• Journal of Power System Engineering
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• v.3 no.1
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• pp.38-44
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• 1999

Subway is one of the most important transportation and its facilities are increased by the drift of population to cities in these days. But heat generation results from lighting, human and traffic increase in subway, half-closed space, gives uncomfortable sense to the subway passengers. Therefore, natural ventilation by piston effect is done to relieve uncomfortable sense. But train wind by piston effect gives uncomfortable sense to the subway passengers, too. So the numerical calculation of inflow and outflow amounts is important to predict thermal environment and reduce train wind. In case of actual survey of train wind in target station, the amount of train wind are about $3100m^3/train$ at the minimum, about $6000m^3/train$ at the maximum, about $4200m^3/train$ on average. When comparison between simulation for train wind prediction and actual survey for accuracy was done train wind prediction program showed similar results.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.157-165
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• 2022

As the stock market is affected by various circumstances including economic and political variables, predicting the stock market is considered a still open problem. When combined with corporate financial statement data analysis, which is used as fundamental analysis, and technical analysis with a short data generation cycle, there is a problem that the time domain does not match. Our proposed method, LSTE the operating profit and market outlook of a petrochemical company and estimates the sales and operating profit of the company, it was possible to solve the above-mentioned problems and improve the accuracy of stock price prediction. Extensive experiments on real-world stock data show that our method outperforms the 8.58% relative improvements on average w.r.t. accuracy.

• KIEAE Journal
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• v.14 no.1
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• pp.67-74
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• 2014

There have distinctly been no the installation criteria and maintenance management of BIPV systems, although the BIPV market is consistently going on increasing. In addition, consideration of the BIPV generation quantity which has been installed at several diverse places is currently almost behind within region in Korea. Therefore, the main aim of this study is to evaluate the BIPV generation and to be base data of reducing rate depending on regional installation angles using PVpro which was verified by measured data. Various conditions were an angle of inclination and azimuth under six major cities: Seoul, Daejeon, Daegu, Busan, Gwangju, Jeju-si for the BIPV system generation analysis. As the results, Seoul showed the lowest BIPV generation: 1,054kWh/kWp.year, and Jeju-si have 5percent more generation: 1,108.0kWh/kWp.year than Seoul on horizontal plane. Gwangju and Daejeon turned out to have similar generation of result, and Busan showed the highest generation: 1,193.5kWh/kWp.year, which was increased by over 13percent from Seoul on horizontal plane. Another result, decreasing rate of BIPV generation depending on regional included angle indicate that the best position was located on azimuth: $0^{\circ}$(The south side) following the horizontal position(an angle of inclination: $30^{\circ}$). And the direction on a south vertical position(azimuth: $0^{\circ}$, an angle of inclination: $90^{\circ}$) then turned out reducing rate about 40percent compared with the best one. Therefore, these results would be used to identify the installation angle of the BIPV module as an appropriate position.

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.183.1-183
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• 2001

• Polymer Science and Technology
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• v.21 no.1
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• pp.41-44
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.359-360
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• 2010

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.95-100
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• 2014

To solve the problem of conventional fossil energy, utilization of renewable energy is growing rapidly. Solar energy as an energy source is infinite, and a variety of research is being conducted into its utilization. To change solar energy into electrical energy, we need to build a solar power plant. The efficiency of such a plant is strongly influenced by meteorological factors; that is, its efficiency is determined by solar radiation. However, when analyzing observed generation data, it is clear that the generated amount is changed by various factors such as weather, location and plant efficiency. In this paper, we proposed a solar power generation prediction algorithm using geographical factors such as latitude and elevation. Hence, changes in generated amount caused by the installation environment are calculated by curve fitting. Through applying the method to calculate this generation amount, the difference between real generated amount is analyzed.

• Current Photovoltaic Research
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• v.5 no.1
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• pp.33-37
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• 2017

Today, photovoltaic power generation mostly uses Si crystalline solar cell modules. The most vulnerable part of the Si solar cell module is that the power generation decreases due to the temperature rise. But, it is widely used because of low installation cost. In the solar market, where Si crystalline solar cell modules are widely used. The CPV (Concentrated Photovoltaic) module appeared in the solar market. The CPV module reduces the manufacturing cost of the solar cell by using non-Si in the solar cell. Also, there is an advantage that a rise in temperature does not cause a drop in power generation. But this requires high technology to install and has a disadvantage that the initial installation cost is expensive compared to normal Si solar cell module. So that we built a testbed to see these characteristics. The testbed was used to measure the amount of power generation in a long-term outdoor environment and compared with the general Si solar cell module.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.95-105
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• 2000

The Purpose of this study is to present a new Trip Generation Model using Backpropagation Neural Networks. For this purpose, it is compared the performance between existing linear/nonlinear Regression models and a new TriP Generation model using Neural Networks. The study was performed according to the below. First, it is analyzed the limits of conventional Regression models, next Proved the superiority of Neural Networks model in theoretical and empirical aspects, and lastly Presented a new approach of Trip Generation methodology. The results show that Backpropagation Neural Networks model is predominant in estimation and Prediction comparable to Regression analysis. Such results mean the possibility of Neural Networks\` application in Trip Generation modeling. Specially under the circumstances of the chancing transportation situations and unstable transportation on vironments, its application in transportation fields will be extended.