• Journal of the Korean Solar Energy Society
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• v.39 no.2
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• pp.57-69
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• 2019

Because the hospital building operates 24 hours a day, 365 days a year for treatment and restoration of patients, it has a different pattern of energy use than that of ordinary buildings. Hospitals contribute to energy consumption and have a negative environmental impact. This study aims to find how meaningful energy performance, reflecting good energy management and ECMs, can be operated for hospital buildings, a category encompassing complex buildings with different systems and large differences between them. In this study, we proposed the energy diagnosis & evaluation method and energy management process to verify energy saving through operation data based on system & facility characteristics, operation pattern and energy consumption characteristics of hospital building. Energy consumption structures were surveyed throughout 4 reference hospital in Seoul, Korea. Findings confirm that different hospital departments have hugely different energy-demand profiles. Energy efficiency and energy saving potentials are presented. The energy performance analysis can be applied to a wide range of problems in energy-system operation.

• KIEAE Journal
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• v.11 no.4
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• pp.55-61
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• 2011

Due to global warming issues caused by climate changes which are internationally being highlighted, recently, there are lots of efforts under way to reduce energy consumption in various fields. Currently, 25 percent of energy consumption in Korea are being generated from buildings and especially, nearly 54 percent of them are being consumed by households. This study, therefore, aims to consider energy consumption status in the existing rural houses and analyze structure system performance, window system performance and air-permeability of domestic passive-type buildings using PHPP which is an analysis program of building energy to improve energy consumption problems in rural areas. Then, energy reduction plans in rural houses were proposed, by comparing and analyzing energy reduction of the existing rural houses, based on these data.

• KIEAE Journal
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• v.12 no.2
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• pp.77-82
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• 2012

Data mining is to discover problems in the large amounts of data. Also, data mining trying to find the cause of the problem and the structure. Building energy consumption patterns, the amount of data is infinite. Also, the patterns have a lot of direct and indirect effects. Discussion is needed about the correlation. This work looking for the cause of energy consumption. As a result, energy management can find out the issue. Building energy analysis utilizing data mining techniques to predict energy consumption. And the results are as follows: 1) Using data mining technique, We classified complicated data to several patterns and gained meaningful informations from them. 2) Using cluster analysis, We classified building energy consumption data of residents and analyzed characters of patterns.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.3
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• pp.137-142
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• 2018

Energy harvesting technology is drawing attention as a means of collecting various eco-friendly energy and accumulating residual energy. Recently, differential power processing (DPP) is being developed as part of energy harvesting. This is being studied as a solution to the loss of power generation between power modules and the problems caused by module small losses depending on the size of power production. In this paper, we propose the necessity of the DPP by comparing and analyzing energy harvesting related module integration system and power supply efficiency of DPP. The power efficiency of the converter and the power difference between the wind power and the photovoltaic power supply have been changed to demonstrate the effectiveness of the proposed system.

• New & Renewable Energy
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• v.2 no.4 s.8
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• pp.27-32
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• 2006

New and renewable energy information becomes one of the greatest issues because of serious environment problems and limited fossil resources. However, There are few system to manage and utilize new and renewable energy information efficiently. Therefore this study establish the GIS based Resource Map System to save and analyze new and renewable energy information about solar energy, wind power, small hydro, biomass, and geothermal. This Resource Map System is composed of the management system, practical system, field system, and Web-service system. This System can provide various spatial analysis tools such as data searching, creating thematic maps, evaluating location requirements for energy facilities.

• 한국신재생에너지학회:학술대회논문집
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• 2011.11a
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• pp.140.2-140.2
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• 2011

Renewable energy(RE) systems have difficulties in operating and management due to the intermittency of the energy generation. Stochastic supply profiles of RE creates problems for mechanical and electrical design in relation to the selection of technology types and capacities of RE to be installed. This paper presents an methodology of the feasibility assessment of RE-integrated energy systems on the basis of hourly demand/supply analysis tools. Also, this paper shows the feasibility and the usefulness of GS REMA(Renewable Energy Matching Analysis) and HOMER by comparing actual energy data.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.8 no.1
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• pp.1-6
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• 2012

This study aims to analysis domestic energy consumption in Korea and reduction greenhouse gas by building mechanical system. At this point be tormented the energy depletion and climate change of earth are big problems on the eatrh. In this paper we will find out best methods to reduction greenhouse gas and energy consumption by practical building mechanical system. Enlargement of greenhome and building adopt, greenhouse gas exhaust reduction in building, publication of energy consumption rate, publish building energy management manual, etc.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.12
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• pp.1090-1097
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• 2000

Predicting building energy use can be useful to evaluate its energy performance. This study proposed empirical approach for predicting building energy use with regression analysis. For the empirical analysis, simple regression models were developed based on the historical energy consumption data as a function of daily outside temperature, the predicting equations were derived for different operational modes and day types, then the equations were applied for predicting energy use in a building. BY selecting a real building as a case study, the feasibilities of the empirical approach for predicting building energy use were examined. The results showed that empirical approach with regression analysis was fairly reliable by demonstrating prediction accuracy of $pm10%$ compared with the actual energy consumption data. It was also verified that the prediction by regression models could be simple and fairly accurate. Thus, it is anticipated that the empirical approach will be useful and reliable tool for many purposes: retrofit savings analysis by estimating energy usage in an existing building or the diagnosis of the building operational problems with real time analysis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.205-210
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• 2020

Thanks to the shift in awareness of environmentally friendly energy and government initiatives, practical light-emitting diode(LED) lighting fixtures have emerged and are being distributed, resulting in very large energy savings. However, in actual use of LED lighting, it is possible to use it as an individual, but when using a large street light or a whole home lighting, the whole lighting system is realized due to various problems such as efficiency, stability, and reliability. Doing so has several problems. Although AC-LED has been developed recently to solve safety problems such as heat generation phenomenon of the conventional DC-LED, it also has various problems such as quality safety and reliability, which are difficult to use as outdoor lighting using existing AC Power. This happens. Accordingly, the appropriate power for AC-LED should be developed and applied, and the emergence of such LED lighting will play a role as a tool that can overcome the limitations of existing LED lighting and implement sustainable energy saving.

• Journal of the Korea Computer Industry Society
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• v.8 no.4
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• pp.237-244
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• 2007

In this paper we investigate the benefits of a data aggregation to prolong the lifetime of wireless sensor networks. To reduce the overload of messages from source node to sink node, data aggregation technique is generally used at intermediate node in path. The DD-G(Directed Diffusion-Greedy) can diminish the consumption of node energy by establishing energy effective single path from source to destination. In this case, the nodes near sink node have some problems, i) overly concentration of energy consumption, ii) increase of message delay time. To solve these problems, we propose a new data aggregation method which consider distribution of network overload, especially at the nodes close to sink node. The result shows that it can save energy and network delay time.