Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15

Geomagnetic Disturbances (GMD) Impacts on Protection Systems

This paper provides background and historical events of Geomagnetic Disturbances (GMD), and reviews GMD impacts on power systems equipment, and associated protection and control systems, mitigating measures, and Geomagnetic Induced Current (GIC) monitoring methods. This paper is a summary of the IEEE PES-TR72 report, titled, GMD Impacts on Protection Systems, prepared by the K17 Working Group of the IEEE Power System Relaying and Control committee

Protection Scheme based on Artificial Neural Network for Fault Detection and Classification in Low Voltage PV-Based DC Microgrid

With the expansion of the DC distribution market, protection, and operational concerns for Direct Current (DC) Microgrids have increased. Different systems have been investigated for detecting, finding, and isolating defects utilising a variety of protective mechanisms. It might be difficult to locate high-resistance faults and shorted DC faults on low-voltage DC (LVDC) microgrids. Therefore, in this study, a Field Transform Technique like Short-Time Fourier Transform (STFT) is proposed for detecting the Fault Current (FC). This method detects the faults Pole-ground (PG), pole-pole (PP), and Arc fault are the major fault types in the DC network with PG fault as the most common and less severe. One of the difficulties the DC system faces in the incidence of a malfunction is the protection of essential converters. During this fault, the diodes, being the most vulnerable component of the system, may encounter a substantial surge in current, which can potentially cause damage if the current surpasses double their specified capacity for withstanding. After the Fault detection (FD), a Taguchi-based ANN is presented to classify the detected faults. This method effectively classifies PV-based faults. Then, to safeguard the FC, the Improved Self-Adaptive Solid State Circuit Breaker (I-SSCB) is introduced. It safeguards the FC in the low-voltage PV-based DC microgrid (DCMG) and restricts FC in the DCMG. The suggested approach is evaluated using the Matlab software and the proposed method produces 400A current and 100 KW power during the PV temperature of 25°C. The output current of the ANN is then 1A for a duration of 0.3 to 0.4 seconds. The fault voltage and FC produced in this proposed work are 1900V and 1950A. Therefore, the proposed work's current and voltage values are 21 KV and 0.35 I. Therefore, the proposed method produces more power and limits the FC in the LV-DCMG. In future studies, the improved or modified neural network or machine learning (ML)-based techniques can be utilized which may improve the protection scheme of the work

Characterization of causes of signal phase and frequency instability Final report

Characteristic instabilities in phase and frequency errors of reference oscillator

Firmware design of a portable medical device to measure the quadriceps muscle group after a total knee arthroplasty by EMG, LBIA and clinical score methods

El objetivo de este proyecto es el diseño del firmware de un dispositivo médico portátil para mediciones de EMG y LBIA, que se utilizará para la evaluación de pacientes de artroplastia total de rodilla, para estudiar la progresión de diferentes prótesis de rodilla (Medial-Pivot y Ultra-Congruente). En la tesis, se expone el conocimiento actual de los estudios y aplicaciones de EMG y LBIA, junto con los dispositivos comerciales utilizados actualmente. Además, se han estudiado e implementado las diferentes técnicas de filtrado y procesamiento digital para señales de EMG y LBIAs. Adicionalmente, se ha realizado un estudio estadístico preliminar con datos LBIA de 12 pacientes de artroplastia total de rodilla. El diseño del firmware de esta tesis incluye: los procesos de adquisición de datos con el uso de diferentes ADCs (Conversor Analógico a Digital) (de la propia placa y externos, utilizando la interfaz SPI) y un DAC (Conversor Digital a Analógico), el correspondiente procesamiento de la señal y la extracción de sus características, la comunicación con un dispositivo externo utilizando un módulo BLE externo con interfaz UART, el proceso de encriptación de los datos médicos, la funcionalidad de manejo de errores y la aproximación del nivel de batería. En esta tesis, todos los flujos de trabajo de los procesos se exponen y explican mediante diagramas de flujo, mientras que se justifica cada cálculo y configuración. Además, todo el código correspondiente se ha programado en lenguaje C y se expone en los anexos. También se ha revisado la normativa aplicable y se ha analizado tanto el impacto ambiental como el coste económico del producto. Por último, se proponen mejoras para futuros trabajos.The aim of this project is the firmware design for a portable medical device for EMG and LBIA measurements which will be used for the assessment of total knee arthroplasty patients to study the progression of different knee prostheses (Medial-Pivot and Ultra-Congruent). For its realization, the state of the art of the EMG and LBIA studies and applications are exposed, along with the currently used medical devices. In addition, the different digital filtering and processing techniques for these studies have been studied and implemented. Furthermore, a preliminary statistical study has been performed with LBIA data from 12 patients with total knee arthroplasty. The firmware design of this thesis includes: the acquiring data processes with the use of different ADCs (from the actual board and external, using the SPI interface) and a DAC, the corresponding signal processing and feature abstraction, the communication with an external device using an external BLE module with UART interface, the medical data encrypting process, the error handling functionality, and the battery level approximation. In this work, all the process workflows are exposed and explained using flowcharts, while every calculation and configuration is justified. In addition, all the corresponding code has been programmed using C language and exposed in the Annexes. Moreover, the applicable regulation has been reviewed, and both the environmental impact and economic cost of the product have been analyzed. Finally, improvements are proposed for future work.L'objectiu d'aquest projecte és el disseny del microprogramari d'un dispositiu mèdic portàtil per a mesures d'EMG i LBIA. L’aparell mèdic s'utilitzarà per a l'avaluació de pacients d'artroplàstia total de genoll per estudiar la progressió de dues pròtesis de genoll (Medial-Pivot i Ultra- Congruent). En el treball, s'exposa el coneixement actual dels estudis i aplicacions d'EMG i LBIA, juntament amb els dispositius comercials utilitzats actualment. A més, s'han estudiat i implementat les diferents tècniques de filtrat i processament digital dels senyals de EMG i LBIA. Addicionalment, s'ha fet un estudi estadístic preliminar amb dades de LBIA de 12 pacients amb artroplàstia total de genoll. El disseny del microprogramari d'aquesta tesi inclou: els processos d'adquisició de dades fent ús de diferents ADCs (de la pròpia placa i externs, utilitzant la interfície SPI) i un DAC, el processament dels senyals i l'abstracció de les seves característiques, la comunicació amb un dispositiu extern utilitzant un mòdul BLE extern amb interfície UART, el procés d'encriptació de les dades mèdiques, la funcionalitat de l’avaluació d'errors i l'aproximació del nivell de bateria. En aquest treball, totes les funcionalitats del dispositiu s'exposen i s'expliquen mitjançant diagrames de flux i es justifiquen els càlculs i configuracions corresponents. Tot el codi desenvolupat s'ha programat en llenguatge C i s'exposa als annexos. A més, s'ha revisat la normativa aplicable i s'ha analitzat tant l'impacte ambiental com el cost econòmic de l’aparell. Finalment, es proposen millores per a futurs desenvolupaments

Novel Approaches for Nondestructive Testing and Evaluation

Nondestructive testing and evaluation (NDT&E) is one of the most important techniques for determining the quality and safety of materials, components, devices, and structures. NDT&E technologies include ultrasonic testing (UT), magnetic particle testing (MT), magnetic flux leakage testing (MFLT), eddy current testing (ECT), radiation testing (RT), penetrant testing (PT), and visual testing (VT), and these are widely used throughout the modern industry. However, some NDT processes, such as those for cleaning specimens and removing paint, cause environmental pollution and must only be considered in limited environments (time, space, and sensor selection). Thus, NDT&E is classified as a typical 3D (dirty, dangerous, and difficult) job. In addition, NDT operators judge the presence of damage based on experience and subjective judgment, so in some cases, a flaw may not be detected during the test. Therefore, to obtain clearer test results, a means for the operator to determine flaws more easily should be provided. In addition, the test results should be organized systemically in order to identify the cause of the abnormality in the test specimen and to identify the progress of the damage quantitatively

Online disturbance prediction for enhanced availability in smart grids

A gradual move in the electric power industry towards Smart Grids brings new challenges to the system's efficiency and dependability. With a growing complexity and massive introduction of renewable generation, particularly at the distribution level, the number of faults and, consequently, disturbances (errors and failures) is expected to increase significantly. This threatens to compromise grid's availability as traditional, reactive management approaches may soon become insufficient. On the other hand, with grids' digitalization, real-time status data are becoming available. These data may be used to develop advanced management and control methods for a sustainable, more efficient and more dependable grid. A proactive management approach, based on the use of real-time data for predicting near-future disturbances and acting in their anticipation, has already been identified by the Smart Grid community as one of the main pillars of dependability of the future grid. The work presented in this dissertation focuses on predicting disturbances in Active Distributions Networks (ADNs) that are a part of the Smart Grid that evolves the most. These are distribution networks with high share of (renewable) distributed generation and with systems in place for real-time monitoring and control. Our main goal is to develop a methodology for proactive network management, in a sense of proactive mitigation of disturbances, and to design and implement a method for their prediction. We focus on predicting voltage sags as they are identified as one of the most frequent and severe disturbances in distribution networks. We address Smart Grid dependability in a holistic manner by considering its cyber and physical aspects. As a result, we identify Smart Grid dependability properties and develop a taxonomy of faults that contribute to better understanding of the overall dependability of the future grid. As the process of grid's digitization is still ongoing there is a general problem of a lack of data on the grid's status and especially disturbance-related data. These data are necessary to design an accurate disturbance predictor. To overcome this obstacle we introduce a concept of fault injection to simulation of power systems. We develop a framework to simulate a behavior of distribution networks in the presence of faults, and fluctuating generation and load that, alone or combined, may cause disturbances. With the framework we generate a large set of data that we use to develop and evaluate a voltage-sag disturbance predictor. To quantify how prediction and proactive mitigation of disturbances enhance availability we create an availability model of a proactive management. The model is generic and may be applied to evaluate the effect of proactive management on availability in other types of systems, and adapted for quantifying other types of properties as well. Also, we design a metric and a method for optimizing failure prediction to maximize availability with proactive approach. In our conclusion, the level of availability improvement with proactive approach is comparable to the one when using high-reliability and costly components. Following the results of the case study conducted for a 14-bus ADN, grid's availability may be improved by up to an order of magnitude if disturbances are managed proactively instead of reactively. The main results and contributions may be summarized as follows: (i) Taxonomy of faults in Smart Grid has been developed; (ii) Methodology and methods for proactive management of disturbances have been proposed; (iii) Model to quantify availability with proactive management has been developed; (iv) Simulation and fault-injection framework has been designed and implemented to generate disturbance-related data; (v) In the scope of a case study, a voltage-sag predictor, based on machine- learning classification algorithms, has been designed and the effect of proactive disturbance management on downtime and availability has been quantified

Lecture Script: "EMI Risk Management"

Content of the lecture: Fundamentals and methods of risk analysis; Basic design and technology of IEMI sources (e.g., VIRCATOR, Magnetron, Klystron, …); Modelling of IEMI threat scenarios; EMI effects on electric systems; Protective measure; Discussion and assessment of the risk for critical infrastructures; Case studies on a generic infrastructur