• Journal of Digital Convergence
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• v.14 no.6
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• pp.457-466
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• 2016

To achieve eco-friendly hospitals it is necessary to empirically verify the effect of meteorological factors on the power consumption of the hospital. Using daily meteorological big data from 2009 to 2013, we studied the weather conditions impact to power consumption and analyzed the patterns of power consumption of two hospitals. R analysis revealed that temperature among the meteorological factors had the greatest impact on the hospital power consumption, and was a significant factor regardless of hospital size. The pattern of hospital power consumption differed considerably depending on the hospital size. The larger hospital had a linear pattern of power consumption and the smaller hospital had a quadratic nonlinear pattern. A typical pattern of increasing power consumption during a hot summer and a cold winter was evident for both hospitals. The results of this study suggest that a hospital's functional specificity and meteorological factors should be considered to improve energy savings and eco-friendly building.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.587-594
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• 2018

The purpose of this study is to propose a power demand volatility evaluation system based on LSTM and not to verify the accuracy of the demand module which is a core module, but to recognize the sudden change of power pattern by using deeplearning in the actual power demand monitoring system. Then we confirm the availability of the module. Also, we tried to provide a visualized report so that the manager can determine the fluctuation of the power usage patten by applying it as a module to the web based system. It is confirmed that the power consumption data shows a certain pattern in the case of government offices and hospitals as a result of implementation of the volatility evaluation system. On the other hand, in areas with relatively low power consumption, such as residential facilities, it was not appropriate to evaluate the volatility.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.6
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• pp.85-88
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• 2009

This paper shows a reasonable power density, that was made by the systematic and statistical way considering actual conditions, such as investigated power consumption capacity for the year and peak power, contract power for the last 5 years of each customer for 23 general customers all data obtained by AMR. In this dissertation, it is necessary to analyze the key features from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and load factor.

• Journal of Energy Engineering
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• v.7 no.2
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• pp.223-230
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• 1998

Energy consumption statistics have been surveyed for 50 large commercial buildings with high energy consumption records in Seoul City. The buildings were classified into three different groups for data analysis: hospitals, hotels, and department stores/office buildings. The analysis was focused on identifying installed boiler and refrigerator data, energy consumption rates, and energy load distribution throughout the year. Refrigerating electricity was confirmed again to affect most on the formation of the summer electricity load peak as expected. Replacing the refrigerator electricity peak in the summer with co-generation in large commercial buildings. However, overall heat load distribution in a single building is still considered not large enough for economically feasible co-generation and thus joint co-generation for multiple neighboring buildings are preferred and the Electric Power Law and LNG pricing policy should be revised favorably for co-generation in advance.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.422-430
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• 2018

Increase in oil prices and building energy consumption has been a great burden for Korea which has significant energy dependence on foreign energy sources. In this context, reduction of building energy consumption, which comprises 40% of total energy consumption, is a very important issue. This research therefore empirically analyzed a hospital "P" that implemented ICT-based energy consumption and cost reduction initiative. The hospital first replaced existing water absorber for heating/cooling air and boiler for heating water with water heat storage heat pump system. This was accompanied by subscribing to different electricity price plans to maximize cost reduction. Secondly, the hospital additionally applied ICT-based optimized control algorithm that considers surrounding factors (external temperature, changes in energy demand). The analysis of these mechanisms indicate that the ICT-based energy consumption and cost reduction initiative for hospitals can reduce energy consumption by 53.6% with replacement of low-efficiency equipment and additionally by 18.2% with optimized control algorithm. The mechanisms will provide energy consumption reduction opportunities for other hospitals and buildings with high energy consumption.