• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.11
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• pp.544-550
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• 2002

This paper describes a strategy of a daily optimal operational scheduling on the industrial cogeneration system. The cogeneration system selected to establish the scheduling consists of three units and several auxiliary devices which include three auxiliary boilers, t재 waste boilers and three sludge incinerators. One unit generated electrical and thermal energy using the back pressure turbine. The other two units generate the energy using the extraction condensing turbine. Three auxiliary devices operate to supply energy to the loads with three units. The cogeneration system is able to supply enough the thermal energy to the thermal load, however it can not sufficiently supply the electric energy to the electrical load. Therefore the insufficient electric energy is compensated by buying electrical energy from utility. In this paper, the evolutionary algorithms was applied to establish the optimal scheduling for the cogeneration systems. Also the GUI System was developed using established mathematics medeling and evolutionary algorithms in order that non-experts are able to establish operational scheduling. This results revel that the proposed modeling and strategy can be effectively applied to cogeneration system for paper mill.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.494-501
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• 2000

This paper describes a strategy of a daily optimal operational scheduling in cogeneration system for paper mill. The cogeneration system selected to establish the scheduling consists of three units and several auxiliary devices. One unit generates electrical and thermal energy using the back pressure turbine. The rest two units generate the energy using the extraction condensing turbine. Three auxiliary boilers, two waste boilers and three sludge incinerators operate to supply energy to the loads with three units. The cogeneration system is able to supply enough the thermal energy to the thermal load, however it can not sufficiently supply the electrical power to the electrical load. Therefore the insufficient electric energy is compensated by buying electrical energy from utility. When the operational scheduling is performed considering the environmental problem. This paper shows the simulation results for daily operational scheduling obtained using the evolutionary algorithm. This results reveal that the proposed modeling and strategy can be effectively applied to cogeneration system for paper mill.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.55-62
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• 2010

This paper studies the problem seeking an efficient operational scheduling for battle ships in the Republic of Korea's navy. The ships' availability means that their main systems such as weapons, navigation and propulsion are in full operational readiness. If some of the major systems are not ready, then the ships should not be available for operations. It is required to maintain a high level availability under the limited resources as it determines the strength of ROK's navy. However, it will result in inefficiencies if some ships are operated without proper maintenance only to improve their availability. Thus, this study suggests the operational scheduling for two squadron ships that considers multiple objectives such as availability, overlapping maintenance, and deviation from available ships in a particular week. We applied NSGA-II algorithm to find better solutions for more efficient scheduling. The experiment result reached an efficient solutions after 1,500 generations. Two efficient operational schedules were compared on the basis of three multiple objectives among them.

• Journal of the Korean Society for Railway
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• v.9 no.1 s.32
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• pp.50-56
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• 2006

This paper presents a mathematical model of the long-term track tamping scheduling problem in the Korean highspeed railway system. The presented model encompasses various operational field constraints, moreover improves a state-of-the-art model in extending the feasible space. We show the model is sized up to intractable scale, then propose another approximation model that is possible to handle with the present computer system and commercial optimization package, directly. The aggregated index, lot, is selected, considering the resolution of the planning horizon as well as scheduling purpose. Lastly, this paper presents two test results for the approximation model. The results expose the approximation model to quite promising in deploying it into an operational software program for the long-term track tamping scheduling problem.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1348-1356
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• 2017

Integration of wind generators with the conventional power plants will raise operational challenges to the electric power utilities due to the uncertainty of wind availability. Thus, the Generation Scheduling (GS) among the online generating units has become crucial. This process can be formulated mathematically as an optimization problem. The GS problem of wind integrated power system is inherently complex because the formulation involves non-linear operational characteristics of generating units, system and operational constraints. As the robust tool is viable to address the chosen problem, the modern bio-inspired algorithm namely, Grey Wolf Optimization (GWO) algorithm is chosen as the main optimization tool. The intended algorithm is implemented on the standard test systems and the attained numerical results are compared with the earlier reports. The comparison clearly indicates the intended tool is robust and a promising alternative for solving GS problems.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.370-375
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• 1992

This paper deals with the scheduling and simulation for FMC(Flexible Manufacturing Cells). In order to achieve CIM, there is a critical need to link factory level and machine level. The primary functions performed by this link for all jobs issued to the shop floor and cell include short-term scheduling and dynamic operational scheduling. Here, hierarchical control structure is introduced to define these functions. And Intelligent scheduling through expert module is adopted for efficiency of FMC operation. Computer simulation reveals that expert scheduling method is better than heuristics in various performance index.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.9-17
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• 2019

In order to deal with high uncertainty and variability in emergency medical centers, many researchers have developed various models for their operational planning and scheduling. However, most of the models just provide static plans without any risk measures as their results, and thus the users often lose the opportunity to analyze how much risk the patients have, whether the plan is still implementable or how the plan should be changed when an unexpected event happens. In this study, we construct a simulation model combined with a risk-based planning and scheduling module designed by Simio LLC. In addition to static schedules, it provides possibility of treatment delay for each patient as a risk measure, and updates the schedule to avoid the risk when it is needed. By using the simulation model, the users can experiment various scenarios in operations quickly, and also can make a decision not based on their past experience or intuition but based on scientific estimation of risks even in urgent situations. An example of such an operational decision making process is demonstrated for a real mid-size emergency medical center located in Seoul, Republic of Korea. The model is designed for temporal short-term planning especially, but it can be expanded for long-term planning also with some appropriate adjustments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.692-699
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• 2008

Semiconductor research and development(R&D) fabs are very different than production fabs in many ways such as the scales of production, job priority, production methods, and performance measures. Efficient operations of R&D fabs are very important to the development of new product, process stability, high yield, and ultimately company competitiveness. This paper proposes the fab-wide scheduling method for operational optimization of the R&D fabs. Most scheduling systems of semiconductor fabs have only focused on maximizing throughput of each separated areas without considering WIP(works in process) flows of entire fab. In this paper, we proposes the a fab-wide scheduling system which schedules all lots to entire fab equipment at once. We develop the MIP(mixed integer programing) model which allocates the lots to production equipment considering many constraints of all processes and the CP(constraint programming) model which determines the sequences of the lots in the production equipment. The proposed FAB-wide scheduling model is applied to the newly constructed R&D fab. As a result, we have accomplished the system based automated job reservation, decrease of the hot lot delay, increase of the queue time satisfaction, the high throughput by maximizing the batch sizes, decrease of the WIP TAT(Turn Around Time).

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.315-319
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• 2020

The modern transportation and mobility sector is expected to encounter high penetration of Electric Vehicles (EVs) because EVs contribute to reducing the harmful emissions from fossil fuel-powered vehicles. With the prospective growth of EVs, sufficient and convenient facilities for fast charging are crucial toward satisfying the EVs' quick charging demand during their trip. Therefore, the Fast Electric Vehicle Charging Stations (FECS) will be a similar role to gas stations. In this paper, we study a charging scheduling problem for the FECS with solar photovoltaic (PV) and an Energy Storage System (ESS). We formulate an optimization problem that minimizes the operational costs of FECS. There are two cost and one revenue terms that are buying cost from main grid power, ESS degradation cost, and revenue from the charging fee of the EVs. Simulation results show that the proposed scheduling algorithm reduces the daily operational cost by effectively using solar PV and ESS.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.102-105
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• 1993

The objective of this study is to solve the operation scheduling problem of plural battery energy storage systems (BESS), and to find useful intonation from its result. Unlike conventional energy storage system, BESS has on hardware characteristics such as high efficiency, fast-acting response and operational loss. Considering rate constraints of thermal unit power as well as hardware characteristics of BESS, the operation scheduling has an intricated problem. In order to solve this optimization problem, we use successive approximations dynamic programming. In two types of operation, the proposed algorithm is applied to test system. one is daily optimal operation, the other weekly optimal operation.