Topic
Power-system protection
About: Power-system protection is a research topic. Over the lifetime, 6353 publications have been published within this topic receiving 117961 citations.
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TL;DR: In this paper, a modified Z-source dc circuit breaker is introduced for the operation at medium-voltage dc with future applications in naval ship power systems, which limits capacitor current in the circuit and can be easily modified for fault detection.
Abstract: The Z-source dc circuit breaker has been introduced as a new circuit for quickly and automatically switching off in response to faults. A modified Z-source breaker design is introduced for the operation at medium-voltage dc with future applications in naval ship power systems. Compared to existing designs, the respective design will allow for greater control of step changes in load. This new design also limits capacitor current in the circuit and can be easily modified for fault detection. Analysis of the breaker operation is presented during both the fault and step changes in load. Low-voltage laboratory validation of the breaker was carried out on two different versions of the proposed circuit.
52 citations
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TL;DR: In this paper, a probabilistic model of the failure of the protection system is used to predict the number and characteristics of voltage sags in large distribution networks, and the results presented in the paper show that the proposed method is superior to the traditional techniques used for the assessment of voltage sag.
Abstract: This paper presents a comprehensive method for stochastic prediction of the number and characteristics of voltage sags in large distribution networks. The novelty of the proposed approach is in probabilistic modeling of the failure of the protection system. The probability of the failure of the protection system is determined using a straightforward, decision tree based method. The paper highlights the effects of the protection system failure on the number and characteristics of voltage sags. The method proposed and its capabilities are demonstrated on the realistic size generic distribution system. The results presented in the paper show that the proposed method is superior to the traditional techniques used for the assessment of voltage sags as it results in higher accuracy of the prediction of the number and characteristics of voltage sags.
52 citations
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TL;DR: In this paper, an efficient computational methodology that can be used for calculating the appropriate strategy for load shedding protection in autonomous power systems is described, which is based on the sequential Monte Carlo simulation approach for comparing alternative strategies by taking into account the amount of load to be shed and the respective risk for the system stability.
Abstract: This paper describes an efficient computational methodology that can be used for calculating the appropriate strategy for load shedding protection in autonomous power systems. It extends an existing method that is based on the sequential Monte Carlo simulation approach for comparing alternative strategies by taking into account the amount of load to be shed and the respective risk for the system stability. The extended methodology uses artificial neural networks (ANNs) for determining directly the parameters of the most appropriate load shedding protection strategy. For this purpose, the system inputs are the desirable probabilistic criteria concerning the system security or the amount of customer load interruptions. Using this methodology, the utility engineers can adopt a specific strategy that meets the respective utility criteria. The methodology was tested on a practical power system using a computer simulation for its operation, and the obtained results demonstrate its accuracy and the improved system performance
52 citations
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TL;DR: This work presents a methodology that combines the use of artificial neural networks and fuzzy logic for alarm processing and identification of faulted components in electrical power systems.
Abstract: This work presents a methodology that combines the use of artificial neural networks and fuzzy logic for alarm processing and identification of faulted components in electrical power systems. Fuzzy relations are established and form a database employed to train artificial neural networks. The artificial neural networks inputs are alarm patterns, while each output neuron is responsible for estimating the degree of membership of a specific system component into the class of faulted components. The proposed method allows good interpretation of the results, even in the presence of difficult corrupted alarm patterns. Tests are performed with a test system and with part of a real Brazilian system.
52 citations
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TL;DR: In this paper, a three-tier hierarchy of stability-related norms defined by branch norm, fault norm, and system norm is proposed to detect an out-of-step condition.
Abstract: Postfault rotor angle oscillations lead to power swings. Both unstable and stable swings can induce distance relay tripping. For unstable swings, a new computational procedure to locate all of the electrical centers is developed. It simplifies the work associated with visual screening of all the R-X plots. For stable swings, a generic three-tier hierarchy of stability-related norms defined by branch norm, fault norm, and system norm is proposed. Ranking by branch norm leads to ranking of power swings. Ranking by fault norm leads to ranking of faults or contingencies. Magnitude and rate of change of system norm can be used to detect an out-of-step condition. Results on a ten-machine system and a utility system with detailed models are also presented.
52 citations