C.J. Kim

Bio: C.J. Kim is an academic researcher from University of Suwon. The author has an hindex of 1, co-authored 1 publications receiving 25 citations.

A study on the characterization of the incipient failure behavior of insulators in power distribution line

Abstract: A feasibility study on the characterization of incipient insulator failure for distribution fault prediction is presented. In this study, real distribution data was collected and analyzed to isolate incipient failure signatures or parameters which were expected to show distinct behaviors before and after failure incident. Several signal analysis methods were applied to isolate the parameters and a new strategy of analysis, the event-date concept, was also applied to find a relationship between nonharmonic and high frequency signal activities and imminent insulator failures.

Multi-agents based protection for distributed generation systems

Abstract: As a result of deregulation, distributed generation (DG) systems with distributed generators installed in the middle or low voltage networks become popular in distribution systems. Traditional protections developed in radial systems are difficult in coordination and in protecting against high impedance fault (HIF), sometimes it may cause nuisance tripping in the DG systems. A decentralized multi-agent based protection with capability of HIF detection, fault location and load shedding for the DG systems is proposed in the paper. Digital relay is designed as a relay agent which is capable of searching for information from other relay agents, interacting with other relay agents and performing tasks of protection with autonomy and cooperating. The agent based protection scheme is also presented. EMTP simulation results show that the proposed agent based protection scheme can remove the influence of load switching operations, protect against HIF, electric shock. The prototype of relay agent is developed, the research is now in progress on testing the prototype in dynamic power system.

Ground-Fault Feeder Detection With Fault-Current and Fault-Resistance Measurement in Mine Power Systems

Abstract: Many mine power systems operate with a floating neutral or are high-resistance grounded, and earth fault current is no more than a few tens of amperes. Traditional earth-fault-detection methods based on zero-sequence current have poor sensitivity in this case. For improvement, a fault-detection scheme with fault-current and fault-resistance measurement is presented in this paper, which is capable of detecting high-impedance ground faults. The scheme has been verified by electromagnetic-transient-program simulation, and a fault-detection prototype has been developed and tested in the laboratory. Results show that the scheme has high sensitivity and robustness.

Cable fault detection

Abstract: A cable fault detection component (168) receives input data indicative of a fault in an electrical power system. The component (168) analyzes the input data to determine if the fault is indicative of a self-clearing cable fault and generates corresponding output data (276). In one implementation, the cable fault detection component (168) is implemented as a software module which operates on a computer (105) of a substation intelligence system (104).

A Generic Waveform Abnormality Detection Method for Utility Equipment Condition Monitoring

Abstract: In recent years, power quality (PQ) disturbance data are increasingly applied to extract useful information about the condition of power systems, such as monitoring incipient equipment failures. A prerequisite for such applications is the ability for a PQ monitor to detect abnormal waveforms. In response to this need, a generic method for waveform abnormality detection is proposed in this paper. The proposed method has two unique features. First, abnormalities are detected by comparing the statistical distributions of waveform variations with and without disturbances. Kullback-Leibler divergence (KLD) is used to assess the difference of the distributions. An abnormality exists if the KLD is larger than a threshold. Second, current waveforms are used for detection since they are more sensitive to equipment conditions. The difficulty to set a proper threshold due to large variations of current values is overcome through the adoption of KLD as the distance measure and a systematic threshold selection scheme. The scheme maximizes the detection probability for a given false alarm probability. Field-measured data and simulated data are applied to verify the effectiveness of the method.

Evaluation of feeder monitoring parameters for incipient fault detection using Laplace trend statistic

Abstract: This paper focuses on a systematic and cumulative statistical approach for identifying symptom parameters of incipient faults in distribution feeders. The proposed method aims at providing a tool for evaluating and identifying the best and highly correlated parameters to the faults so that they could be used for incipient fault detection and feeder condition monitoring. The Laplace test statistic is adopted for trend analysis of the event log of candidate parameters and applied to actual feeder event data for online detection and monitoring purposes.