• Journal of Energy Engineering
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• v.22 no.2
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• pp.211-225
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• 2013

To run an optimal operation of Integrated energy supply facilities, we need to analyze heat consumption patterns of District heating users and derive optimum and maximum load ratio of heat production facilities unit. This study selects three District heat production facilities. It also classifies District heating users into residential apartment buildings and eight non-residential buildings and analyzes heat consumption results for an year. Finally it carries out the analysis of how the ratio change of each type affects maximum load ratio, facility utilization ratio, heat supply range. According to this study, three different District heat facilities of residential apartment building show similar daily and annual heat consumption patterns. Annual average load ratio, maximum load ratio and annual heat demand increase as outdoor temperatures decrease. Non-residential buildings in urban District focused on apartment buildings display similar by the daily and annual heat consumption patterns. Yet their daily and annual maximum load ratio differ according to outdoor temperature, District, building types and their composition ratio. In the case of urban District focused on apartment buildings reach optimum and maximum load ratio when apartment buildings reaches 60-70% of the total. At that point heat supply range becomes maximized and the most economic efficiency is obtained.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.747-750
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• 2011

최근 에너지와 자원 절약 사업의 일원으로 차세대 전력 관리 시스템인 스마트 그리드에 대한 관심이 증가하고 있다. 스마트 그리드는 전력 공급자와 소비자 사이에 통신망을 기반으로 한 양방향 전력 공급 방식을 말한다. 스마트 그리드를 통하여 전력 공급자는 소비자의 전력 사용량에 따른 탄력적인 전력 생산 및 공급이 가능하고, 소비자는 자신의 소비 패턴을 통한 효율적 전력 소비를 할 수 있다. 하지만 사이버 공격에 대한 위협이 높아지면서 공용망을 기반으로 운용되는 스마트 그리드 운용 정보에 대한 보안요구사항이 증가하고 있다. 이에 본 논문에서는 소비자 전력 사용량, 전력 사용 패턴 등의 정보가 송수신되는 지능형검침인프라의 보안 위협을 분석하고, 이를 해결하기 위한 방안을 제안한다.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.279-280
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• 2009

최근 경세성장과 함께 생활수준의 향상으로 인하여 에너지 수요는 매년 증가하고 있으며 그 중에서 하나인 전력수요도 역시 급격히 늘어나고 있는 추세이다. 이와 더불어 투자자원 및 입지확보의 어려움, 환경제약의 문제로 전력 공급의 어려움은 날로 증가되고 있다. 따라서 수요증가를 전력공급 능력의 증진뿐만 아니라 수요관리 측면에서도 필요성이 대두되고 있다. 전력선 통신은 전력선을 매체로 하기 때문에 신규선로의 포설 없이 가전기기 및 정보화 서비스 모뎀들의 네트워크화에 용이할 뿐만 아니라 커버리지 확장에도 뛰어나서 디지털 가전, 원격검침, 전력설비 감시제어, 국가 재난 감시 시스템 등의 기본 통신 방식으로 가장 유력한 기술로써 디지털 가전을 포함한 유비쿼터스 전기설비 네트워크 구성에서 필수적 기술로 채택되고 있기 때문에 지능형 홈 네트워크, 전력IT 부가서비스, 설비감시 네트워크, 유비쿼터스 네트워크 관련 기술에 대한 파급 효과가 매우 크며, 디지털 가전의 기본 통신 방식으로 가장 유력한 기술로써 디지털 가전 구성에서 필수적 기술로 채택되고 있기 때문에 지능형 홈 네트워크 관련 기술에 대한 파급 효과가 매우 크다. 본 연구에서는 전력선통신모뎀을 이용하여 가전기기의 전력 소비를 감지할 수 있는 센서를 내장한 전력선 통신기반의 전력 감시 모듈을 개발하여 실시간 원격 모니터링을 통해 소비전력 패턴을 작성한다. 그리고 전력감시 모듈에 연결된 가전기기의 소비전력 패턴 분석을 통해 전력소비 이상 유무를 감지할 수 있는 알고리즘을 개발, 탑재하여 이상유무를 판단하고 전력소비가 급증할 시 자동으로 전력을 차단하여 화재나 누전의 위험을 방지한다. 이에 본 연구는 전력선통신을 이용하여 전력소비감시 및 이상전력차단에 관한 연구에 관한 것이다.

• Journal of Energy Engineering
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• v.25 no.3
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• pp.73-82
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• 2016

The energy consumption efficiency in a variety of operational test mode was considered for domestic gas boiler below 70 kW. The energy efficiency test carried out in the experimental conditions similar to the actual operation status was analyzed and compared with the current Korean efficiency test method. Four types of test modes for each boiler(Non-condensing and condensing boiler) were carried out in the condition of laboratory mode(full load, steady state) and actual operating mode. Futhermore divided into two operational status for each of these, it was applied by maximum gas consumption and consumer sales conditions. Test equipment has the function referred to gas boiler standards, such as KS or European standard EN. The equipment should be continuously measured and record the measuring factors which are the flow volume of gas and water, laboratory temperature, water flow volume for heating, return water volume after heating and quantity of the exhaust gases(CO, NO, $NO_2$). The experimental results were found that non-condensing boiler efficiency of laboratory mode is about 10% higher than that of actual mode. In case of condensing boiler, the efficiency of laboratory condition is about 20% higher than that of the actual using conditions. I suggest that the government will gradually take the efficiency test method considering the actual conditions.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.245-253
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• 2011

Due to the imprudent spending of the fossil fuels, the environment was contaminated seriously and the exhaustion problems of the fossil fuels loomed large. Therefore people become taking a great interest in alternative energy resources which can solve problems of fossil fuels. The wind power energy is one of the most interested energy in the new and renewable energy. However, the plants of wind power energy and the traditional power plants should be balanced between the power generation and the power consumption. Therefore, we need analysis and prediction to generate power efficiently using wind energy. In this paper, we have performed a research to predict power generation patterns using the wind power data. Prediction approaches of datamining area can be used for building a prediction model. The research steps are as follows: 1) we performed preprocessing to handle the missing values and anomalous data. And we extracted the characteristic vector data. 2) The representative patterns were found by the MIA(Mean Index Adequacy) measure and the SOM(Self-Organizing Feature Map) clustering approach using the normalized dataset. We assigned the class labels to each data. 3) We built a new predicting model about the wind power generation with classification approach. In this experiment, we built a forecasting model to predict wind power generation patterns using the decision tree.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.594-600
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• 2006

The optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model has been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme ate utilized, respectively. As a result, two meta-models for trip time and energy consumption are constructed. The optimization to search an economical running pattern is achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.896-899
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• 2016

Server management and power management are important to operate a data center stably and efficiently. By this paper, we introduce an web based application that is able to monitor and visualize energy consumption, help to energy consumption analysis of a data center due to provide server monitoring information such as temperatures for server, status of each device, power status using server management interfaces and power management modules in data center, also suggest the methods to implement them. This application takes advantage of IPMI which is server management standard interfaces and server management technology in manufacturer's individual way so it can do integrated monitoring for heterogeneous severs, and there is little monitoring load inside of server system because it doesn't need to install agent program for monitoring target system, and it can be used successfully to energy consumption analysis, server management in a data center due to realtime provided energy consumption and monitoring information.

• Proceedings of the KIPE Conference
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• 2010.11a
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• pp.48-49
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• 2010

전기에너지의 가격상승과 에너지 소비량 증가, 이산화탄소 배출 문제의 해결방안으로 직류 배전 시스템에 대한 연구가 진행되고 있다. 직류배전 시스템은 각 부하에서 발생되는 AC/DC 변환 손실을 줄이기 위해 각 기기의 AC/DC 컨버터를 통합하여 부하에 직류를 공급하여 효율 및 신뢰도의 향상을 얻는다. 설계된 직류배전 시스템의 효용성을 입증하기 위해서는 실제 사용 패턴에 근접한 부하의 사용정보가 요구된다. 본 논문에서는 전력사용통계에 근거한 계절별, 가구별 전력소비 패턴을 분석하고, 세대별 연중 부하사용 시나리오를 구성한다. 또한 작성된 시나리오를 직류 배전 전력계 시스템 설계 툴에 적용하여 직류 기반 시스템의 효용성을 검증한다.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1154_1155
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• 2009

본 논문은 철도부하의 이동을 고려한 전력조류계산 알고리즘에 기반하여, 에너지 저장장치를 설치하였을 때 철도계통의 영향 해석에 관한 논문이다. 철도부하는 위치적 변화 뿐 만 아니라 기동-타행-제동의 운전모드의 변화에 따라 전력소비 패턴이 달라지는데, 제동 시에 발생하는 회생에너지를 에너지 저장장치를 이용하여 활용함으로서 에너지 절감 효과 및 가선전압 안정화를 구현할 수 있다. 본 논문에서는 서울지하철 2호선의 실계통에 대한 사례연구를 수행하여, 실계통에 에너지 저장장치를 적용함으로서 그 필요성을 증명하였다.