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Faculty of Engineering and Built Environment

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Subject: search.filters.subject.Electric fault location

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    Controlled Switching of 11 kV vacuum circuit breaker for fault interruption
    (2022-09-29) Goolam Hoosen, Nadeem; Ojo, Evans Eshiemogie; Ijumba, Nelson M.
    Fault currents are identified as the reason for the poor quality of supply in a power system. The circuit breakers are the most dynamic and transient equipment in transmission and distribution power systems and they are the main interrupter for the clearing of faults. In the power system, 95% of faults occur in the medium voltage network. If a faults occurs and is not interrupted timeously by the circuit breaker, the entire system ages faster. It was identified that the arcing temperature during fault interruption is most responsible for the wearing of the circuit breaker arcing contacts, thus, leading to the reduced breaker lifespan. The useful life improvement was dependant on the reduction of the arcing current and power of the arc which is proportional to the arcing energy and temperature. The vacuum circuit breaker was investigated for the controlled switching technologies. A predicted controlled trip time logic equation was derived using the controlled switching methodology with the addition of using input parameter variables relevant to the circuit breaker environment to predict early current zero tripping. The environmental conditions comprised of the ambient temperature, idle time and standard circuit breaker operation time. The advanced controlled circuit breaker logic was also developed using electromagnetic transient simulation software called PSCAD to predict the earlier current zero tripping times based on the vacuum circuit breakers environmental conditions. The software uses the black box modules to mimic operation of each environmental condition namely the idle time logic controller, temperature delay logic controller and predicted current zero controller. The results for the predicted controlled trip time equation was compared to the results obtained using the simulated results on PSCAD. The results from the predicted controlled trip equation versus the simulated advanced controlled simulated module proved to be within a 0.1% tolerance. The PSCAD software also facilitated the analysis of results for the various interruption phenomena namely the namely arc voltage, arc current, transient recovery voltage, re-ignition, restrikes, dynamism and temperature of arc that occur during the circuit breaker fault interruption. The abovementioned interruption had seen a reduction when compared to the conventional circuit breaker during fault interruption with the average arc current being reduced by 10%. The advanced controlled simulated results obtained for the interruption phenomena was thereafter benchmarked against the simulated conventional vacuum circuit breaker using the Arrhenius equation to determine its impact on the circuit breaker useful life. The results for the advanced controlled switching circuit breaker had proven an average of 7% improvement in useful life when compared to a conventional circuit breaker. The 7% improvement proved to increase the circuit breaker lifespan for an average of 20 years to 21.4 years. This is a 1.4-year improvement in the circuit breaker lifespan. Thus, the cost of replacement of the circuit breaker may be deferred by 1.4 years but this has a significant impact on the total annual capital expenditure budget due to the number of circuit breakers used.
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    Modeling and recognition of faults in smart distribution grid using maching intelligence technique
    (2018) Onaolapo, Adeniyi Kehinde; Akindeji, Timothy Kayode; Adetiba, Emmanuel
    Electrical power systems experience unforeseen faults attributable to diverse arbitrary reasons. Unanticipated failures occurring in power systems are to be prevented from propagating to other parts of the protective system to enhance economic efficacy of electric utilities and provide better service to energy consumers. Since most consumers are directly connected to power distribution networks, there is an increasing research efforts in distribution network fault recognition and fault-types identifications to solve the problem of outages due to faults. This study focuses on fault recognition and fault-types identification in electrical power distribution system based on the Design Science Research (DSR) approach. Diverse simulations of fault types at different locations were applied to the IEEE 13 Node Test Feeder to produce three phase currents and voltages as data set for this study. This was realized by modelling the IEEE 13-node benchmark test feeder in MATLAB-Simulink R2017a. In order to achieve intelligent fault recognition and fault-type identification, different Multi-layer Perceptron Artificial Neural Networks (MLP-ANN) models were designed and subsequently trained using the generated dataset with the Neural Network toolbox in MATLAB R2017a. The fault recognition task verifies if a fault occurs or not while the fault-types identification task determines the fault class as well as the faulty phase(s). Results obtained from the various MLP-ANN models were recorded and statistically analyzed. Acceptable performances were obtained for fault recognition with the 6-25-20-15-1 MLP-ANN architecture, for fault-types identification with the 6-40-4 MLP-ANN architecture and for fault location with the 6-30-15-5-4 MLP-ANN architecture. Given the result obtained in this study, MLP-ANN is adjudged suitable for intelligent fault recognition and fault-types identification in power distribution systems. The trained MLP-ANNs in this study could ultimately be incorporated in power distribution networks within South Africa and beyond in order to enhance energy customers’ satisfaction.