• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1463-1471
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• 2009

In this paper, a new algorithm of Integrated Volt/Var Control (IVVC) is proposed using Volt/Var control for the Distribution Automation System (DAS) based on the modeling of the distributed load and the distributed current. In the proposed, the load flow based on the modeling of the distributed load and the distributed current are estimated from constants of four terminals using the measurement of the current and power factor from a Feeder Remote Terminal Unit (FRTU). For Integrated Volt/Var Control (IVVC), the gradient method is applied to find optimal solution for tap and capacity control of OLTC (On-Load Tap Changers), SVR (Step Voltage Regulator), and SC (Shunt Condenser). What is more Volt/Var control method is proposed using moving the tie switch as well as IVVC algorithm using power utility control. In the case studies, the estimation and simulation network have been testified in Matlab Simulink.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2002.11a
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• pp.23-32
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• 2002

The torsional forward extrusion is the process that is executed by punch travel and die rotation. The advantages of having the die rotation on this process are that forming load can be reduced and optimal die angle can be increased. This provides a possibility to extrude cold-worded material where a large extrusion force and die angle are required. Also, this process can improve the material properties owing to the high deformation and uniform strain distribution. The forming load and optimal die angle of this process are determined by the upper bound analysis using stream function and the optimization technique. To verify the theoretical result, we have carried out experiments and FE simulations using DEFORM3D.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.960-972
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• 1992

This paper deals with the development of expert system in distribution system which combined with graphic user interface. The proposed expert system can recognize and adjust to the system change, and includes the rule bases of security monitoring. Also it provides load transfer algorithm for efficient load distribution. The graphic user environment for expert system is implemented in the mouse-oriented user interface with overlapped window functions and pull-down menus. Therefore, the developed graphic integrated expert system can afford to assist system operators very conveniently through the various graphic function in proposing an optimal plan of load transfer for fault restoration and outage schedule.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.3
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• pp.83-92
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• 2008

This paper develops the theory for a fault-tolerant, permanent magnet biased, homopolar magnetic bearing. If some of the coils or power amplifiers suddenly fail, the remaining coil currents change via a novel distribution matrix such that the same magnetic forces are maintained before and after failure. Lagrange multiplier optimization with equality constraints is utilized to calculate the optimal distribution matrix that maximizes the load capacity of the failed bearing. Some numerical examples of distribution matrices are provided to illustrate the theory. Simulations show that very much the same dynamic responses (orbits or displacements) are maintained throughout failure events (up to any combination of 3 coils failed for the 6 pole magnetic bearing) while currents and fluxes change significantly. The overall load capacity of the bearing actuator is reduced as coils fail. The same magnetic forces are then preserved up to the load capacity of the failed.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.435-447
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• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• 전기의세계
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• v.18 no.6
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• pp.9-22
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• 1969

This thesis has suggested a method of applying the Maximum Principle of Pontryagin to the optimal control of distributive electrical networks. In general, electrical networks consist of branches, nodes, sources and loads. The effective values of steady state currents and voltages are independent of time but only expressed as the functions of position. Moreover, most of the node voltages and branch currents are not predetermined, that is, initially unknown, and their inherent loop characteristics satisfy only Kirchhoff's current and voltage laws. The Maximum Principle, however, needs the initial fixed values of all state variables for its standand way of application. In spite of this inconsistency this thesis has undertaken to suggest a new approach to the successful solution of the above mentioned networks by introducing scaling factors and a state variable change technique which transform the boundary-value unknown problem into the boundary-value partially fixed and partially free problem. For the examples of applying the method suggested, the control problems for minimizing copper quantity in a distribution line have been solved with voltage drop constraint imposed on. In the case of uniform load distribution it has been shown that the optimal wire diameter of the distribution line is reciprocally proportional to the root of distance. For the same load pattern as above the wire diameter giving the minimum copper loss in the distribution line has been shown to be reciprocally proportional to distance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.27-34
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• 2014

The paper proposed a sizing method of an energy storage system(ESS) for peak shaving of high-speed railway substations based on load profile patterns of substations. A lithium based battery ESS was selected since it can produce high-power at high speed that peak shaving requires, and also takes up a relatively smaller space for installation. Adequate size of the ESS, minimum capacity which can technically meet a peak shaving target, was determined by collectively considering load patterns of a target substation, characteristics of the ESS to be installed, and optimal scheduling of the ESS. In case study, a local substation was considered to demonstrate the proposed sizing method. Also economic analysis with the determined size of ESS was performed to calculate electricity cost savings of the peak shaving ESS, and to offer pay-back period and return on investment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.2
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• pp.63-70
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• 2008

This paper resents the spatial electric load forecasting algorithm using the multiple regression analysis method which is enhanced from the algorithm of the DISPLAN(Distribution Information System PLAN). In order to improve the accuracy of the spatial electrical load forecasting, input variables are selected for GRDP(Gross Regional Domestic Product), the local population and the electrical load sales of the past year. Tests are performed to analyze the accuracy of the proposed method for Gyeong-San City, Gu-Mi City, Gim-Cheon City and Yeong-Ju City of North Gyeongsang Province. Test results show that the overall accuracy of the proposed method is improved the percentage error 11.2[%] over 12[%] of the DISPLAN. Specially, the accuracy is enhanced a lot in the case of high variability of input variables. The proposed method will be used to forecast local electric loads for the optimal investment of distribution systems.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.2
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• pp.58-66
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• 2001

This paper presents an application of a newly designed Adaptive Genetic Algorithm (AGA) to solve the Optimal Feeder Routing (OFR) problem for distribution system planning. The main objective of the OFR problem usually is to minimize the total cost that is the sum of investment costs and system operation costs. We propose a properly designed AGA, in this paper, which can handle the horizon-year expansion planning problem of power distribution network in which the location of substation candidates, the location and amount of forecasted demands are given. In the proposed AGA, we applied adaptive operators using specially designed adaptive probabilities. we also a Simplified Load Flow (SLF) technique for radial networks to improve a searching efficiency of AGA. The proposed algorithm has been evaluated with the practical 32, 69 bus test system to show favorable performance. It is also shown that the proposed method for the OFR can also be used for the network reconfiguration problem in distribution system.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.804-811
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• 2015

The presence of responsive loads in the promising active distribution networks (ADNs) would definitely affect the power system problems such as distributed generations (DGs) studies. Hence, an optimal procedure is proposed herein which takes into account the simultaneous placement of DGs and smart meters (SMs) in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Seeking to power loss minimization, the optimization procedure is tackled with genetic algorithm (GA) and tested thoroughly on 69-bus distribution test system. Different scenarios including variations in the number of DG units, adaptive power factor (APF) mode for DGs to support reactive power, and individual or simultaneous placing of DGs and SMs have been established and interrogated in depth. The obtained results certify the considerable effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the lowest value of power losses as well.