• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.187-200
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• 1998

This paper presents an original approach for solving short-term power scheduling in extended power system with two fuels in a unit and a limited fuel using Lagrangian relaxations. The underlying model incorporates the full set of costs and constraints including setup, production, ramping, and operational status, and takes the form of a mixed integer nonlinear control problem. Moreover, the mathematical model developed includes two fuels in a unit and a limited fuel, regulation reserve requirements of prespecified group of units. Lagrangian relaxation is used to disaggregate the model by generator into separate subproblems which are then solved with a nested dynamic program including empirical knowledges. The strength of the methodology lies partially in its ability to construct good feasible solutions from information provided by the dual. Thus, the need for branch-and-bound is eliminated. In addition, the inclusion of two fuels in a unit and a limited fuel provides new insight into the limitations of current techniques. Computational experience with the proposed algorithm indicates that Problems containing up to 23 units including 8 unit used two fuels and 24 time periods can be readily solved in reasonable times. Duality gaps of less than 4％ were achieved.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.10-14
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• 2001

We studied the use of time-related information, with and without prediction, to support human operators performing moni-toring and control tasks in the process. Based on monitoring and control techniques used for Project Management we developed a display design for the process industries. A simulated power plant was used to test the hypothesis that availability of predictions along with information on past trends can improve the performances of the human operator handling faults. Several designs of dis-plays were tested in the experiment in which human operators had to detect and handle two types of faults(local and systems wide) in the simulated electricity generation process. Analysis of the results revealed that temporal data, with and without prediction, signifi-cantly reduced response time. Our results encourage the integration of temporal information and prediction in displays used for the control processes to enhance the capabilities of the human operators. Based on the analysis we proposed some guidelines for the de-signer of the human interface of a process control system.

• Asian Oncology Nursing
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• v.5 no.1
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• pp.3-10
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• 2005

Back ground: Nurses now occupy one third of all hospital human resources. Therefore, efficient management of nursing manpower is getting more important. While it is very clear that nursing workload requirement analysis and patient severity classification should be done first for the efficient allocation of nursing workforce, these processes have been conducted manually with ad hoc rule. Purposes: This study was tried to make a predict model for patient classification according to nursing need. We tried to find the easier and faster method to classify nursing patients that can help efficient management of nursing manpower. Methods: The nursing patient classifications data of the hospitalized cancer patients in one of the biggest cancer center in Korea during 2003.1.1-2003.12.31 were assessed by trained nurses. This study developed a prediction model and analyzing nursing needs by data mining techniques. Patients were classified by three different data mining techniques, (Logistic regression, Decision tree and Neural network) and the results were assessed. Results: The data set was created using 165,073 records of 2,228 patients classification database. Main explaining variables were as follows in 3 different data mining techniques. 1) Logistic regression : age, month and section. 2) Decision tree : section, month, age and tumor. 3) Neural network : section, diagnosis, age, sex, metastasis, hospital days and month. Among these three techniques, neural network showed the best prediction power in ROC curve verification. As the result of the patient classification prediction model developed by neural network based on nurse needs, the prediction accuracy was 84.06%. Conclusion: The patient classification prediction model was developed and tested in this study using real patients data. The result can be employed for more accurate calculation of required nursing staff and effective use of labor force.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.137-147
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• 2008

Recently, Power and thermal management are becoming major concerns in computer system design. The energy efficiency is an important attribute of the mobile and embedded systems. Today's powerful mobile processors needs more energy and longer battery life. Many research has been focused to reduce energy consumption for the mobile processors.In this paper, performance monitoring system for the Power-management techniques is implemented for Intel's XScale microarchitecture-based Marvell PXA320 processor on Windows CE platform. It also provides software interface for changing DVFS configuration. Performance and power consumption are measured for benchmark programs through performance counter value and voltage/current measurements on LabVIEW platform. By using the developed monitoring system, it is possible for dynamic power management to track processor's workload and to determine the actual power consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5904-5927
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• 2019

Many artificial intelligence (AI) techniques have been embedded into various engineering technologies to assist them in achieving different goals. The integration of modern technologies with energy consumption management system and occupant's comfort inside buildings results in the introduction of intelligent building concept. The major aim of this integration is to manage the energy consumption effectively and keeping the occupant satisfied with the internal environment of the building. The last few couple of years have seen many applications of AI techniques for optimizing the energy consumption with maximizing the user comfort in smart buildings but still there is much room for improvement in this area. In this paper, a hybrid of two AI algorithms called firefly algorithm (FA) and genetic algorithm (GA) has been used for user comfort maximization with minimum energy consumption inside smart building. A complete user friendly system with data from various sensors, user, processes, power control system and different actuators is developed in this work for reducing power consumption and increase the user comfort. The inputs of optimization algorithms are illumination, temperature and air quality sensors' data and the user set parameters whereas the outputs of the optimization algorithms are optimized parameters. These optimized parameters are the inputs of different fuzzy controllers which change the status of different actuators according to user satisfaction.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1390-1396
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• 2013

The paper estimated the reasonable market price of lead-acid battery energy storage system (BESS) intended for demand management of electricity customers. As time-of-use (TOU) tariffs have extended to a larger number of customers and gaps in the peak and off-peak rates have gradually risen, deployment of BESS has been highly needed. However, immature engineering techniques, lack of field experiences and high initial investment cost have been barriers to opening up ESS markets. This paper assessed electricity cost that BESS operation could save for customers and, based on the possible cost savings, estimated reasonable prices at which BESSs could become a more prospective option for demand management of customers. Battery scheduling was optimized to maximize the electricity cost savings that BESS would possibly achieve under TOU tariffs conditions. Basic economic factors such as payback period and return on investment were calculated to determine reasonable market prices. Actual load data of 12 industrial customers were used for case studies.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.2
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• pp.202-207
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• 2014

Recently, the study of energy saving technology of ships begins in earnest, as energy saving policies are performed all around the world. SEMS (Ship Energy Management System) is one of the techniques to increase energy efficiency by applying to a independent system like a ship and offshore. SEMS is composed of Cooling Pump Control System (CPCS), Renewable Energy Emergency Power Control System (REEPCS), Load Control System (LCS), and Heating, Ventilation, and Air Conditioning System (HVACS). SEMS is enable to increase energy efficiency and achieve integrated management through the interlocking of each system. Especially, it is possible to improve the flexibility of the selection of the generator capacity in conjunction with a rechargeable battery and renewable energy. In this paper, SEMS applied rechargeable battery is proposed and simulated. By applying the rechargeable battery, it was confirmed that SEMS applied rechargeable battery can be operated at optimum efficiency of the generator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1560-1566
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• 2015

To enable the efficient use of energy, the environment where unscheduled receivers can harvest energy from the transmitted signal is considered in next-generation wireless communication systems. In this paper, we propose a scheme for allocating subchannel and power to maximize the system throughput and harvested energy simultaneously using optimization techniques. Through simulations, we verify that the proposed scheme can increase the system throughput and harvested energy harmoniously. In particular, the proposed scheme improves the harvested energy remarkably with a negligible degradation of system throughput, compared with conventional scheme, as a result, energy can be used efficiently in the system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.242-247
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• 2010

This paper introduces a real-time load flow program for Korean energy management system(EMS). This study is concentrated on the following aspects. First, we propose the model of the real-time database and power system equipment for the real-time load flow. These models are extracted from the needs of load flow functions and are designed to the application common information. Second, several techniques are applied for the efficient convergence and computational speed. The generation/load mismatch is redistributed using generator participation factors which are separated to the reference bus. For the voltage control, the jacobian matrix is composed with the basic Y matrix elements and the voltage control elements. Through the optimally ordering, jacobian row and column for a column is changed. However all jacobian matrix entries have same order with the Y matrix. The proposed program is tested using the Korea Electric Power Corporation(KEPCO) system. Through the test, we verified that the proposed program can be effectively used to accomplish the Korean EMS system.

• International Journal of Safety
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• v.3 no.1
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• pp.38-46
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• 2004

This paper introduces the software life-cycle V&V (verification and validation) tasks for the KNICS (Korea nuclear instrumentation and control system) project. The objectives of the V&V tasks are mainly to develop a programmable logic controller (PLC) for safety critical instrumentation and control (I&C) systems, and then to apply the PLC to developing the prototype of an engineered safety features-component control system (ESF-CCS) in nuclear power plants. As preparative works for the software V&V, various kinds of software plans and V&V task procedures have been developed according to the software life-cycle management. A number of software V&V tools have been adopted or developed to efficiently support the V&V tasks. The V&V techniques employed in this work include a checklist-based review and inspection, a requirement traceability analysis, formal verification, and life-cycle based software testing.