Design and Implementation of New Measurement Models and Procedures for Characterization and Diagnosis of Electrical Assets

The measurement is an essential procedure in power networks for both network stability, and diagnosis purposes. This work is an effort to confront the challenges in power networks using metrological approach. In this work three different research projects are carried out on Medium Voltage underground cable joints diagnosis, inductive Current Transformers modeling, and frequency modeling of the Low power Voltage Transformer as an example of measurement units in power networks. For the cable joints, the causes and effects of Loss Factor have been analyzed, while for the inductive current transformers a measurement model is developed for prediction of the ratio and phase error. Moreover, a frequency modeling approach has been introduced and tested on low power voltage transformers. The performance of the model on prediction of the low power voltage transformer output has been simulated and validated by experimental tests performed in the lab

Design and characterization of a system for loss factor measurement in MV underground cable joints under temperature variation conditions

Cable joints are considered to be the weakest components of the MV cable network, being the ones with the highest failure rate. Furthermore, from statistical analysis of different cable network failure data, a noticeably increase in cable joint breakdowns has been showed during summer months. The request for Distribution System Operators to avoid line outages as much as possible indicates a significant need for non-invasive diagnostic technologies able to monitor the health condition of MV cable junctions. Moreover, a better knowledge is required on the main causes of the detected increase in cable joint failure rate, in which temperature seems to play an important role. The present master thesis consists in the design and complete characterization of a simple and cheap laboratory setup for loss factor measurements on cable joints. Using the developed circuit, tan delta measurements are performed on four thermally cycled cable joint samples and the trend in relation to temperature variations has been investigated and widely discussed. In particular, it has been found that the loss factor of cable joint samples decreases considerably when temperature rises and vice-versa. From result analysis, some hypotheses have been made trying to explain this particular behavior of the loss factor versus temperature. In particular, temperature variations seem to cause expansions and contractions of the different dielectric layers present in cable joint, giving rise to pressure fluctuations at the interface between them. Consequently, variations in the breakdown strength of the joint insulation system and in the amount of conduction losses are expected to happen. These conclusions must be demonstrated by future studies and tests on cable junctions. It is worth saying that a conference proceeding has been published from the present work, and, currently, a journal paper is submitted, waiting to be approved

Effects of thermal cycles on interfacial pressure in MV cable joints

The use of medium voltage cable joints is mandatory when dealing with power cable faults and the installation of new lines. However, such an accessory is among the top causes of faults among the grid. To this purpose, one of the quantities monitored to understand the causes of such faults is the interfacial pressure between the insulating layers of the cable joint. In this work, the interfacial pressure between Cross-linked polyethylene (XLPE) and silicon rubber has been evaluated when the cable joint experiences thermal cycles. From the results, the pressure variation caused by the thermal cycles is demonstrated. Such a phenomenon may be connected to the generation of voids and weak spots that accelerate cable joint ageing. Therefore, proper comments and conclusions are drawn

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

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

Manutenzione predittiva dei giunti mediante tecnologie di Intelligenza Artificiale per la prevenzione dei guasti nelle reti di distribuzione in MT

Lo scopo dell’elaborato è quello di valutare una prima applicazione di intelligenza artificiale per svolgere manutenzione predittiva sui giunti installati nella rete di distribuzione, al fine di prevenirne i guasti. L’estensione delle reti in cavo è infatti in costante aumento per supportare lo sviluppo della rete elettrica e, per l’installazione di nuove linee o nella manutenzione di cavi, si fa uso di giunti, spesso soggetti a guasti e di difficile manutenzione. Risulta quindi importante svolgere manutenzione predittiva su questi componenti, al fine di prevenirne i guasti ed ottenere un risparmio in termini di tempo e denaro. A seguito un’attenta analisi della struttura dei giunti, dei loro modi di guasto e dei parametri caratteristici, si è proceduto alla generazione sintetica di un dataset contenente misure sui giunti e, sulla base di specifici criteri applicati a questi valori, l’informazione sulla presenza o sull’assenza di un guasto. Il dataset è stato poi utilizzato per la fase di apprendimento e di test di sei algoritmi di machine learning, selezionati a partire da considerazioni sullo stato dell’arte, valutato tramite una Revisione Sistematica della Letteratura (SLR). I risultati così ottenuti sono stati analizzati tramite specifiche metriche e da questo caso di studio sono emerse le elevate potenzialità delle tecnologie di intelligenza artificiale ai fini della prevenzione dei guasti nelle reti di distribuzione, soprattutto se considerata la semplicità implementativa degli algoritmi

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

DOWNHOLE RF COMMUNICATION: CHARACTERIZATION AND MODELING OF WAVEGUIDE PROPAGATION IN A FLUID-FILLED DRILL PIPE

Current technologies for downhole communication in oil and gas drilling applications are severely limited in data rate and latency. This work proposes that a system based upon guided wave propagation could be designed to utilize a wireless, radio frequency (RF) signal to yield tens of megabits per second of data transfer. To determine the feasibility of the proposed system, a test setup was built to measure attenuation of RF signals transmitted through a pipe filled with various drilling fluids. A finite element analysis model was also built to further investigate waveguide propagation of electromagnetic signals in a fluid filled pipe. The measurement setup was validated using fluids of known dielectric properties. A number of a drilling base fluids and oil-based fluids were measured and their dielectric properties calculated. The feasibility of the proposed communication system is not promising for liquid based fluids. However, there is significant potential in an air-based system

Suspension systems for ground testing large space structures

A research program is documented for the development of improved suspension techniques for ground vibration testing of large, flexible space structures. The suspension system must support the weight of the structure and simultaneously allow simulation of the unconstrained rigid-body movement as in the space environment. Exploratory analytical and experimental studies were conducted for suspension systems designed to provide minimum vertical, horizontal, and rotational degrees of freedom. The effects of active feedback control added to the passive system were also investigated. An experimental suspension apparatus was designed, fabricated, and tested. This test apparatus included a zero spring rate mechanism (ZSRM) designed to support a range of weights from 50 to 300 lbs and provide vertical suspension mode frequencies less than 0.1 Hz. The lateral suspension consisted of a pendulum suspended from a moving cart (linear bearing) which served to increase the effective length of the pendulum. The torsion suspension concept involved dual pendulum cables attached from above to a pivoting support (bicycle wheel). A simple test structure having variable weight and stiffness characteristics was used to simulate the vibration characteristics of a large space structure. The suspension hardware for the individual degrees of freedom was analyzed and tested separately and then combined to achieve a 3 degree of freedom suspension system. Results from the exploratory studies should provide useful guidelines for the development of future suspension systems for ground vibration testing of large space structures