Smart characterization of rogowski coils by using a synthetized signal

With the spread of new Low-Power Instrument Transformers (LPITs), it is fundamental to provide models and characterization procedures to estimate and even predict the LPITs\u2019 behavior. In fact, distribution system operators and designers of network models are looking for all forms of information which may help the management and the control of power networks. For this purpose, the paper wants to contribute to the scientific community presenting a smart characterization procedure which easily provides sufficient information to predict the output signal of a Low-Power Current Transformer (LPCT), the Rogowski coil. The presented procedure is based on a synthetized signal applied to the Rogowski coil. Afterwards, the validity of the procedure is assessed within the Matlab environment and then by applying it on three off-the-shelf Rogowski coils. Simulations and experimental tests and results involving a variety of distorted signals in the power quality frequency range and by adopting a quite simple measurement setup demonstrated the effectiveness and the capability of the procedure to correctly estimate the output of the tested device

A General Easy-to-use Expression for Uncertainty Evaluation in Residual Voltage Measurement

The paper addresses one of the new and most important issues arising when Low Power Voltage Transformers (LPVTs) are used in power network substations for evaluating, among others, the residual voltage measurement. Conversely to open-triangle inductive instrument transformers, the use of phase voltage transformers for measuring the residual voltage gets challenging due to the very high accuracy required for the three LPVTs. In the paper, a general expression to estimate the residual voltage measurement uncertainty, starting from the LPVTs accuracy, is presented. The effectiveness of the proposed approach is then confirmed with both Monte Carlo simulations and actual measurements on a general three-phase system

Uncertainty analysis of a test bed for calibrating voltage transformers vs.Temperature

The paper addresses the evaluation of the uncertainty sources of a test bed system for calibrating voltage transformers vs. temperature. In particular, the Monte Carlo method has been applied in order to evaluate the effects of the uncertainty sources in two different conditions: by using the nominal accuracy specifications of the elements which compose the setup, or by exploiting the results of their metrological characterization. In addition, the influence of random effects on the system accuracy has been quantified and evaluated. From the results, it emerges that the choice of the uncertainty evaluation method affects the overall study. As a matter of fact, the use of a metrological characterization or of accuracy specifications provided by the manufacturers provides respectively an accuracy of 0.1 and 0.5 for the overall measurement setup

Re-evaluation of the Lagrangian particle modelling system on an experimental campaign in complex terrain

Slovenian legislation for industrial air pollution control requires efficient modelling systems for small domains over complex topography. To determine the performance and efficiency of the Lagrangian particle modelling system used for this purpose a study was made where a general purpose modelling system designed for local-scale areas was used. The main goal of the study was to evaluate a modelling system of this kind using an operational configuration of both input data and model parameters, choosing a testing period with very complex dispersion conditions. This severe check could help to better understand the general quality that a model can achieve in these conditions giving some idea on how to better evaluate and use some results that seem to be very negative simply looking at some statistical parameter. Data from a three-week experimental campaign performed around the ˇSoˇstanj thermal power plant during the spring of 1991 was used (analyzed) for evaluation. The database covers very high ambient concentrations (due to the absence of desulphurisation plants) over complex terrain. The simulation was performed for the full duration of the campaign and a particular situation during the 1st and the 2nd of April 1991 was used as an example to outline the model behaviour in complex conditions. During this selected sub-period measurements revealed that (measured) wind speeds were very low, wind changed course in all directions rapidly and consequently the plume spread in all directions. A comparison between measured and reconstructed SO2 concentrations was made at the positions of several automatic air quality measuring stations located around the thermal power plant. Standard statistical indexes to evaluate model performances are instead computed at the same positions for the entire period of the experimental campaign. Overall the reconstructed SO2 concentrations were underestimated relative to the measured ones, but all direct air pollution events were reconstructed. Some weaknesses of the model in the correct reconstruction of peak events are explained and a way to better describe them and to enhance statistical indexes is proposed

Low-Power Instrument Transformers and Energy Meters: Opportunities and Obstacles

Low-Power Instrument Transformers (LPITs) are becoming the preferred measurement device in the medium voltage (MV) distribution network (DN). They have several benefits compared to legacy solutions. However, the adoption of LPITs results in the need for adapting the grid and its assets to accept them. One practical example is using LPITs as the current and voltage source for energy meters (EMs), which are also used for billing purposes. The resulting measurement chain introduces several metrological challenges that must be studied and investigated. Therefore, in this work, the scenarios of LPITs and energy meters are introduced along with the latest relevant international standards. Afterwards, the opportunities and obstacles due to the implementation of the LPIT plus energy meter measurement chain are discussed. The discussion focuses on metrological requirements, accuracy evaluation, target uncertainty, and influence quantities affecting the performance of the devices

Comparison of Algorithms for the AI-Based Fault Diagnostic of Cable Joints in MV Networks

Abstract Electrical utilities and system operators (SOs) are constantly looking for solutions to problems in the management and control of the power network. For this purpose, SOs are exploring new research fields, which might bring contributions to the power system environment. A clear example is the field of computer science, within which artificial intelligence (AI) has been developed and is being applied to many fields. In power systems, AI could support the fault prediction of cable joints. Despite the availability of many legacy methods described in the literature, fault prediction is still critical, and it needs new solutions. For this purpose, in this paper, the authors made a further step in the evaluation of machine learning methods (ML) for cable joint health assessment. Six ML algorithms have been compared and assessed on a consolidated test scenario. It simulates a distributed measurement system which collects measurements from medium-voltage (MV) cable joints. Typical metrics have been applied to compare the performance of the algorithms. The analysis is then completed considering the actual in-field conditions and the SOs’ requirements. The results demonstrate: (i) the pros and cons of each algorithm; (ii) the best-performing algorithm; (iii) the possible benefits from the implementation of ML algorithms

On the long-period accuracy behavior of inductive and low-power instrument transformers

The accuracy evaluation of instrument transformers is always a key task when proper control and management of the power network is required. In particular, accuracy becomes a critical aspect when the grid or the instrumentation itself is operating at conditions different from the rated ones. However, before focusing on the above non-rated conditions, it is important to fully understand the instrument transformer behavior at rated conditions. To this end, this work analyzed the accuracy behavior of legacy, inductive, and low-power voltage transformers over long periods of time. The aim was to find patterns and correlations that may be of help during the modelling or the output prediction of voltage transformers. From the results, the main differences between low-power and inductive voltage transformers were pointed out and described in detail

Accuracy Type Test for Rogowski Coils Subjected to Distorted Signals, Temperature, Humidity, and Position Variations

Low-Power Instrument Transformers (LPITs) are becoming the first choice for distributed measurement systems for medium voltage networks. However, there are still a lot of challenges related to their operation. Such challenges include their accuracy variation when several influence quantities are acting on them. Among the most significant influence quantities are temperature, electromagnetic field, humidity, etc. Another aspect that increases the importance of studying the LPITs’ accuracy behavior is that, once installed, they cannot be calibrated for several years; hence, one cannot compensate for in-field conditions. Hence, this work aims at introducing a simple type test for a specific LPIT, the Rogowski coil. First, an experimental setup to assess the effect of temperature, humidity, and positioning on the power quality accuracy performance of the Rogowski coil is described. Second, from the results and the experience of the authors it has been possible to design a specific type test. The test has the aim of finding the limits of the accuracy variations of a single Rogowski coil. Afterwards, such limits can be used to compensate for the in-field measurements, obtaining an overall higher accuracy. The results of this work may contribute to the alwaysevolving standardization work on LPITs

Modeling Stray Capacitances of High-Voltage Capacitive Dividers for Conventional Measurement Setups

Stray capacitances (SCs) are a serious issue in high-voltage (HV) applications. Their presence can alter the circuit or the operation of a device, resulting in wrong or even disastrous consequences. To this purpose, in this work, we describe the modeling of SCs in HV capacitive dividers. Such modeling does not rely on finite element analysis or complicated geometries; instead, it starts from an equivalent circuit of a conventional measurement setup described by the standard IEC 61869-11. Once the equivalent model including the SCs is found, closed expressions of the SCs are derived starting from the ratio error definition. Afterwards, they are validated in a simulation environment by implementing various circuit configurations. The results demonstrate the expressions applicability and effectiveness; hence, thanks to their simplicity, they can be implemented by system operators, researchers, and manufacturers avoiding the use of complicated methods and technologies

An intercomparison of two turbulence closure schemes and four parameterizations for stochastic dispersion models

Two Lagrangian particle models, developed by Luhar and Britter (Atmos. Environ., 23 (1989) 1191) and Weil (J. Atmos. Sci., 47 (1990) 501), satisfying the “well-mixed” condition as prescribed by Thomson (J. Fluid. Mech., 180 (1987) 529), are compared. They differ in the closure scheme used in calculating the probability density function of the random forcing in a convective boundary layer. Four different turbulent parameterizations were used as input to both models. Their performances are evaluated against one of the well-known Willis and Deardorff water tank experiments (Atmos. Environ., 12 (1978) 1305). Predicted and measured ground-level concentrations (g.l.c.), maximum g.l.c. distance, mean plume height and plume vertical spread are presented and discussed