Calibrating Instrument Transformers with Phasor Measurements

During the life span of an instrument transformers (IT), non-catastrophic and typically undetected problems may degrades the overall performance of the instrumentation system. Synchrophasor provides high resolution synchronized data compared to the Supervisory Control and Data Acquisition (SCADA) systems. In the proposed non-intrusive method, time-series Phasor Measurement Units (PMUs) data are processed using three step approach for real time condition monitoring of IT at the control center. Bad data are filtered or flagged using MLE based ensemble method before applying density-based spatial clustering of applications with noise (DBSCAN) to detect clusters, changing over time within each time window. In the third step, a decision logic diagram is developed using additional data and system information to categorize the observed anomalies into different types of malfunction, failure, event or degradation. The proposed method has been validated using IEEE test system modeled in the Real Time Digital Simulator (RTDS) interfaced with industrial hardware PMU device. Detecting equipment failures at an early stage will result in improved system reliability and reduced maintenance cost. Several test cases demonstrate superiority of the proposed method for detecting incipient failures in the IT, and provides early warning mechanism for preventing full blown faults resulting in major impact on the power grid.

Frequency response and harmonic distortion testing of inductive voltage transformer used for power quality measurements

The knowledge of line parameters is fundamental for building a network model that can become the basis for all the monitoring and management applications. Network line impedances are employed, for instance, for the state estimation or for protection applications in relay setting. The Phasor Measurement Units (PMUs), thanks to the synchronized voltage and current phasor measurements, provide the accurate information that can be used to evaluate the network parameters of the monitored branches. Nevertheless, the impact of instrument transformers (ITs) makes the parameter estimation a hard task. For this reason, in this paper an estimation paradigm is proposed that includes the estimation of both systematic errors (mainly due to ITs) and line parameters. The proposed method, particularly focused on distribution systems, is designed to perform simultaneous estimations across different branches of the network, aiming at exploiting the links between the involved parameters, due to topology and operating conditions. The estimation is based on a sound and detailed model of the uncertainty sources.

State estimator is an important tool for online monitoring, analysis and control of power systems. With the increased use of phasor measurement units in a power grid, utilization of synchro phasor measurements in State Estimation (SE) becomes essential. Conventional State Estimation (CSE) has been done from measurements obtained by Supervisory Control And Data Acquisition (SCADA) systems. Linear State Estimation (LSE) is done using phasor measurements alone. The paper presents a hybrid method called Two Stage State Estimation (TSSE), wherein the states of the system are estimated by incorporating both the SCADA measurements and phasor measurements. Simulations are done on IEEE 14 bus, IEEE 30 bus and IEEE 118 bus systems and results are compared.

This report describes an evaluation of »observer variation« in history taking and examination of patients with abdominal pain. After an initial survey in which the degree of observer variation amongst the present authors fully confirmed previous rather gloomy forecasts, a system of »agreed definitions« was produced, and further studies showed a rapid and considerable fall in the degree of observer variation between the data recorded by the same authors. Finally, experience with a computer-based diagnostic system using the same system of agreed definitions showed the maximum diagnostic error rate due to faulty acquisition of data to be low (4.7°/o in a series of 552 cases). It is suggested as a result of these studies that — at least in respect of abdominal pain — errors in data acquisition by the clinician need not be the prime cause of faulty diagnoses.

This paper presents the assessment of an enhanced line parameter estimation technique for modern distribution networks. The estimation method takes advantage of the use of Phasor Measurement Units or, more in general of synchronized phasor measurements. A comprehensive modeling of the uncertainty of synchronized data permits performing an accurate estimation. The validity of the estimation technique has been tested on a portion of the digital twin of the Forschungszentrum Jülich (FZJ) campus, a self-managed distribution network with more than 100 nodes. Realistic measurement assumptions have been considered by taking into account the accuracy of a measurement chain (instrument transformer and measurement device) for distribution networks. Furthermore, the presence of distributed generation has been also taken into account. The results will show that the parameter estimation in these challenging conditions is successful, and the technique can be applied for the analysis of real distribution networks.

The world's modernization resulted to a sharp rise in the demand for power. Decentralized power generation and the inclusion of renewable energy sources are making power system operation more complex. As a result, power system monitoring and measurement also became more complicated. One of the main disadvantages of power system monitoring is the slower rate of the measurement and monitoring data obtained from the current power system monitoring techniques, such as Supervisory Control and Data Acquisition (SCADA) and Energy Management Systems (EMS), as they only provide a limited amount of information on the parameters of the power system. Therefore, it is necessary to improve the current power system monitoring techniques for gathering data from the power system. Phasor measurements using Intelligent Electronic Devices (IEDs) provide faster data gathering from the power system and more information about the parameters of the power system. In order to determine the phasor values of voltage, current, remaining power system operational parameters frequency, Change of Frequency (COF) and Rate of Change of Frequency (ROCOF), this IED gathers the voltage and current signal data from the power system more quickly and sends it to a software program. By using this software program, very quickly phsors, power system operational parameters are calculated.The calculated phasors gave the live representation of the power system feasible by appending a time tag to each phasor value. This is a crucial requirement for power system monitoring across a large area, leads to massive storage system of phasors and power system paprameters. To store only required and effective data and to avoid routine data storage, new storage method is proposed. This paper presents a phasor calculation technique, synchronized phasor measurements, effective data storage, and identifying of faults in the dynamic state.

A method for improved 4D-computed tomography data acquisition

In the context of modern power systems, the availability of accurate knowledge of line parameters is a requirement to improve any monitoring and control applications. This knowledge is not easy to obtain even in the presence of a monitoring infrastructure of last generation based on Phasor Measurement Units (PMUs). To address this challenge, the paper proposes a method for improving line parameters estimation through the simultaneous estimation of the systematic measurement errors from the instrument transformers. The problem is faced starting from an appropriate modelling of the system, which includes the uncertainties associated with instrument transformers and PMUs. Moreover, the designed algorithm exploits the available constraint equations derived from the network model. The validity of the proposed approach is tested on a portion of the IEEE 14 bus system and confirmed by the presented results.

New accuracy standards are proposed for phase-shifting transformers generally applied in polyphase circuits for var (reactive volt-amperes) measurement. Limiting values of ratio correction factor (RCF) and phase angle defect (PD) are given for three proposed standard accuracy levels, namely, 0.3 per cent, 0.6 per cent, and 1.2 per cent. These levels represent the maximum error in var measurement owing to the phase-shifting transformer. The limiting values appear as circle diagrams. The proposals bring the standards up to the same level of development as those for instrument current and potential transformers.

Wind farms require advanced monitoring systems to increase the reliability of the turbines. A critical component is the gearbox of wind turbines because of its high failure cost and large downtime. Supervisory control and data acquisition and monitoring systems employed in wind turbines generate large amounts of data. This data set must be processed with advanced analytics to become useful information for the reliability of the turbine. The novelty of this paper is based on the adjustment of the wind speed curve versus gearbox temperatures for the analysis of the alarms produced in the gearbox, being the data from the supervisory control and data acquisition and monitoring systems.

A new on-line insulation monitoring system for power transformers, instrument transformers and MOA is developed. For each of the three phase HV apparatus, signal sensing and data acquisition and reduction are done by a micro-computer unit which is installed locally. Data from many substations can be transmitted remotely to an expert diagnosis system. This monitoring system shows a strong interference tolerance. For HV apparatus, the system can monitor the health of the insulation and indicate the evolution of any developing problems in real time.

Remote calibration of instrument transformers seems possible if sufficient certainty in field measurements can be achieved. This opportunity, until now, was only investigated from a theoretical point of view and in this paper, is now further investigated by using real-life synchrophasors. A transmission line is emulated, and voltage and current synchrophasors collected across the transmission line by two different synchrophasor recorders to derive a ratio correction factor for the remote instrument transformers.

In recent years, the electrical substations are experiencing a rapid transition towards a fully digital measurement infrastructure, in terms of data acquisition, storage and processing. The IEC Std 61850-9-2 defines the data format, also known as Sampled Value (SV), to be employed by instrument transformers, merging units, and controller devices. In this scenario, it is reasonable to expect that also Phasor Measurement Units (PMUs) will be directly connected with digital instrument transformers and will be required to process directly the SV data stream. In this paper, we present the design and development of a stand-alone PMU based on digital inputs to be used as reference instrument in the metrological characterization of Intelligent Electrical Devices (IEDs) operating both as PMU and Stand Alone Merging Units (SAMUs). The prototype has been characterized in terms of estimation accuracy and computational requirements, by means of a dedicated IEC Std 61850-9-2 calibration system. The preliminary results prove the potential of SV-based PMUs, but also reveal some implementation bottlenecks that have to be properly addressed before an effective deployment on the field.

The demand for digital oil field solutions in artificially lifted wells is higher than ever, especially for wells producing heavy oil with high sand content and gas. A real-time supervisory control and data acquisition solution has been applied in a large-scale thermal pilot for 28 instrumented sucker rod pumping wells in North Kuwait. This paper focuses on the advantages of real-time data acquisition for identifying production-optimization candidates, improving pump performance, and minimizing down time when using intelligent alarms and an analysis engine. Real-time surveillance provided a huge amount of information to be analyzed and discussed by well surveillance and field development teams to determine required actions based on individual well performance. Controller alarms and intelligent configurable alarms in one screen enabled early detection of unexpected/unwanted well behavior, re-investigating well potential, and taking necessary actions. The challenge was to handle heavy oil, sand, and gas production, maintain all wells at optimum running conditions before and after steam injections, and take into consideration the effect that injections would have on nearby wells. Recording in the database a "tracking item" for each well event enabled review and evaluation of the wells and creation of optimization reports. The daily, 24-hour surveillance of the wells resulted in observing common problems/issues on almost all wells and other individual issues for specific wells. The following are examples of problems identified in early stages: Detected wells with gas interference before they reached gas lockDetected wells with high flowline pressure before flowline blockage resulted from sand productionDetected wells with standing valve and/or traveling valve leak—resulting from sand production—before the pump stuck The availability of such a supervisory control and data acquisition (SCADA) system helped in guiding the operations team to further investigate only specific items from the field side to confirm the findings. The ability to remotely control the wells and remotely change configuration of the variable speed drive parameters enabled instant implementation and continuous production optimization. The powerful SCADA solution enabled creating short- and long-term plans and monitoring the behavior of wells while the implementation phase was executed. For the first time in South Ratqa in North Kuwait, the smart field approach was implemented in a thermal pilot using sucker rod pumps; and the results will be used as a reference for the upcoming projects in this area. Real-time monitoring and data storage in a single database with an analysis engine provided fully automated surveillance and the capability of remotely controlling and applying required actions for production optimization.