Real-time wireless, contactless and coreless monitoring of the current distribution in substation conductors for fault diagnosis

Parallel conductors are found in electrical transmission and distribution systems including large ampacity feeders or loads. However, current unbalance often occurs, especially in alternating current systems. This non-regular current distribution causes overheating and premature ageing, facilitating the occurrence of failures. Therefore, a fault diagnosis system is a must, which can be performed by monitoring in real-time the individual currents flowing through the conductors. In this paper a setup including three parallel aluminum conductors of large cross section, a spacer and two terminal substation connectors is analyzed. A real-time, wireless, coreless and contactless system based on three low cost Hall effect sensors is proposed, which is also easy to install. Experimental results, which include fourteen cases, comprising thirteen fault modes and a well installed set, prove the suitability and potential of the proposed approach, since it allows a correct real-time detection of all analyzed faulty conditions as well as the detection of currents exceeding the thermal rating of the conductors.Peer ReviewedPostprint (author's final draft

Development of an open-architecture temperature data logger for hydro-distillation agarwood oil extractor

Microcontroller based data logger system recently emerged as a powerful, flexible and cost-effective measurement solution to many innovative field applications in environmental monitoring, agriculture and solar energy. Real-time temperature is vital to provide discrete knowledge in the process of distillation as it involves mixture boiling, evaporation and condensation at the difference in liquid phases. The development of a data logger namely OCTATherm for use in the Agarwood extraction industry is realized by designing an electronic enclosure to protect an Arduino-based microcontroller system that can acquire eight (8) thermocouples readings for monitoring the hydro-distillation process. The accuracy and reliability of the data logger have been evaluated by assessing the hydro-distillation (HD) process on a laboratory scale by comparing its performance to the commercial data logger (HOBO UX120). Finally, the assessment in the industry with multi-boiler operate simultaneously shows that real-time monitoring of the temperature measurements at critical points of the conventional HD system can improve the yield of the extracted Agarwood essential oil by three (3) times higher from 0.027% to 0.101%. The implementation of real-time thermal management technology in the HD system in the Agarwood essential oil production industry is therefore of great importance. This developed data logger is significant to produce a real-time data acquisition and monitoring platform of temperature measurement, which aims to facilitate agriculture industry process monitoring as well as academic research purpose in another area. The open-architecture based system design is also highlighted in which provides future upgrades of expansion and extension features of the data logger

Development of the future generation of smart high voltage connectors and related components for substations, with energy autonomy and wireless data transmission capability

The increased dependency on electricity of modern society, makes reliability of power transmission systems a key point. This goal can be achieved by continuously monitoring power grid parameters, so possible failure modes can be predicted beforehand. It can be done using existing Information and Communication Technologies (ICT) and Internet of Things (10T) technologies that include instrumentation and wireless communication systems, thus forming a wireless sensor network (WSN). Electrical connectors are among the most critical parts of any electrical system and hence, they can act as nodes of such WSN. Therefore, the fundamental objective of this thesis is the design, development and experimental validation of a self-powered IOT solution for real-time monitoring of the health status of a high-voltage substation connector and related components of the electrical substation. This new family of power connectors is called SmartConnector and incorporates a thermal energy harvesting system powering a microcontroller that controls a transmitter and several electronic sensors to measure the temperature, current and the electrical contact resistance (ECR) of the connector. These measurements are sent remotely via a Bluetooth 5 wireless communication module to a local gateway, which further transfers the measured data to a database server for storage as well as further analysis and visualization. By this way, after suitable data processing, the health status of the connector can be available in real-time, allowing different appealing functions, such as assessing the correct installation of the connector, the current health status or its remaining useful life (RUL) in real-time. The same principal can also be used for other components of substation like spacers, insulators, conductors, etc. Hence, to prove universality of this novel approach, a similar strategy is applied to a spacer which is capable of measuring uneven current distribution in three closely placed conductors. This novel IOT device is called as SmartSpacer. Care has to be taken that this technical and scientific development has to be compatible with existing substation bus bars and conductors, and especially to be compatible with the high operating voltages, i.e., from tens to hundreds of kilo-Volts (kV), and with currents in the order of some kilo-pm peres (kA). Although some electrical utilities and manufacturers have progressed in the development of such technologies, including smart meters and smart sensors, electrical device manufacturers such as of substation connectors manufacturers have not yet undertaken the technological advancement required for the development of such a new family of smart components involved in power transmission, which are designed to meet the future needs.La mayor dependencia de la electricidad de la sociedad moderna hace que la fiabilidad de los sistemas de transmisión de energía sea un punto clave. Este objetivo se puede lograr mediante la supervisión continua de los parámetros de la red eléctrica, por lo que los posibles modos de fallo se pueden predecir de antemano. Se puede hacer utilizando las tecnologías existentes de Tecnologías de la Información y la Comunicación (1CT) e Internet de las cosas (lo T) que incluyen sistemas de instrumentación y comunicación inalámbrica, formando así una red de sensores inalámbricos (WSN). Los conectores eléctricos se encuentran entre las partes más críticas de cualquier sistema eléctrico y, por lo tanto, pueden actuar como nodos de dicho VVSN. Por lo tanto, el objetivo fundamental de esta tesis es el diseño, desarrollo y validación experimental de una solución IOT autoalimentada para la supervisión en tiempo real del estado de salud de un conector de subestación de alta tensión y componentes relacionados de la subestación eléctrica. Esta nueva familia de conectores de alimentación se llama SmartConnector e incorpora un sistema de recolección de energía térmica que alimenta un microcontrolador que controla un transmisor y varios sensores electrónicos para medir la temperatura, la corriente y la resistencia del contacto eléctrico (ECR) del conector. Esta nueva familia de conectores de alimentación se llama SmartConnector e incorpora un sistema de recolección de energía térmica que alimenta un microcontrolador que controla un transmisor y varios sensores electrónicos para medir la temperatura, la corriente y la resistencia al contacto eléctrico (ECR) del conector. De esta manera, después del procesamiento de datos adecuado, el estado de salud del conector puede estar disponible en tiempo real, permitiendo diferentes funciones atractivas, como evaluar la correcta instalación del conector, el estado de salud actual o su vida útil restante (RUL) en tiempo real. El mismo principio también se puede utilizar para otros componentes de la subestación como espaciadores, aislantes, conductores, etc. Por lo tanto, para demostrar la universalidad de este enfoque novedoso, se aplica una estrategia similar a un espaciador, que es capaz de medir la distribución de corriente desigual en tres conductores estrechamente situados. Hay que tener cuidado de que este desarrollo técnico y científico tenga que sea compatible con las barras y "busbars" de subestación existentes, y sobre todo para ser compatible con las altas tensiones de funcionamiento, es decir, de decenas a cientos de kilovoltios (kV), y con corrientes en el orden de algunos kilo-Amperes (kA). Aunque algunas empresas eléctricas y fabricantes han progresado en el desarrollo de este tipo de tecnologías, incluidos medidores inteligentes y sensores inteligentes, los fabricantes de dispositivos eléctricos, como los fabricantes de conectores de subestación, aún no han emprendido el avance tecnológico necesario para el desarrollo de una nueva familia de componentes intel

Fault Detection and Performance Analysis of Photovoltaic Installations

The cumulative global photovoltaic (PV) capacity has been growing exponentially around the world, especially due to the installation of grid connected photovoltaic (GCPV) plants. Fault detection and analysis are important for the efficiency, reliability and safety of solar photovoltaic (PV) systems. Even This thesis reports the results of the research work conducted to invent novel fault detection algorithms and evaluate their deployment in multiple existing PV installation, and empirically validate their performance. A major contribution of this thesis is the development of PV fault detection algorithms based on two indicators named power ratio (PR) and voltage ratio (VR). Both ratios are used to identify the type of the fault that occurs in the PV modules, in PV string, and/or in maximum power point tracking (MPPT) unit. Three AI based algorithms were also used to detect faults in PV modules. The first algorithm uses six regions of the power and voltage ratio in order to detect faults in PV systems. The average detection accuracy for the algorithm is equal to 94.74%. However, Mamdani Fuzzy Logic system has been used to enhance the occurrence of fault detection in the PV installations which resulted in an increase to 99.12%. The second proposed PV fault detection algorithm detects defective bypass diodes in PV modules using Mamdani Fuzzy Logic. Whereas, a third PV detection algorithm is based on artificial neural networks (ANN) networks. Four different ANN models have been modelled, which can be classified as follows: - 2 inputs, 5 outputs using 1 hidden layer - 2 inputs, 5 outputs using 2 hidden layers - 2 inputs, 9 outputs using 1 hidden layer - 2 inputs, 9 outputs using 2 hidden layers The output results for the last ANN network had the highest overall fault detection accuracy of 92.1%. In this thesis, the development of two hot spot mitigation techniques used in PV modules will be discussed. These techniques are capable of enhancing the output power of PV modules which are affected by hot spots and partial shading conditions. The detection of hot spots was captured using i5 FLIR thermal imaging camera. Finally the thesis describes the impact of PV micro cracks on the output power of PV modules. A new statistical analysis approach using T-test and F-test was used to identify the significance impact of the cracks on the output power performance of the PV modules. This is developed using LabVIEW software