• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.730-731
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• 2011

EPA(Electric Power Automation IT Infra) is a System for Protective Information Transmitter & Receiver and network service. KEPCO(Korea Electric Power Corporation) is building up a high-speed communication network to accept Smart Grid Infra expansion and various terminal communication media characteristic. Recently, MSPP(Multi Service Provisioning Platform) System is establishted to network service. But there are many considerations for optimal design of network service for the Electric Power Automation IT Infra.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.76-82
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• 2001

This paper presents a approach for a service restoration and optimal reconfiguration of distribution network using Genetic algorithm(GA) and Tabu search(TS) method. Restoration and reconfiguration problems in distribution network are difficult to solve in short times, because distribution network supplies power for customers combined with many tie-line switches and sectionalizing switches. Furthermore, the solutions of these problems have to satisfy radial operation conditions and reliability indices. To overcome these time consuming and sub-optimal problem characteristics, this paper applied Genetic-Tabu algorithm. The Genetic-Tabu algorithm is a Tabu search combined with Genetic algorithm to complement the weak points of each algorithm. The case studies with 7 bus distribution network showed that not the loss reduction but also the reliability cost should be considered to achieve the economic service restoration and reconfiguration in the distribution network. The results of suggested Genetic-Tabu algorithm and simple Genetic algorithm are compared in the case study also.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.700-705
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• 2004

Clustering of incomplete data using the Autoencoder and the Fuzzy c-Means(PCM) is proposed in this paper. The Proposed algorithm, called Optimal Completion Autoencoder Fuzzy c-Means(OCAEFCM), utilizes the Autoencoder Neural Network (AENN) and the Gradiant-based FCM (GBFCM) for optimal completion of missing data and clustering of the reconstructed data. The proposed OCAEFCM is applied to the IRIS data and a data set from a financial institution to evaluate the performance. When compared with the existing Optimal Completion Strategy FCM (OCSFCM), the OCAEFCM shows 18％-20％ improvement of performance over OCSFCM.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.6
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• pp.302-310
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• 2002

This paper presents an application of a improved branch exchange (IBE) algorithm with a tie branch power (TBP) flow equation to solve the Optimal Routing problem for operation of a radial Power system including power distribution system. The main objective of the Optimal Routing problem usually is to minimize the network real power loss and to improve the voltage profile in the network. The new BE algorithm adopts newly designed methods which are composed by decision method of maximum loss reduction and new index of loss exchange in loop network Thus, the proposed algorithm in this paper can search the optimal topological structures of distribution feeders by changing the open/closed states of the sectionalizing and tie switches. The proposed algorithm has been evaluated with the practical IEEE 32, 69 bus test systems and KEPCO 148 bus test system to show favorable performance gained.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2079-2088
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• 2009

The optimal operation in distribution system is to select tie switches considering important elements(Load balance, Loss minimization, Voltage drop, Restoration index..) in distribution system. Optimal Tie Switches Selection is very important in operation of distribution system because that is closely related with efficiency and reliability. In this paper, a new algorithm considering important elements is proposed to find optimal location of tie switches. In the case study, the proposed algorithm has been testified using real distribution network of KEPCO for verifying algorithm and complex network for applying future distribution network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10A
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• pp.941-949
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• 2007

By the newly emerging Network access technology, we face the new heterogeneous network environment. The required level of service quality and diversity are now multiplied by the increment of wireless service subscribers. Focusing on the co-existence of multiple access network technology and the complex service needs of users, the wireless service operators should present the stable service quality for every user. The service operators should build the new operation framework which combines the pre-established networks and newly adopted ones. Our problem is finding the optimal heterogeneous network operation framework. We suggest a market-based marginal cost function for evaluating the relative value of resource of each network and develop the whole new heterogeneous network operation framework.

• Journal of Korea Water Resources Association
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• v.44 no.12
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• pp.1001-1013
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• 2011

Development of an optimal water supply system considering water quantity, quality, and economical efficiency is needed to decide optimal available area by combine water supply systems in overlapped area where are more than 2 water sources. The EPAnet and the KModSim were coupled to develop optimal network model. The developed network model was calibrated by measured data from water supply system in Geoje City, Korea in 2007 which have three water sources such as Sadeong booster pumping station, Guchun dam reservoir and Yoncho dam reservoir. The optimum network model was validated by operating results of 2011 to assess the economically optimized service area and optimal pump combination under the given hydraulic operating rules developed in this study. The developed model can be applied into designing water supply systems and operating rules for the conjunctive operation since the model can give the optimal solution satisfied with water quantity, economical efficiency and quality.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.7
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• pp.1025-1032
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• 1990

We proposed a neural network energy function for the optimal graph partitioning and its optimization method using Boltzmann Machine. We composed a Boltzmann Machine with the proposed neural network energy function, and the simulation results show that we can obtain an optimal solution with the energy function parameters of A=50, B=5, c=14 and D=10, at the Boltzmann Machine parameters of To=80 and \ulcorner0.07 for a 6-node 3-partition problem. As a result, the proposed energy function and optimization parameters are proved to be feasible for the optimal graph partitioning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1802-1814
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• 2012

In order to guide users to select the most optimal access network in heterogeneous wireless networks, a network selection algorithm is proposed which is designed based on multi-objective discrete particle swarm optimization (Multi-Objective Discrete Particle Swarm Optimization, MODPSO). The proposed algorithm keeps fast convergence speed and strong adaptability features of the particle swarm optimization. In addition, it updates an elite set to achieve multi-objective decision-making. Meanwhile, a mutation operator is adopted to make the algorithm converge to the global optimal. Simulation results show that compared to the single-objective algorithm, the proposed algorithm can obtain the optimal combination performance and take into account both the network state and the user preferences.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.7
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• pp.1881-1897
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• 1994

This paper presents a neural network-based computational scheme to generate the optimized robotic assembly sequence for an assembly product consisting of a number of parts. An assembly sequence is considered to be optimal when it meets a number of conditions : it must satisfy assembly constraints, keep the stability of in-process subassemblies, and minimize assembly cost. To derive such an optimal sequence, we propose a scheme using both the Hopfield neural network and the expert system. Based upon the inferred precedence constraints and the assembly costs from the expert system, we derive the evolution equation of the network. To illustrate the suitability of the proposed scheme, a case study is presented for industrial product of an electrical relay. The result is compared with that obtained from the expert system.