• 한국기후변화학회지
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• 제7권1호
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• pp.95-101
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• 2016

This study measured the amount of electricity consumed by the vending machines installed on campus and aim to come up with measures to address excessive consumption of electricity. We chose 10 universities located in the city of Seoul and Gyeonggi province and measured electricity consumption of 10 vending machines installed in each university. We then calculated annual electricity consumption of the machines based on previously calculated electricity consumption of 100 samples. According to the result of the calculation, it is estimated that the machines studied on consume 700 KWh a year. This amount could translate into approximately 3,000 tons of annual carbon emissions and 640 million KRW in annual electricity bills. It was also found that there is a significant difference between ordinary vending machines and machines certified for being eco-friendly and energy efficient, in terms of electric power consumption. It is expected that, if the ordinary machines are replaced with the eco-friendly and high-efficient machines, 640 KWh of electricity, 300 kg of carbon, and 61,640 KRW in electricity bills would be saved, which means 28% saving in energy, emissions and bills. In conclusion, we determined that, as one of the ways to reduce electric power consumption and carbon emissions, old vending machines on campus could be replaced with eco-friendly and high-efficient machines.

• Architectural research
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• 제21권1호
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• pp.21-29
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• 2019

Recent years in Korea, some new developed buildings are only using electricity as power for heating, cooling, bathing and even cooking which means except electricity, there is no natural gas or other kinds of energy used in such kind of building. In vehicle industry area, scientists already invented electric vehicle as an environment friendly vehicle; after that, in architecture design and construction field, buildings only using electricity appeared; the curiosity of the environment impact of energy consumption by such kind of building lead me to do this research. In general, electricity is known as a clean energy resource reasoned by it is noncombustible energy resource; however, although there is no environmental pollution by using electricity, electricity generation procedure in power plant may cause huge amount of environment pollution; especially, electricity generation from combusting coal in power plant could emit enormous air pollutants to the air. In this research, the yearly amount of air pollution by energy using under traditional way in research target building that is using natural gas for heating, bathing and cooking and electricity for lighting, equipment and cooling is compared with yearly amount of air pollution by only using electricity as power in the building; result shows that building that only uses electricity emits much more air pollutants than uses electricity and natural gas together in the building. According to the amount of air pollutants comparison result between two different energy application types in the building, residential SOFC (Solid oxide fuel cell) is simulated to apply in this building for decreasing environment pollution of the building; furthermore, high load factor could lead high efficiency of SOFC, in the scenario of simulating applying SOFC in the building, SOFC is shared by two or three households in spring and autumn to increase efficiency of the SOFC. In sum, this research is trying to demonstrate electricity is a conditioned environment friendly energy resource; in the meanwhile, SOFC is simulated efficiently applying in the building only using electricity as power to decrease the large amount of air pollutants by energy using in the building. Energy consumption of the building is analyzed by calibrated commercial software Design Builder; the calibrated mathematical model of SOFC is referred from other researcher's study.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.162-175
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• 2018

Currently, electricity consumption and feedback mechanisms are being widely researched in Internet of Things (IoT) areas to realise power consumption monitoring and management through the remote control of appliances. This paper aims to develop a smart electricity utilisation IoT platform with a deep belief network for electricity utilisation feature modelling. In the end node of electricity utilisation, a smart monitoring and control module is developed for automatically operating air conditioners with a gateway, which connects and controls the appliances through an embedded ZigBee solution. To collect electricity consumption data, a programmable smart IoT gateway is developed to connect an IoT cloud server of smart electricity utilisation via the Internet and report the operational parameters and working states. The cloud platform manages the behaviour planning functions of the energy-saving strategies based on the power consumption features analysed by a deep belief network algorithm, which enables the automatic classification of the electricity utilisation situation. Besides increasing the user's comfort and improving the user's experience, the established feature models provide reliable information and effective control suggestions for power reduction by refining the air conditioner operation habits of each house. In addition, several data visualisation technologies are utilised to present the power consumption datasets intuitively.

• KIEAE Journal
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• 제11권5호
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• pp.91-96
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• 2011

This study is to analysis the characteristics of electric power consumption of apartments complex in Korea. This study shows the pattern of electric power consumption and correlation of each apartment complex's completion year monthly and timely. With this result, we are able to predict the demand pattern of electricity in a house and make the schedule by demand pattern. It is expected this data is used as reference of electric consumption of Daejeon area to operate the simulation tools to predict the building energy. The yearly data of 10 apartment complexes of 2010 are analyzed. The results of this study are followed. The averaged amount of electricity consumption in winter is higher as summer because of the high capacity of heating equipment. All of the house has electric base load from 0.26kWh to 0.5kWh. The average of the electricity consumption of month is shown as 310.2kWh. A week is seperated, as 4 part such as week, weekend, Saturday and Sunday. During week, the average of timely electricity consumption is shown as 0.426kWh. The Saturday consumption is 0.437kWh. The Sunday is 0.445kWh. The peak electricity consumption in summer and winter is measured. The peak consumption on summer season is 1.389kW on 22th August 64% higher than winter season 0.887kW on 3rd January.

• 대한전기학회논문지:전력기술부문A
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• 제53권8호
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• pp.472-476
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• 2004

Standby power is the electricity consumed in an electrical equipment when it is switched-off or not performing its main function. Due to the acceleration of digital electronics and home networking, standby power use tends to increase rapidly year by year. In this paper, standby power consumption in residential sector in Korea has been surveyed and reported for the first time. Totally 825 pieces of electrical equipments that consume standby power in 53 households were investigated. The average standby power per equipment and total standby power per household were 3.66W and 57.0W, respectively. Annual standby power consumption per household was estimated 306kWh; which means the standby power consumption in residential sector in Korea can be estimated 4.6TWh a year representing 1.67 percent of total electrical consumption (274TWh).

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1843-1850
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• 2014

In this paper, we investigate a group building based power consumption scheduling to minimize the electricity cost. We consider the demand shift to reduce the peak load and suggest the compensation function reflecting the relationship between the change of the building demand and the occupants' comfort. Using that, the electricity cost minimization problem satisfied the convexity is formulated, and the optimal power consumption scheduling algorithm is proposed based on the iterative method. Extensive simulations show that the proposed algorithm achieves the group management gain compared to the individual building operation by increasing the degree of freedom for the operation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.165-167
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• 2004

End-user electric power consumption trends shows various load curves dependant on industry, contract, season, day and time. Analysis of end-user electric power consumption trends has a key role to efficiently meet electricity demand. There are several factors of change in electricity demand such as the change of weather, international conflict, and industrial trends during summer. This paper has analyzed the analysis the end-user electric power consumption trends using the load curve during international conflict. We observed that international conflict decreased electric demand by $5.4\%$. This increase is not significant, and therefore we conclude that the international conflict has not greatly affected Korea's electricity demands. This paper provides useful information so as to mon: efficiently perform demand side management.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전력기술부문
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• pp.151-155
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• 2005

An electricity consumption is closely related to the economic growth structure. The change of economic growth structure affects the pattern of electricity consumption widely and severely. This paper gives that the primary changing factors of electricity growth are economic growth, change of industry structure(the change of electricity consumption ratio in case of residential sector), and the effect of electricity saying. It gives a model to analyze the influence of GDP to the change of electricity consumption patterns by sector through the period of pre and post 1998(IMF, financial crisis) to observe the contribution of each factor to the growth of electricity demand. It is anticipated that this study shows the feasible scheme of economic structure to become the developed country.

• 조명전기설비학회논문지
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• 제28권12호
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• pp.103-107
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• 2014

Together with housings, general buildings and industrial facilities, multi-purpose complexes are equipped with various and special equipment. They are often used by many unspecified people, which causes an increase in annual electricity consumption. Because of this, a great amount of money has been spent for electric charge, far more in excess of the budget, so a reasonable electricity rate needs to be estimated. In this study, we surveyed the power consumption, average power use, and annual electricity bill of multi-purpose complexes in the past five years. To see the general tendency of the survey, we conducted a statistical analysis with such parameters as average, maximum, and minimum values. Through regression analysis, we could see the trend of the survey in linear way. Based on the survey, we have developed an electric-rate calculation program to estimate the next year's budget on electricity.

• 한국융합학회논문지
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• 제8권1호
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• pp.19-23
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• 2017

전력은 모든 나라에서 사회 발전과 경제 성장에 가장 기본적인 자원이다. 산업이 고도화 되고 경제의 규모가 발전하면서 전력의 소비량은 점점 증가하고 있다. 전력을 공급하는 쪽에서는 전력을 생산할 때 자원의 낭비를 줄이기 위해 전력 사용량을 예측하는 것은 중요한 일이다. 또한 전력 수요 예측을 통해 여름과 겨울의 피크 타임에서의 전력 수요를 분산하는 것이 가능하다. 그리고 소비 전력의 예측은 국내에서 수요자원 거래시장(Negawatt market)이 본격화되면서 더욱 중요하게 되었다. 더구나 전력 소비량 예측은 소비자가 전력 시장에 직간접적으로 참여하는 수요관리 방법을 제공해준다. 본 연구에서는 1999년부터 2011년까지의 국내총생산, 1인당 국민총소득, 부가세, 국내전력소비량을 이용하여 제주도의 어업 전력 사용량을 예측하는데 유전자 알고리즘을 사용하고 있다. 유전자 알고리즘은 다양한 조합 최적화 분야에서 최적해를 찾는데 유용하게 사용되는 알고리즘이다. 본 논문에서 유전자 알고리즘에서 최적의 동작을 위한 파라미터들을 찾는다. 그리고 실제 전력 소비량 예측을 위해 사용되는 계수(coefficient)들의 최적값을 찾아 예측값과 실제 전력 소비량의 오차를 최소화하는데 목적이 있다.