• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.305-310
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• 2012

In 2009, The Ministry of Land, Transport and Maritime Affairs, Korea opens apartment maintenance fee to public in "Apartment Management Info System". The high energy consumption component of apartment, which is hot water, water, electricity and heating, is released to public on this system. Through this system, apartment energy consumption and greenhouse gas emissions data can be compiled and expected to be accurately analyzed. Energy consumption and greenhouse gas emissions statistics of the apartment are collected being made to reduce energy and gas emissions. However, The accurate survey of energy consumption trends have not been accomplished. The energy consumption and greenhouse gas emissions survey in Apartment should be made first in order to reduce energy consumption. and then the correlation factors analysis which is affecting energy consumption is required. The purpose of this study is to analyze energy consumption characteristics of apartment in Bundann-gu, Seongnam, Korea in monthly, unit area and building built year basis. And then the research can be used as the basis of policy to Reduce energy consumption and greenhouse gas emissions.

• Journal of the Ergonomics Society of Korea
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• v.4 no.2
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• pp.25-31
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• 1985

Mechanical energy consumption during human running was studied. The subject was modeled by an eleven segment planar open linkage system and analyzed by Newtonian equations of motion from film data with a sampling rate of 50 Hz. The motion data from films were smoothed by lower 7 harmonics before analysis. And this study was tried for a normal male subject running on a concrete floor. The mechanical energy consumption was evaluated from the five different criteria suggested by others and a joint energy consumption criterion newly devised based on the muscle contraction.

• 월간 기계설비
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• s.127
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• pp.40-50
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• 2001

The study focused on the analysis of energy consumption of hotel in Jeju. For this study, we regionally investigated the energy consumption in Jeju and Seogwipo by questionnaires. Based on the fundamental data, we classified the energy consumption accordi

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2029-2046
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• 2016

Energy consumption is an important index in mobile ad hoc networks. Data packet transmission increases among nodes, particularly in big data communication. However, nodes may be unable to transmit data packets because of energy over-consumption. Consequently, information may be lost and network communication may block. While opportunistic network is a kind of mobile ad hoc networks, researchers do not focus on energy consumption in opportunistic network communication. This study proposed an effective sensor energy supply scheme that can be applied in opportunistic networks. This scheme considers nodes sensor requests and communication model. In this scheme, nodes do not only accomplish energy supply in communication, but also extend communication time in opportunistic networks. Compared with the Spray and Wait algorithm and the Binary Spray and Wait algorithm in simulations, the proposed scheme extends communication time, increases data packet transmission, and accomplishes energy supply among nodes.

• Journal of Energy Engineering
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• v.22 no.1
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• pp.38-43
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• 2013

There was a dire need to compile data about energy consumption data by use to analyze residential energy consumption patterns relating to changes in lifestyles, or changes in life behavior. Accordingly, bottom-up model for residential energy consumption by residential use was developed by life behavior classification in an attempt to analyze energy consumption. This paper multiplied each appliance's running times by each appliance by life behavior and built a residential bottoms-up model to figure out the energy consumption of each household. The uses by life behavior were broken down into lighting, heating, cooling, entertainment, obtaining information, hygiene, and cooking.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.10a
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• pp.279-283
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• 2009

Distributed generation(DG) of combined cooling, heat. and power(CCHP)has been gaining momentum in recent year as efficient, secure alternative for meeting increasing energy demands. This paper presents the energy performance of microturbine CCHP system equipped with an absorption chiller by modelling it in hospital building. The orders of study were as following. 1)The list and schedule of energy consumption equipment in hospital were examined such as heating and cooling machine, light etc. 2) Annual report of energy usage and monitoring data were examined as heating, cooling, DHW, lighting, etc. 3) The weather data in 2007 was used for simulation and was arranged by meteorological office data in Daejeon. 4) Reference simulation model was built by comparison of real energy consumption and simulation result by TRNSYS and ESP-r. The energy consumption pattern of building were analyzed by simulation model and energy reduction rate were calculated over the cogeneration. As a result of this study, power generation efficiency of turbine was about 30% after installing micro gas turbine and lighting energy as well as total electricity consumption can be reduced by 40%. If electricity energy and waste heat in turbine are used, 56% of heating energy and 67% of cooling energy can be reduced respectively, and total system efficiency can be increased up to 70%.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.6
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• pp.15-22
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• 2018

The purpose of this study was to suggest specific evaluation data for heating and DHW energy consumption characteristics through analyzing energy consumption measurement data of gas boiler in Apartment Buildings with individual heating systems. To do this, it was measured both gas flow and electricity for heating and DHW respectively, and then it was analyzed not only characteristics according to energy sources; gas and electricity, but also the effect of various factors on heating and DHW energy consumption. The result of this study were as follows. It was developed the electric energy estimation model of a gas boiler through analysis on patterns by energy sources. And the effective factors for heating and DHW energy consumption were demonstrated as follows: the area for exclusive use, the number of auxiliary heating equipments, the number of occupants, and the number of sanitary fixtures.

• Journal of the Korean housing association
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• v.22 no.6
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• pp.43-50
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• 2011

Korea is a country with an exceptionally high energy consumption. For economic reasons, Korean households are forced to save more energy. Korea's household energy consumption has grown slowly compared to other sectors and household energy consumption per capita is lower than the OECD average. However, its per capita electricity consumption soared and is expected to remain climbing mainly due to the increasing number of one-person households. To establish an effective strategy against a possible electricity shortage, the actual condition survey of electricity energy consumption first needs to be clearly understood. This study adopted both a general survey and a detailed survey of people living in apartment housings and data was collected on electrical appliance use according to individual schedules. Based on these data, the results were used to attempt to analyze electricity consumption patterns resulting from energy using activities of residents and to determine electricity consumption propensity according to each household member's characteristics in apartment housings.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.1
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• pp.82-87
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• 2005

The purpose of this study is to suggest the characteristics and actual state of energy consumption by the analysis of energy consumption data in an office building. This study examines and analyzes daily and monthly energy consumption of an office building located in Seoul, Korea regarding type of load and business classification within a building. The results are as follows. 1) Energy consumption of office building for each type of load show similar consumption patterns, regardless of seasons such as cooling period and heating period. 2) Out of all annual energy consumption, consumption for lighting took about $43\;\%,$ general electric Power about $23\;\%,$ emergency power $25\;\%,$ computer center $5\;\%$ and cooling power $4\;\%,$ showing that the consumption for lighting was highest, and the percentage of energy consumption for cooling power for operation of cooling facilities took the lowest percentage. 3) Annual gas consumption used for heating and hot water supply were $38,\;36\;\%$ for officetel and office respectively, and $26\;\%$ for arcade. 4) Electricity consumptions used for cooling power for each use of building, office and officetel recorded in July and August of cooling seasons. Even though it shows different patterns for each month, energy consumption showed unique pattern throughout the cooling seasons.