• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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• pp.376-383
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• 2001

Factors leading to poor control of the steam generator in a nuclear power plant are nonminimum phase characteristics, unreliable of flow measurements and nonlinear characteristics, which increase more at low power(below 20%) operation. And the study of problems for water level control in the steam generator is that design water level controller only power renge, not entire. This paper introduces a model predictive control(MPC) algorithm for solving poor control factors and quadratic programming(QP) for solving input constraints. Also presents the design method of stable model predictive controller in the entire power range. The simulation results show the efficiency of proposed MPC controller by comparing with PI controller, and effect of the design parameters.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.1-7
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• 2016

An uninterruptible power supply (UPS) allows small companies and domestic users to cope with power outages; but existing designs lack flexibility of control and require expensive battery maintenance, with a cost proportional to the outage compensation time. We combine a compact synchronous generator with a battery, with 10% of the capacity that would otherwise be required, to obtain a UPS with reduced maintenance costs for the same performance. Any UPS must respond immediately to a power loss, and our uninterruptible generator supply (UGS) is therefore built around real-time scheduling of its internal operations; this also makes it suitable for integration into the industrial gateway. The UGS is based on a real-time operating system, with an integrated wireless module providing connectivity to a web server, for monitoring and management, which can be performed remotely on a mobile device.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1882-1890
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• 2014

This paper proposes an augmented Lagrange Hopfield network (ALHN) based method for solving multi-objective short term fixed head hydrothermal scheduling problem. The main objective of the problem is to minimize both total power generation cost and emissions of $NO_x$, $SO_2$, and $CO_2$ over a scheduling period of one day while satisfying power balance, hydraulic, and generator operating limits constraints. The ALHN method is a combination of augmented Lagrange relaxation and continuous Hopfield neural network where the augmented Lagrange function is directly used as the energy function of the network. For implementation of the ALHN based method for solving the problem, ALHN is implemented for obtaining non-dominated solutions and fuzzy set theory is applied for obtaining the best compromise solution. The proposed method has been tested on different systems with different analyses and the obtained results have been compared to those from other methods available in the literature. The result comparisons have indicated that the proposed method is very efficient for solving the problem with good optimal solution and fast computational time. Therefore, the proposed ALHN can be a very favorable method for solving the multi-objective short term fixed head hydrothermal scheduling problems.

• Journal of the Korean Institute of Navigation
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• v.14 no.1
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• pp.21-38
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• 1990

This paper discusses the various modes of operations of cargo ships which are liner operations, tramp shipping and industrial operations, and mathematical programming, simulation , and heuristic method that can be used to solve ships routing and scheduling problems for each of these operations. In particular, this paper put emphasis on a crude oil tanker scheduling problem. The problem is to achieve an optimal sequence of cargoes or an optimal schedule for each ship in a given fleet during a given period. Each cargo is characterized by its type, size, loading and discharging ports, loading and discharging dates, cost, and revenue. Our approach is to enumerate all feasible candidate schedate schedules for each ship, where a candidate schedule specifies a set of cargoes that can be feasibly carried by a ship within the planning horizon , together with loading and discharging dates for each cargo in the set. Provided that candidate schedules have been generated for each ship, the problem of choosing from these an optimal schedule for each ship is formulated as a set partitioning problem, a set packing problem, and a integer generalized network problem respectively. We write the PASCAL programs for schedule generator and apply our approach to the crude oil tanker scheduling problem similar to a realistic system.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.553-555
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• 1995

This paper presents the optimal short-term operation scheduling by using on cogeneration systems connected with auxiliary equipments. Simulation is performed in case of the bottomming cycle which generates the demand heat preferentially. Heat storage tank, electricity charger, auxiliary boiler and independent generator are considered as auxiliary equipments connected to cogeneration systems. The results of simulation show the auxiliary equipments can be effeciently operated in case of the bottomming cycle by modeling proposed in this paper. The effectiveness of operation scheduling gained by application of fuzzy theory is evaluated by detailed comparison and investigation of the simulation results.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.9
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• pp.609-615
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• 1987

The optimal operation of power system is developed by alternately using real power dispatch and reactive power dispatch problem. The real power system scheduling process is formulated as an optimization problem with linear inequality constraints. A.C. loadflow method is used for the problem solution and line losses are considered. The constraints under consideration are generator power limits, load scehdling limits and line capacity limits. In solving the objective function the Dual Relaxation method is adopted. Tests indicate that the method is practical for real time application. The reactive power control problem uses the Dual Simplex Relaxation method as in the real scheduling case. Insted of minimizing the cost of power system, the objective is selected as to determine the highest possible voltage schedule. The constraints under consideration are the voltage limits at each node and the possibilities of supply or absobtion of reactive energy by generator units and the compensation facilities. Tests indicate that the method is practical for real time applications. The overall optimization methods developed in this paper proved to obtained fine results in minimizing object function compared with the method without using voltage control. And the overall voltage profiles were also improved.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.717-725
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• 2011

In the power system with an electric storage system that can increase utilization rate of the source of such new renewable energy, this paper introduces the approach on the daily unit commitment scheduling that determines simultaneously optimum operational condition and output of thermal generators and electric storage device. The unit commitment is one of the most important issues in economic operation and security of short-term operational plan of the power system. It is to determine on/off status of generator to minimize operational cost during the given period. The committed generator should satisfy various operational limitation such as estimated demand by system, spinning reserve condition within minimum operational cost. In order to determine on/off or charge/discharge/idle condition and output level of units and electric storage system, the MILP(Mixed Integer Linear Programming) is suggested. The proposed approach is the mixed method between LP(Linear Programming) and IP(integer programming) which seeks the value of real number and integer that maximize or minimize function objective within given condition. The daily unit commitment problem with the electric storage system is applied to MILP algorithm through linearization and formulation process. The proposed approach is applied to the test system.

• Proceedings of the Korea Society for Simulation Conference
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• 1996.05a
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• pp.15-15
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• 1996

A shop floor control system (SFCS) is the central part of a CIM system used to control the activities of several pieces of manufacturing equipment (e.g., NC machines, robots, conveyors, AGVs, AS/RS). The SFCS receives orders and related process plans, and then performs selecting a specific process routing, allocating resources, scheduling the workpieces, downloading the processing instructions (e.g., RS-274 instructions for NC machines, VAL II programs for robot), monitoring the progress of activities, detecting and recovering from errors, and preparing reports on the status of the manufacturing system. Simulation has been utilized in discovering control policies used for resolving shop floor be control problems such as resource contentions, part dispatching, deadlock. The simulation model must be designed to respond to real-time data coming from a shop floor. However, to rapidly build a realtime simulation model of SFCS cannot be easily accomplished. This talk is to address an automatic program generator of discrete event simulation model for shop floor control from process plans and resource models. The program generator is capable of constructing complete discrete simulation models for multi-product and multi-stage flexible manufacturing systems.

• Proceedings of the KSR Conference
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• 1999.11a
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• pp.46-53
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• 1999

As of July 1999, i,185 lomocotives(excluding metropolitan area electric locomotives) are in Korean National Railroad(KNR). With this limited number of resources assigning locomotives to each trains of timetable is very important in the entire railway management point of view because schedule can be regarded as goods in transportation industry. On a simple rail network, it is rather easier to assign proper locomotives to trains with the experience of operating experts and get optimal assignment solution. However, as the network is getting bigger and complicated, the number of trains and corresponding locomotives will be dramatically increased to rover all the demands required to service all of the trains in timetable. There will be also numerous operational constraints to be considered. Assigning proper locomotives to trains and building optimal cyclic rotations of locomotive routings will result in increasing efficiency of schedule and giving a guarantee of more profit. The purpose of this study is two fold: (1) we consider a planning-level locomotive scheduling problem with the objective of minimizing the wasting cost under various practical constraints and (2) development of implementation prototype program of its assigning result. Not like other countries, i.e. Canada, Sweden, Korean railroad operates on n daily schedule basis. The objective is to find optimal assignment of locomotives of different types to each trains, which minimize the wasting cost. This problem is defined on a planning stage and therefore, does not consider operational constraints such as maintenance and emergency cases. Due to the large scale of the problem size and complexity, we approach with heuristic methods and column generation to find optimal solution. The locomotive scheduling prototype consists of several modules including database, optimization engine and diagram generator. The optimization engine solves MIP model and provides an optimal locomotive schedule using specified optimization algorithms. A cyclic locomotive route diagram can be generated using this optimal schedule through the diagram generator.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.329-337
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• 2016

With the increasing deployment of distributed generators in the distribution system, a very large search space is required when dynamic programming (DP) is applied for the optimized dispatch schedules of voltage and reactive power controllers such as on-load tap changers, distributed generators, and shunt capacitors. This study proposes a new optimal voltage and reactive power scheduling method based on dynamic programming with a heuristic searching space reduction approach to reduce the computational burden. This algorithm is designed to determine optimum dispatch schedules based on power system day-ahead scheduling, with new control objectives that consider the reduction of active power losses and maintain the receiving power factor. In this work, to reduce the computational burden, an advanced voltage sensitivity index (AVSI) is adopted to reduce the number of load-flow calculations by estimating bus voltages. Moreover, the accumulated switching operation number up to the current stage is applied prior to the load-flow calculation module. The computational burden can be greatly reduced by using dynamic programming. Case studies were conducted using the IEEE 30-bus test systems and the simulation results indicate that the proposed method is more effective in terms of saving electric charges and improving the voltage profile than loss minimization.