• Journal of the Architectural Institute of Korea Structure & Construction
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• v.36 no.5
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• pp.165-176
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• 2020

The purpose of this study is to develop a estimation method of energy consumption by end-use in office buildings. For this, the current status of information on building energy use was investigated, and the domestic and foreign literature on the classification of energy use in non-residential buildings and the estimation method of energy use were reviewed. In addition, the characteristics of energy consumption by end-use were analyzed with measurement data of 48 office buildings in Seoul. As results, the annual and monthly estimation method of energy consumption by end-use in office buildings using public and measurement data was presented, and the applicability of the estimation method was examined by applying to sample office buildings.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.7
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• pp.43-52
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• 2018

In this study, annual site and primary energy use intensities (EUIs) and CO2 emission intensities (CEIs) per area by end use were estimated based on the measurement data from June 2016 to May 2017 of 50 sample apartment units in Seoul. In addition, estimated site EUIs by end use were compared to the U.S. Residential Energy Consumption Survey (RECS) 2009 data. Site EUIs by end use were found to be in the order of heating > electric appliance > domestic hot water > cooking > lighting > cooling > air movement. In the case of primary EUIs and CEIs by end use, electric appliance was found to be the largest. As results of comparison with the RECS 2009 data, it was found that site EUIs were very similar for heating, domestic hot water and electric appliance, etc., but slightly different for cooling. The number of sample apartment units will continue to increase until 2020 (total number of samples 200) and intensities data by end use will be continuously updated through continuous collection of measurement data.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.580-588
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• 2016

Energy efficiency is the main objective in the design of a wireless sensor network (WSN). In many applications, sensing data must be transmitted from sources to a sink in a timely manner. This paper describes an investigation of the trade-off between two objectives in WSN design: minimizing energy consumption and minimizing end-to-end delay. We first propose a new distributed clustering approach to determining the best clusterhead for each cluster by considering both energy consumption and end-to-end delay requirements. Next, we propose a new energy-cost function and a new end-to-end delay function for use in an inter-cluster routing algorithm. We present a multi-hop routing algorithm for use in disseminating sensing data from clusterheads to a sink at the minimum energy cost subject to an end-to-end delay constraint. The results of a simulation are consistent with our theoretical analysis results and show that our proposed performs much better than similar protocols in terms of energy consumption and end-to-end delay.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.8
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• pp.19-27
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• 2018

In this study, annual site and primary energy use intensities (EUIs) and $CO_2$ emission intensities (CEIs) per area by end use were estimated based on the measurement data from June 2016 to May 2017 of 19 sample office buildings in Seoul. In addition, the estimated site EUIs by end use were compared to the U.S. Commercial Buildings Energy Consumption Survey (CBECS) 2012 data. Average site EUIs by end use were found to be in the order of electric appliance (typical floors) > heating > cooling > lighting > air movement > domestic hot water > vertical transportation > city water supply. In the case of primary EUIs and CEIs by end use, electric appliance was found to be the largest. As results of comparison with the CBECS 2012 data, it was found that the site EUIs were similar for heating, cooling, domestic hot water, and electric appliance, etc., but slightly different for lighting and air movement. The number of sample office buildings will continue to increase until 2020 (total number of samples 85) and intensities data by end use will be continuously updated through continuous collection of measurement data.

• Journal of the Korean Solar Energy Society
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• v.34 no.6
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• pp.93-102
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• 2014

The aim of this study is to analyze the influence of various factors on energy consumption of apartment buildings. Energy consumption data of the Green Together, integrated building energy management system maintained by the government were used, and end-use and primary energy consumption data of 2012 were analyzed for 181 apartment complexes completed between 2004 and 2011 in Seoul. Energy consumption by use, source and heating type were analyzed. Then, energy consumption trends were analyzed and suggested according to energy efficiency ratings, number of households, areas for exclusive use, number of floors, core types, building types, orientations and completion years.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.941-950
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• 1999

This paper presents a DSM monitoring methodology that is able to evaluate the impact of DSM programs especially focused on the strategic conservation i.e. the enhancement of end-use energy efficiency. For an effective assessment of DSM programs, it is foremost necessary to examine the market characteristics on the specific end-use appliance according to the customer's adoption of DSM programs. The proposed monitoring methodology contains a diffusion process of high efficient end-uses considering major factors of DSM impact such as, price, reference capacity, forecasted capacity and lifetime of end-use appliances. Case studies show the projection of power reductions and energy savings resulted from DSM monitoring in order to diagnose the current status properly and provide a baseline of DSM policy and analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.515-524
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• 2010

Recently, many actions are taking to accelerate progress toward social consensus and implementation of Smart Grid. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. The most distinguished element will be Advanced Metering Infrastructure (AMI) that will be installed to every end-use consumer's home or building and optimize the energy consumption of the end-use consumer. The key function of AMI is energy management capability that coordinates and optimally controls the various loads according to the operating condition and environments. In this study, we figure out the basic function of AMI in Smart Energy House that can be defined as a model house implementing in Smart Grid. This paper proposes the energy management algorithm that will be implemented in AMI at Smart Energy House. The paper also show how energy saving in Smart Energy House can be achieved applying the proposed algorithm to an actual house model that has mainly lighting, air-conditioning, TV loads.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.05a
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• pp.179-184
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• 1998

'90년대 이후 전기에너지의 효율적 이용에 따른 절약과 전력사용패턴의 개선을 목적으로 하는 수요관리 즉 DSM(Demand Side Management)의 중요성이 증대되고 있다. 하지만 전기소비량의 약 60%를 차지하는 산업용에 대해서는 전동기 보급율 조사, 냉방수요 행태 조사 및 조명기기 보급실태 조사와 같이 단일기기나 온도에 대한 조사 및 분석만이 이루어져 왔으며, 산업용 전체를 대상으로 업종별 End-Use별 사용실태 조사, 분석, 예측 등 체계적 분석이 이루어지지 않았다. (중략)

• Journal of Communications and Networks
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• v.12 no.2
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• pp.103-113
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• 2010

In this paper, a tradeoff between the total energy consumption-per-bit and the end-to-end rate under spatial reuse in wireless multi-hop network is developed and analyzed. The end-to-end rate of the network is the number of information bits transmitted (end-to-end) per channel use by any node in the network that is forwarding the data. In order to increase the bandwidth efficiency, spatial reuse is considered whereby simultaneous relay transmissions are allowed provided there is a minimum separation between such transmitters. The total energy consumption-per-bit includes the energy transmitted and the energy consumed by the receiver to process (demodulate and decoder) the received signal. The total energy consumption-per-bit is normalized by the distance between a source-destination pair in order to be consistent with a direct (single-hop) communication network. Lower bounds on this energy-bandwidth tradeoff are analyzed using convex optimization methods. For a given location of relays, it is shown that the total energy consumption-per-bit is minimized by optimally selecting the end-to-end rate. It is also demonstrated that spatial reuse can improve the bandwidth efficiency for a given total energy consumption-per-bit. However, at the rate that minimizes the total energy consumption-per-bit, spatial reuse does not provide lower energy consumption-per-bit compared to the case without spatial reuse. This is because spatial reuse requires more receiver energy consumption at a given end-to-end rate. Such degraded energy efficiency can be compensated by varying the minimum separation of hops between simultaneous transmitters. In the case of equi-spaced relays, analytical results for the energy-bandwidth tradeoff are provided and it is shown that the minimum energy consumption-per-bit decreases linearly with the end-to-end distance.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.3
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• pp.128-136
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• 2015

Reducing the building energy consumption has become one of the most important issues. However, the current engineering and technological involvement in energy analysis has been relatively low in the existing buildings. In the existing buildings, end-use analysis must be accompanied to calculate the exact amount in energy savings and such analysis should be conducted based on the energy billing data or measurement data by calibration process. Mostly, detailed energy simulation programs have been proposed for the analysis but, it is difficult to utilize them due to realistic problems. In this paper, we developed an end-use analysis tool that have input function for energy audit data and two case studies were conducted in the real-life office buildings located in Seoul, Korea. Mean Bias Error (MBE) and Coefficient of Variation of Root-Mean- Squreaed-Error (CV(RMSE)) are used for the criteria of comparison. Each index was calculated by using monthly utility bills of electricity and gas consumption. Results showed that MBE and CV (RMSE) represented with acceptable values of -0.1% and 5.7% respectively.