement method, even in the presence of noisy signals and ambient data

Axial loading MRI of the lumbar spine

Background: The aim of our study was to evaluate the incoming interrelations between chronic low back pain and biomechanical changes of the lumbar spine, using an MRI-compatible axial-loading device mimicking the standing position. Materials and methods: Fifty consecutive patients (28 males and 22 females), with both chronic low pack pain and recurrent painful blockages, were selected and studied using a 1.5 T Gyroscan Intera Philips MRI unit (Philips, Best, Holland) and a dedicated axial loading apparatus (MIKAI manufacturing, Genoa, Italy). Results: After loading, no significant modifications occurred in ten patients (20%), a spinal stenosis was seen in 18 patients (45%), an increase in the discal protrusions or hernias was detected in 8 patients (20%) and a significant accentuation of the spondylolisthesis was observed in 6 patients (15%). Conclusion: Axial loading MRI provides valuable information for specific non-invasive or operative management of low back pain