• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.950-953
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• 2016

A packet loss caused TCP segment drop and retransmission. This makes the energy useless, which is consumed to deliver the whole packets of the dropped segment over many hops. In this paper, end-to-end TCP retramission will be analyzed for the effect to energy consumed for delivering data. Especially, this paper will compare and analyze the legacy TCP method and Store-and-Forward method, and the method of computing the energy efficiency to transmission loss. This paper expects that the proposed method can contribute to new energy saving decision or algorithm on diverse data transmission situation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.4
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• pp.47-53
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• 2015

The electrical safety and efficiency is the most important thing of the electric vehicle charging system. The prior system is contact charging system that is contacted directly by human. So, it has riskiness such as electric shock in the case of poor insulation or contact problems. To solve these safety issues and the convenience problems, a wireless power transmission system has been developed and is currently in trial operation. However, because high frequency is used in wireless power transmission system instead of commercial frequency, we need to apply protection measures concerning electric shock and equipment protection. Also, it should be accompanied by measuring efficiency for the effective operation of the wireless power transmission system. Therefore, we structured monitoring system in trial operation area of wireless power transmission system and applied decision algorithm for protection of human and equipment and economic operation of it.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2230-2237
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• 2015

Inspired by the synchronization phenomena observed in the Nature, we propose an autonomous load balancing method for a wireless network. We model the load balancing problem of cells providing wireless access services as a synchronization problem in the Nature and design an algorithm for each cell to distribute loads in a self-determining way based on the load differences among its neighbor cells. Through simulations, we verify the feasibility of the proposed method in that cell loads can be balanced efficiently eve if cells make decision autonomously using their local information.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.145-155
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• 2010

This paper presents a new approach to obstacle avoidance for mobile robot in unknown or partially unknown environments. The method combines two navigation subsystems: low level and high level. The low level subsystem takes part in the control of linear, angular velocities using a multivariable PI controller, and the nonlinear position control. The high level subsystem uses ultrasonic and IR sensors to detect the unknown obstacle include static and dynamic obstacle. This approach provides both obstacle avoidance and target-following behaviors and uses only the local information for decision making for the next action. Also, we propose a new algorithm for the identification and solution of the local minima situation during the robot's traversal using the set of fuzzy rules. The system has been successfully demonstrated by simulations and experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.83-93
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• 2000

This paper proposes the use of the analytic hierarchy process(AHP) controller for obtaining optimal cycle time of traffic intersection signal. By means of simulations that have data from expert traffic estimators, the performance of AHP controller is compared with a fixed-time controller and fuzzy controller. A simulation was executed using data obtained from many expert interviewer of Ansan City hall rotary. The principal issue is how AHP controller algorithm can aid traffic signal supervisor to construct an expert system for traffic intersection signal control. This paper has two steps: (I) we shall present a new methodology based on the work of Satty for calculating a scale of importance of each of the objectives, (2) we also consider that the human's decision mechanism is represented by approximating reasoning where the fuzzy integral is used.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.7 s.110
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• pp.615-622
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• 2006

DVB-S2 offers various coding rate and modulation schemes. Therefore this paper proposes bit split methods to applying to multilevel modulation. Log-likelihood ratio method splits multilevel symbols to soft decision symbols using the received in-phase and quadrature component based on Gaussian approximation. However it is too complicate to calculate and to implement hardware due to exponential and logarithm calculation. Therefore this paper presents Euclidean, MAX and Sector method to reduce the high complexity of LLR method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1020-1023
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• 2011

In this paper, we present a symbol remapping method of BRGC M-ary QAM signal by using LLR soft bit decision information which is obtained after iterative decoding process. In order to reconstruct estimated transmitted signal constellation, we have to use exponential or hyperbolic tangent(tanh) function resulting in high implementation complexity. The BRGC mapping rule enables us to use a recursive operation. In addtion, we reduce the implementing complexity by using a curve fitting algorithm.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.128-132
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• 2001

In this paper, we evaluate and contrast four neural network rule extraction approaches for credit scoring. Experiments are carried our on three real life credit scoring data sets. Both the continuous and the discretised versions of all data sets are analysed The rule extraction algorithms, Neurolonear, Neurorule. Trepan and Nefclass, have different characteristics, with respect to their perception of the neural network and their way of representing the generated rules or knowledge. It is shown that Neurolinear, Neurorule and Trepan are able to extract very concise rule sets or trees with a high predictive accuracy when compared to classical decision tree(rule) induction algorithms like C4.5(rules). Especially Neurorule extracted easy to understand and powerful propositional if -then rules for all discretised data sets. Hence, the Neurorule algorithm may offer a viable alternative for rule generation and knowledge discovery in the domain of credit scoring.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1269-1273
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• 2010

Typically users prefer to manage and access personal photo collections taken from a cell phone based on events. In this paper we propose an event clustering algorithm that requires low computation cost with high accuracy supporting incremental operation. The proposed method is based on the statistical analysis of the elapsed interval of intra-event photos on the real sample data for the decision of an event boundary. We then incorporate both location and visual information for the ambiguous range to split with only temporal cue. According to test results, we show higher performance compared to existing general clustering approaches.