• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.4
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• pp.441-446
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• 2013

A thermal model of power modules based on the physical dimension and thermal properties is proposed in this paper. The heat path in the power module is considered as a one-dimensional heat transfer in the model. The method of the parameters extraction for the model is given in the paper. With high speed and accuracy, the thermal model is suit for electrothermal simulation. The proposed model is verified by experimental results.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.4
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• pp.1-16
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• 2011

It is important not only to introduce the C4I(Command and Control, Communication, Computer, Intelligence) system for realizing the NCW(Network Centric Warfare) but also to evaluate the synergistic effect by the C4I system. However, the study effort for evaluating the system's synergistic effect is insufficient compared with introducing the system. Therefore, in this paper, we proposed a model that measures the synergistic effect of combat power by the warfare information system. To measure the synergistic effect of warfare information system, the network power must be considered, so we also proposed a new methodology for measurement of network power based on SNA(Social Network Analysis), not Metcalfe's law. A model we proposed is a model that measures the raised combat power by the network effectiveness. The methodology and model we proposed in this paper will be used usefully to analyze the practical effect of constructing future warfare information system.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.337-347
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• 2008

Based on social welfare maximum theory, the optimal scale of power plants entering generation power market being is researched. A static non-cooperative game model for short-term optimization of power plants with different cost is presented. And the equilibrium solutions and the total social welfare are obtained. According to principle of maximum social welfare selection, the optimization model is solved, optimal number of power plants entering the market is determined. The optimization results can not only increase the customer surplus and improve power production efficiency, but also sustain normal profits of power plants and scale economy of power production, and the waste of resource can also be avoided. At last, case results show that the proposed model is efficient.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.1
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• pp.83-88
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• 2018

Engineering is a sector with more than three times the industrial effectiveness of manufacturing. In the domestic engineering life cycle, the Operations & Maintenance (O&M) phase is a relatively high level of technology. Based on accumulated knowledge of O&M phase, it is necessary to advance operating technology and expand overseas O&M market expenditure. This study is the early stage of knowledge-based power plant O&M service framework reference model. In this study, we propose a conceptual model of architecture framework for power plant O&M. We survey the architecture framework and reference model and propose conceptual model of architecture framework for power plant O&M. The conceptual model of architecture framework for power plant O&M consists of stakeholder, O&M scenario, O&M technology. In particular, the O&M technology is defined as the fourth industrial revolution intelligence information technology. We defined a meta model from the conceptual model to define the power plant O&M architecture framework. In the future, we intend to development an architecture framework from the conceptual model and meta model.

• East Asian mathematical journal
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• v.37 no.5
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• pp.567-576
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• 2021

In this paper, we deal with the pricing of vulnerable power exchange option. We consider the hybrid model as the credit risk model. The hybrid model consists of a combination of the reduced-form model and the structural model. We derive the closed-form pricing formula of vulnerable power exchange option based on the change of measure technique.

• Journal of Korean Port Research
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• v.14 no.1
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• pp.57-64
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• 2000

For composing the structure model of national maritime power system by system structural modeling, in this study, the 50 basic factors are selected by survey of the extensive and through literatures on maritime, sea, maritime power and sea power. And the basic factors are classified into 36 component factors by cluster method. The 9 attributes are extracted by the application of the principle component analysis method, one of the factor analysis method in system engineering, to component factors. In this study, we define the attributes composing the national maritime power system by integrating the result of this study and existed our studies relating to this topic. Which are showed in Table 2. and we show the structure model of national maritime power system in Fig. 3. In Table 2, the 9 attributes are as follows : the fundamental power of maritime, shipping and port power, naval power, fishing power, shipbuilding power, the power of ocean research and development, dependency on seaborne trade, the protection power of ocean environment and the will and inclination of govemment. Also, in the case of evaluating this system, we conform the importance of considering the interactions among the attributes which have strong interactions in structure model of national maritime power system.

• Korean Journal of Mathematics
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• v.17 no.4
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• pp.399-409
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• 2009

We study the weak convergence of various models to Fractional Brownian motion. First, we consider arima process and ON/OFF source model which allows for long packet trains and long inter-train distances. Finally, we figure out power spectrum density as a Fourier transform of autocorrelation function of arima model and binary signal model.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.63-75
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• 2002

To improve the efficiency of the electric power generation, monthly maximum electric power consumptions for a next one year should be forecasted in advance and used as the fundamental input to the yearly electric power-generating master plan, which has a greatly influence upon relevant sub-plans successively. In this paper, we analyze the past 22-year hourly maximum electric load data available from KEPCO(Korea Electric Power Corporation) and select necessary data from the raw data for our model in order to reflect more recent trends and seasonal components, which hopefully result in a better forecasting model in terms of forecasted errors. After analyzing the selected data, we recommend to KEPCO the Winters' multiplicative model with decomposition and exponential smoothing technique among many candidate forecasting models and provide forecasts for the electric power consumptions and their 95% confidence intervals up to December of 1999. It turns out that the relative errors of our forecasts over the twelve actual load data are ranged between 0.1% and 6.6% and that the average relative error is only 3.3%. These results indicate that our model, which was accepted as the first statistical forecasting model for monthly maximum power consumption, is very suitable to KEPCO.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.409-413
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• 2016

The 500 MW rated steam turbine model in coal fired power plant is developed to be used for validation and verification of controller rather than for the education of operator. The valve, steam turbine, reheater and generator are modeled and integrated into the simulator. And the data from the plant heat balance diagram are used for estimation of the model parameters together with actual operating data. It is found that the outputs of model such as pressure, temperature and speed are similar to the operating ones. So, it is expected that the developed model will play a very big role in controller development.