1,721,047 research outputs found
A Hybrid Control System for LC filters that couple Energy Storage Systems with AC grids
No full textA hybrid control system for LC network filters is proposed in this paper, which enables coupling energy storage systems with the main grid suitably. The proposed control system is developed by combining both linear and predictive control approaches: particularly, the outer grid current loop is designed by means of PI regulators, whereas the intermediate capacitor voltage and the inner inductor current loops are designed in a deadbeat predictive control fashion. As a result, three nested loops have been achieved, whose performance can be set properly through dynamic decoupling and multi-rate sampling. The effectiveness of the proposed solution is verified through numerical simulations, which refer to different grid operating conditions in terms of active/reactive power exchanges
Tracking Power Systems Events: PMU, Reporting Rate, Interpolation
No full textThe increasing penetration of renewable energy sources make modern power systems more prone to fast dynamics and system contingencies. In this scenario, Phasor Measurement Units (PMUs) are required not only to provide a snapshot of the system state at a given reporting time instant, but also to track the time evolution. This capability does not depend uniquely on the accuracy of the synchrophasor estimation algorithm, but more generally on the configuration of the PMU itself and how data is employed. In this context, the paper investigates the potential advantages and the open issues of PMU-based dynamic tracking using real-world datasets, discussing how different algorithms and reporting rates affect the overall results
Compressive Sensing Taylor-Fourier Multifrequency Approach for Three-Phase Signals
Full text linkPhasor Measurement Units represent nowadays a key technology for the development of new monitoring and control applications in transmission and, in a likely future scenario, also distribution systems. For this reason, a lot of effort is ongoing in designing PMU algorithms that are more accurate and responsive. In this regard, addressing the problem of tracking faster dynamics while cancelling the impact of harmonics, interharmonics and wideband disturbances has great relevance. This paper leverages the properties of three-phase signals to unlock the potentiality of recently proposed compressive sensing weighted Taylor-Fourier multifrequency (CS-WTFM) models to design a new algorithm (CS3-WTFM) with higher performance, particularly in the presence of interharmonic interference. Simulations prove CS3-WTFM effectiveness with reductions of total vector, frequency and rate of change of frequency errors of one or even two orders of magnitude under several testing conditions
Enhanced Support Recovery for PMU Measurements Based on Taylor-Fourier Compressive Sensing Approach
Full text linkModern distribution networks are characterized by higher distortion and faster variability of voltages and currents. Accurate synchrophasor, frequency, and rate-of-change-of-frequency measurements thus ask for new techniques trying to reduce latency while limiting the impact of spurious components. In this respect, Taylor-Fourier multifrequency approach is a good candidate for phasor measurement units intended for distribution system applications. In this present article, we propose an enhanced version of this approach based on the joint application of window functions and iterative support refinement by means of the phasor first-order derivative. The performance of the algorithm is thoroughly characterized through extensive numerical simulation of nonstandard test conditions that reproduce the challenges of real-world scenarios, with fundamental dynamics superimposed on interfering tones. The reported results confirm the enhanced spectral support recovery, resulting in a remarkable improvement of estimation accuracy
Synchrophasor Estimation for Three-Phase Systems Based on Taylor Extended Kalman Filtering
Full text linkSynchronized phasor and frequency measurements are key tools for the monitoring and management of modern power systems. Under dynamic conditions, it is vital to define algorithms that allow accurately measuring time-varying signals with short latencies and high reporting rates. A dynamic phasor model can help the design of these algorithms and, in particular, of those based on the Kalman filter approach. This article proposes a three-phase synchrophasor estimator based on the extended Kalman filter; state variables are obtained from Taylor expansions of amplitudes and phase angles. The underlying dynamic model considers the inherent relationship among the phases and includes harmonics in an effective way. The process noise covariance matrix that allows representing the uncertainty introduced by the dynamic model has been written by considering that practical ac power systems are nearly three-phase symmetric during typical operation. This a priori information allows improving noise rejection and increasing accuracy in the presence of amplitude modulation, as highlighted by the reported simulation results
A space vector phase-locked-loop approach to synchrophasor, frequency and rocof estimation
No full textPhasor measurement units represent the most advanced measurement devices in ac power systems. Their most important feature is permitting to estimate synchrophasor, frequency and rate of change of frequency of voltages and currents in a shared, synchronized timescale. Most of the estimation algorithms have been designed to operate with a unique signal; however, ac power systems are inherently three-phase and weakly unbalanced during regular operation. Therefore, these three-phase signals benefit from peculiar properties than can be leveraged by specifically suited measurement algorithms. For this reason, space vector based techniques have been proposed. Usually, the reference frame is supposed to be stationary or rotating at the rated angular frequency. This work proposes to exploit measurements performed in a previous reporting instant in order to generate the instantaneous angular position of the reference frame, so that it tracks the phase evolution of the positive sequence synchrophasor. A P class implementation is reported, and the results highlight excellent performance. Accuracy is remarkable even under conditions going well beyond those required by compliance tests
E-learning in instrumentation and measurement courses
No full textE-learning is the one possible evolution of traditional teaching techniques and is becoming a mature technology. Several commercial suites are available to author multimedia courses either to be distributed in physical form (e.g. on CD or DVD) or to be used on-line. However the application of these suites to the instrumentation and measurement courses and in general to courses that require students to learn the use of real devices is difficult and sometime useless. In this paper, some peculiar aspects of the instrumentation and measurement courses are discussed, focusing on the impact of e-learning techniques in laboratory activities. Practical hints coming from the authors' experience in several years of in-the-field trials are reported and discusse
Assessing Feature Importance for Short-Term Prediction of Electricity Demand in Medium-Voltage Loads
Full text linkThe design of new monitoring systems for intelligent distribution networks often requires both real-time measurements and pseudomeasurements to be processed. The former are obtained from smart meters, phasor measurement units and smart electronic devices, whereas the latter are predicted using appropriate algorithms—with the typical objective of forecasting the behaviour of power loads and generators. However, depending on the technique used for data encoding, the attempt at making predictions over a period of several days may trigger problems related to the high number of features. To contrast this issue, feature importance analysis becomes a tool of primary importance. This article is aimed at illustrating a technique devised to investigate the importance of features on data deemed relevant for predicting the next hour demand of aggregated, medium-voltage electrical loads. The same technique allows us to inspect the hidden layers of multilayer perceptrons entrusted with making the predictions, since, ultimately, the content of any hidden layer can be seen as an alternative encoding of the input data. The possibility of inspecting hidden layers can give wide support to researchers in a number of relevant tasks, including the appraisal of the generalisation capability reached by a multilayer perceptron and the identification of neurons not relevant for the prediction task
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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