• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1330-1333
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• 2004

The methodology for modeling building energy consumption is well established for energy saving calculation in the temperate zone both for performance-based energy retrofitting contracts and measurement and verification (M&V) projects. Mostly, statistical regression models based on utility bills and outdoor dry-bulb temperature have been applied to baseline monthly and annual whole building energy use. This paper presents the application of neural networks (NN) to model landlord energy consumption of commercial buildings in Singapore. Firstly, a brief background information on NN and its application on the building energy research is provided. Secondly, five commercial buildings with various characteristics were selected for case studies. Monthly mean outdoor dry-bulb temperature ($T_0$), Relative Humidity (RH) and Global Solar Radiation (GSR) are used as network inputs and the landlord monthly energy consumption of the same period is the output. Up to three years monthly data are taken as training data. A forecast has been made for another year for all the five buildings. The performance of the NN analysis was evaluated using coefficient of variance (CV). The results show that NNs is powerful at predicting annual landlord energy consumption with high accuracy.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.613-624
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• 2021

This paper analyzes the relationship between income distribution and energy consumption from a Pareto optimal approach. For this purpose, the causality relationship between electricity consumption per capita (kWh) with respect to country groups and energy consumption per capita (kg of oil equivalent) along with gross domestic product per capita was analyzed. In addition to this purpose, a Pareto analysis was conducted to determine the countries with the highest per capita national income, how much of the world total energy they consume, and whether the law of power in the energy and electricity markets exists. Finally, the impact of official development assistance provided to low-income countries by high-income countries on the low-income countries' electricity and energy consumption was analyzed. In other words, it was questioned whether pareto redistribution policies serve the purpose or not. The Engle-Granger causality approach was used in the analysis of the causality relationship between variables. Our analysis indicated that, first, the energy data of the country groups may be inadequate in revealing income inequalities. Second, the existence of Pareto law of power and global income inequality can be explained based on energy data. Finally, Pareto optimal redistribution policies to eliminate income inequality remain inadequate in practice.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.49-54
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• 2010

Most energy using in building part is mainly consumed for heating and cooling to meet occupancy's comfort temperature. Generally, heating energy consumption show high value than cooling energy in Korea because of high temperature difference in winter season as compared with summer in apartment building. The efforts to develope mechanical performance have been studied to reduce energy consumption in building energy field until now. However, the energy consumption in building is impacted by not only system performance but also PMV particularly at temperature and Clo value. This means that energy consumption can be changed by occupancy's comfort setting temperature in apartment building. This study investigated the passibility of overheating in apartment building by occupant' slow Clo and its setting temperature from preceding research and then the heating energy consumption by setting temperature was calculated with ESP-r. The effects of heating energy and $CO_2$ reduction are also evaluated quantitatively with Clo value. The results showed that keeping ISO-7730 standards can reduce heating energy up to 21% in compared with option 2; also, wearing underclothes with ISO-7730 standard can considerably reduce heating energy consumption up to 50%. As compared with option 2, the reduction of $CO_2$ emission for option 3 showed 0.63TCO2 of kerosene, 0.49TCO2 of LNG and 1.09TCO2 of electricity. The option 4 can be reduced by 1.48TCO2 of kerosene, 1.16TCO2 of LNG and 2.57TCO2 of electricity respectively.

• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.451-460
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• 2013

This paper presents the necessary elements and data flow in developing a monitoring system of energy usage for apartment houses with a Smart TV. Energy consumption data in each home are collected and analyzed in the HUB station by way of measuring instruments. And the amount of energy usage, such as electricity, gas, hot water, heating, water and other utilities are displayed through the Smart TV application. Energy consumption Database in the HUB station are processed and displayed in the browser of a Smart TV through XML, JAVASCRIPT and Flash. Smart TV users can get the energy consumption status through the energy consumption analysis display of the Smart TV application and improve the energy efficiency by comparing the usage patterns with neighboring houses. And the application display energy usage information, consumption ranking, rates to user as well. Furthermore, usage of last month or year can be compared to help to reduce the energy usage. The proposed system can provide the information about the amount of energy use to be reduced and the warning on the waste of energy.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.12
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• pp.1092-1101
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• 2002

The objective of this study is to develop energy saving strategies for indoor swimming pools and to estimate the effect of each energy saving strategy. For this purpose, field measurements regarding pool water heating energy, domestic hot water heating energy are conducted and a base energy consumption model is implemented using the DOE-2.1E program. The results of the study reveal that 25% of the total pool water heating energy may be saved by using night time pool covers, 27% of the total domestic hot water heating energy may be saved by using a waste water heat recovery system (effic. 60%), and of the total ventilation energy may be saved using an exhaust air heat recovery system (effic. 60%).

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.10 no.2
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• pp.7-12
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• 2014

Government has recently restricted heating and cooling set temperatures for the commercial and public buildings due to increasing national energy consumption. The goal of this paper is to visualize a future two way indoor set temperature control impact on building energy consumption by using TRNSYS simulation modeling. The building was modelled based on the twin test cell with the same dimension. Air source ground coupled heat pump performance data has been used for modeling by TRNSYS 17. Daejeon weather data has been used from Korea Solar Energy Society. The heating set temperature in the reference room is $24^{\circ}C$ as well as the target room set temperature are $23^{\circ}C$, $22^{\circ}C$, $21^{\circ}C$ and $20^{\circ}C$. The cooling set temperature of the reference room is also $24^{\circ}C$ as well as the target room set temperature of $25^{\circ}C$, $26^{\circ}C$, $27^{\circ}C$ and $28^{\circ}C$. For the air source heat pump system, heating season energy consumption is $35.52kWh/m^2y$ in the reference room. But the heating energy consumption in the target room is reduced to 7.5% whenever the set temperature decreased every $1^{\circ}C$. The cooling energy consumption in the reference room is $4.57kWh/m^2y$. On the other hand, the energy consumption in the target room is reduced to 22% whenever the set temperature increased every $1^{\circ}C$ by two way controller. For the geothermal heat pump system, heating energy consumption in the reference room is reduced to 20.7%. The target room heating energy consumption is reduced to 32.6% when the set temperature is $22^{\circ}C$. The energy consumption in the target room is reduced to 59.5% when the set temperature is $26^{\circ}C$.

• Journal of the Korean Institute of Educational Facilities
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• v.18 no.5
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• pp.13-21
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• 2011

In case of school buildings, energy consumption has been noticeably on the increase, along with the changes in outdoor temperature triggered by the improvement in national economic development and educational environments. Research on the characteristics of energy consumption in school buildings influenced by the changes in outdoor temperature is considered very significant in social aspects in that it will be fundamental to the suggestion of the alternatives, such as saving energy consumption in construction buildings and control of emitting carbon dioxide. In this regard, this study examined sensitivity to temperature of power consumption in school buildings, based on the changes of outdoor temperature for the past five years in the target buildings of elementary, middle and high schools and the amount of energy consumption. From the results, it has been believed that this study was very significant in terms of figuring out a quantitative, optimum level of energy consumption, maintenance of pleasant environments and functions, and the necessity of effective energy use and management in school buildings.

• Journal of Environmental Policy
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• v.12 no.3
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• pp.97-122
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• 2013

The ARDL(Autoregressive Distributed Lag) method is employed analyzes the long-run equilibrium relationships among environmental pollution($CO_2$ emissions) per capita, income levels per capita, and energy consumption per capita. The error correction model is employed to analyze the short-term effects of income and energy consumption on $CO_2$ emissions. The Toda-Yammamoto method is employed for causal analysis among the three variables. The results show that income levels, energy consumption, and $CO_2$ emissions are cointegrated. We found the N type relationship between income and $CO_2$ emissions. Long-term elasticities of income and energy consumption with respect to $CO_2$ emission were greater than their short-term elasticities. There were a bilateral causality between energy consumption and $CO_2$ emissions. There was a unilateral causality from $CO_2$ emissions to income and from energy consumption to income not vice versa. Energy consumption can be an important variable to contribute to forecasting $CO_2$ emissions.

• Journal of Drive and Control
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• v.17 no.2
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• pp.38-44
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• 2020

Various efforts have been initiated to reduce the energy consumption of the compressor as it is one of the approaches to saving a large portion of the fixed cost of the production site. Various results of reducing the energy consumption of the compressor have been reported, but to reduce the energy consumption of the compressors fundamentally, regular management of the compressor should ensure optimum operation. This requires periodic on-site visits by experts, but is often overlooked as a cost issue, resulting in the use of the compressor in low-efficiency conditions. Thus, it is necessary to develop a low-cost evaluation technology for compressor condition monitoring and efficiency analysis to ensure that the compressor is always driven at the optimum efficiency without imposing undue burden on the compressor user. In this study, a sensor was installed at the inlet, outlet, and power supply of the compressor, and a method for evaluating the energy consumption of the compressor using the minimum sensor was derived. The experimental results are presented to show the validity of the proposed method. It was confirmed that the energy consumption of the compressor can be easily as well as efficiently evaluated by using the method developed in this study.

• Journal of People, Plants, and Environment
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• v.22 no.2
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• pp.219-229
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• 2019

This study was carried out to verify the accuracy of fitness tracking devices in monitoring heart rate and energy consumption and to contribute to the development of a forest exercise program that can recommend the intensity and amount of forest exercises based on personal health-related data and provide monitoring and feedback on forest exercises. Among several commercially available wearable devices, Fitbit was selected for the research, as it provides Open API and data collected by Fitbit can be utilized by third parties to develop programs. Fitbit provides users with various information collected during forest exercises including exercise time and distance, heart rate, energy consumption, as well as the altitude and slope of forests collected by GPS. However, in order to verify the usability of the heart rate and energy consumption data collected by Fitbit in forest, the accuracy of heart rate and energy consumption were verified by comparing the data collected by Fitbit and reference. In this study, 13 middle-aged women were participated, and it was found that the heart rate measured by Fitbit showed a very low error rate and high correlation with that measured by the reference. The energy consumption measured by Fitbit was not significantly different from that measured in the reference, but the error rate was slightly higher. However, there was high correlation between the results measured by Fibit and the reference, therefore, it can be concluded that Fitbit can be utilized in developing actual forest exercise programs.