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EN
Electromagnetic forces generated by the short circuit current and leakage flux in low- and high-voltage windings of distribution transformers as well as amorphous core transformers will cause the translation, destruction, and explosion of the windings. Thus, the investigation of these forces plays a significant role for researchers and manufacturers. Many authors have recently used the finite element method to analyze electromagnetic forces. In this paper, an analytic model is first developed for magnetic vector potential formulations to compute the electromagnetic forces (i.e., axial and radial forces) acting on the low- and high-voltage windings of an amorphous core transformer. The finite element technique is then presented to validate the results obtained from the analytical model. The developed model is applied to an actual problem.
EN
For voltage-source-converter based high-voltage-direct-current (VSC-HVDC)transmission systems, fault ride-through (FRT) capability is a very important grid requirement in order to enhance its operational availability under an alternating current (AC) gridfault condition. Voltage sags during a short-circuit fault in power transmission lines can leadto fluctuations in the direct current (DC) link voltage of converter systems, and may inducereversed power flow and even trip a VSC-HVDC transmission system. A practical methodis developed in this paper for investigating FRT capability of VSC-HVDC transmissionsystem characteristics during a voltage sag event using experimental results from Smart Grid Laboratory. Symmetrical and asymmetrical voltage sag events with different remaining voltages are applied to an AC grid that lasts with a variable duration. The experimental waveforms of the two converter systems are recorded and analyzed in order to evaluate theFRT capability of VSC-HVDC transmission systems.
EN
This paper proposes an advanced Internet of Things (IoT) system for measuring, monitoring, and recording some power quality (PQ) parameters. The proposed systemis designed and developed for both hardware and software. For the hardware unit, three PZEM-004T modules with non-invasive current transformer (CT) sensors are used tomeasure the PQ parameters and an Arduino WeMos D1 R1 ESP8266 microcontroller isused to receive data from the sensors and send this data to the server via the internet. For the software unit, an algorithm using Matlab software is developed to send measurement datato the ThingSpeak cloud. The proposed system can monitor and analyse the PQ parameters including frequency, root mean square (RMS) voltage, RMS current, active power, and the power factor of a low-voltage load in real-time. These PQ parameters can be stored on theThingSpeak cloud during the monitoring period; hence the standard deviation in statistics of the voltage and frequency is applied to analyse and evaluate PQ at the monitoring point.The experimental tests are carried out on low-voltage networks 380/220 V. The obtained results show that the proposed system can be usefully applied for monitoring and analysing chosen PQ parameters in micro-grid solutions.
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