• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.8
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• pp.444-449
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• 2003

In this paper present Autonomous Adaptive Digital Over Current Relay for distribution networks which acts autonomous setting using the short circuit impedance measured by relay of power systems. Automation of relay setting is one of the basic requirements for distribution automation, although manual relay setting is used at present. The short circuit impedance from a power source in distribution networks essential for the Autonomous Relay Setting changes frequently in distribution networks. In this paper the short circuit impedance is calculated with voltage and current measured in real time operation of digital relay using the Recursive Least Squares. A new method of digital relay setting is introduced using the the short circuit impedance and load current.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.6-8
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• 2002

In this paper present Autonomous Adaptive Digital Over Current Relay which acts autonomous setting using voltage and current measured by relay in the change of power systems. Automation of relay setting is required for distribution automation although manual relay setting is used at present. This paper presents Autonomous Relay Setting which knows change of the power system and acquires setting element using the Recursive Least Squares. Relay setting is very difficult work. But proposed relay is expected to decrease burden of relay setting using acquired information of power system change and autonomous setting. Also fast protective ability is expected according to change of power system.

• ETRI Journal
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• v.40 no.3
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• pp.318-329
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• 2018

Femtocell (FC) technology envisaged as a cost-effective approach to attain better indoor coverage of mobile voice and data service. Deployment of FCs over macrocell forms a heterogeneous network. In urban areas, the key factor limits the successful deployment of FCs is inter-cell interference (ICI), which severely affects the performance of victim users. Autonomous FC transmission power setting is one straightforward way for coordinating ICI in the downlink. Application of intelligent control using soft computing techniques has not yet explored well for wireless networks. In this work, autonomous FC transmission power setting strategy using Adaptive Neuro Fuzzy Inference System is proposed. The main advantage of the proposed method is zero signaling overhead, reduced computational complexity and bare minimum delay in performing power setting of FC base station because only the periodic channel measurement reports fed back by the user equipment are needed. System level simulation results validate the effectiveness of the proposed method by providing much better throughput, even under high interference activation scenario and cell edge users can be prevented from going outage.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1521-1526
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• 2007

This paper presents the application of Adaptive Evolutionary Algorithm (AEA) to search an optimal setting of overcurrent relay coordination to protect ring distribution systems. The AEA takes the merits of both a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. The overcurrent relay settings and coordination requirements are formulated into a set of constraint equations and an objective function is developed to manage the overcurrent relay settings by the Time Coordination Method. The domain of overcurrent relays coordination for the ring-fed distribution systems is a non-linear system with a lot of local optimum points and a highly constrained optimization problem. Thus conventional methods fail in searching for the global optimum. AEA is employed to search for the optimum relay settings with maximum satisfaction of coordination constraints. The simulation results show that the proposed method can optimize the overcurrent relay settings, reduce relay mis-coordinated operations, and find better optimal overcurrent relay settings than the present available methods.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1590-1599
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• 2016

The installation of distributed generation (DG) in the electrical networks has numerous advantages. However, connecting and disconnecting of DGs (CADD) leads to some problems in coordination of protection devices due to the changes in the short circuit levels in the different points of network. In this paper, an adaptive method is proposed based on available setting groups (SG) of relays. Since the number of available SG is less than possible CADD states, a classifying index (CI) is defined to categorize the several states in restricted setting groups. Genetic algorithm (GA) with a suitable objective function (OF) is used as an optimization method for the classification. After grouping, a modified coordination method is applied to achieve optimal coordination for each group. The efficiency of the proposed technique is demonstrated by simulation results.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.893-895
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• 1998

This paper presents the adaptive setting method of distance relay under the single line ground fault. The apparent impedance measured at the relaying point and actual impedance is different because of fault resistance and various prefault loading condition. For a resistance earth fault detection, relay setting zone is adaptively changed with measured load current and bus voltage at the relaying point to avoid maloperation.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.61-63
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• 1993

This parer propose an adaptive methodlogy for setting of the underfrequency relays that is based on the initial rate of change of the frequency at the relay. During severe emergencies which result in insufficient power generation to meet load, an automatic load shedding program throughout the affected area can prevent total collapse. To avoid this kind of insufficient power generation, load shedding relays are often applied throughput the system to provide a means of helping balance the load to the remaining generation. Comparing, it has been found that the use of the proposed method for the amount and the timing of load shed more efficiently than the conventional method.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.241-250
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• 2023

In this paper, when using the LMS algorithm for adaptive ultrasonic beamforming system, the effect of initial value setting on the margin of step parameters was studied. To this end, quasi-ideal beams, rotational beams with arbitrarily set beam widths were used as examples. In the numerical simulations, an arbitrary initial value(the number of sound sources fixed to any number) was set in the ultrasonic beamforming system, and the margin of the step parameter and convergence characteristics thereof were compared.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.1-11
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• 2018

In various engineering fields, determining the appropriate parameter set is a cumbersome and difficult task when solving optimization problems. Despite the appropriate parameter setting through parameter sensitivity analysis, there are limits to evaluating whether the parameters are appropriate for all optimization problems. For this reason, kinds of a Self-adaptive Harmony searches have been developed to solve various engineering problems by the appropriate setting of algorithm's own parameters according to the problem. In this study, various types of Self-adaptive Harmony searches were investigated and the characteristics of optimization were categorized. Six algorithms with a differentiation of optimization process were applied and compared with not only the mathematical optimization problem, but also the engineering problem, which has been applied widely in the algorithm performance comparisons. The performance of each algorithm was compared, and the statistical performance indicators were used to evaluate the application results quantitatively.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.27-39
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• 2016

This paper considers variable selection in the sparse vector autoregressive (sVAR) model where sparsity comes from setting small coefficients to exact zeros. In the estimation perspective, Davis et al. (2015) showed that the lasso type of regularization method is successful because it provides a simultaneous variable selection and parameter estimation even for time series data. However, their simulations study reports that the regular lasso overestimates the number of non-zero coefficients, hence its finite sample performance needs improvements. In this article, we show that the adaptive lasso significantly improves the performance where the adaptive lasso finds the sparsity patterns superior to the regular lasso. Some tuning parameter selections in the adaptive lasso are also discussed from the simulations study.