• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.13-18
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• 2009

Building is a major energy consumer, and now many efforts are made to save energy in the design and using equipments. The most noticeable achievement in those efforts is a building energy performance assessment program. But most programs are not satisfying enough to provide exact meteorological data, and data source and calculation, and data collection period are not clearly defined. That is common in most of domestic programs. This study collects typical meteorological data in 16 items and analyzes them with Visual DOE 4.0 to compare with existing data. The comparison found that revised data shows a 11% increase on average during cooling period from June to September, and a 13% decrease on average during heating period from December to February, in terms of building heating and cooling load in a monthly basis.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.607-608
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• 2012

Data aggregation is a fundamental problem in wireless sensor networks which attracts great attention in recent years. Delay and energy efficiencies are two crucial issues of designing a data aggregation scheme. In this paper, we propose a distributed, energy efficient algorithm for collecting data from all sensor nodes with the minimum latency called Delay-aware Power-efficient Data Aggregation algorithm (DPDA). The DPDA algorithm minimizes the latency in data collection process by building a time efficient data aggregation network structure. It also saves sensor energy by decreasing node transmission distances. Energy is also well-balanced between sensors to achieve acceptable network lifetime. From intensive experiments, the DPDA scheme could significantly decrease the data collection latency and obtain reasonable network lifetime compared with other approaches.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.3
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• pp.205-212
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• 2008

This paper describes the application of an inverse building model to a calibrated forward building model using EnergyPlus program. Typically, inverse models are trained using measured data. However, in this study, an inverse building model was trained using data generated by an EnergyPlus model for an actual office building. The EnergyPlus model was calibrated using field data for the building. A training data set for a month of July was generated from the EnergyPlus model to train the inverse model. Cooling load prediction of the trained inverse model was tested using another data set from the EnergyPlus model for a month of August. Predicted cooling loads showed good agreement with cooling loads from the EnergyPlus model with root-mean square errors of 4.11%. In addition, different control strategies with dynamic cooling setpoint variation were simulated using the inverse model. Peak cooling loads and daily cooling loads were compared for the dynamic simulation.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.149-150
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.139-140
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• 2005

• Journal of the Korean Solar Energy Society
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• v.29 no.6
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• pp.69-74
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• 2009

Monitoring system is an absolutely-required system for assessing a performance and fatigue load of the wind turbine in an on-shore wind energy experimental research complex. It was implemented for the purpose of monitoring the wind information measured from a meteorological tower at the monitoring house, and of utilizing the measured data(fatigue data and electric analyzing data of wind turbine)for the performance assessment, by using the LabVIEW program. Then, by adding the performance assessment-related data acquired from the wind turbine during the performance assessment and the data recorder for synchronizing the data of meteorological tower, the system(BusDAQ) was implemented. Because it transmitted the data by converting the output 'RS-232' of data logger which measures the wind condition into CAN protocol, the data error rate was minimized. Also, This paper is introduced to make the best use of the developed monitoring system and to explain about construct of the system and detailed data communication of its system.

• Journal of the Korean Solar Energy Society
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• v.29 no.3
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• pp.66-72
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• 2009

As 'Low Carbon Green Building' is highly required, programs to evaluate building performance are actively and commonly used. For most of these programs, dynamic responses of buildings against external weather changes are very important. In order to simulate the programs, weather data of each region must be properly entered to estimate accurate amount of building energy consumption. To this end, the existing weather data and weather data of KSES were compared and analyzed to find out how weather changes. Energy load of Korea's standard houses was also analyzed based on this data. As a result, data corresponding to June ${\sim}$ September when cooling is supplied shows 23% of average increase with 30% of peak increase(June). On the other hand, data corresponding to November ${\sim}$ February when heating is supplied shows 29% of average decrease with 34% of peak decrease(November). Increase in cooling load and decrease in heating load in the above data comparison/analysis show that KSES 2009 data reflects increase in average temperature caused by global warming unlike the existing data. Increase in dry-bulb temperature depending on weather change of standard houses increases cooling load by 17% and decreases heating load by 36%

• Journal of the Korean Solar Energy Society
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• v.33 no.6
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• pp.62-69
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• 2013

In this paper, Korea Institute of Energy Research, building integrated renewable energy monitoring system that utilizes solar power generation forecast data forecast model is proposed. Renewable energy integration of real-time monitoring system based on monitoring data were building a database and the database of the weather conditions and to study the correlation structure was tailoring. The weather forecast cloud cover data, generation data, and solar radiation data, a data mining and time series analysis using the method developed models to forecast solar power. The development of solar power in order to forecast model of weather forecast data it is important to secure. To this end, in three hours, including a three-day forecast today Meteorological data were used from the KMA(korea Meteorological Administration) site offers. In order to verify the accuracy of the predicted solar circle for each prediction and the actual environment can be applied to generation and were analyzed.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.11
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• pp.580-591
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• 2017

In accordance with 2015 Paris agreement, each individual country around the world should voluntarily propose not only its (individual) reduction target, but also actively develop and present expansion targets of its scope and concrete reduction goals exceeding the previous ones. Accordingly, it is necessary to prepare a macroscopic, long-range strategy for reducing energy consumption and greenhouse gas emissions, which can cover a single building, town, city and eventually even a province. The purpose of this research is to gather and compile government-acquired data from various sources and (in accordance with contents and specificity), combine building data by stages by using multi-variable matrix and then analyze the significance of combined data for each stage. The first order data presents the probability and the cost effectiveness of energy saving on the scale of a city or a province, based only upon general information, size and power consumption of buildings. The second order data can identify a pattern of energy consumption for a building of a specific purpose and which tends to consume a larger amount of energy during one particular season (than others). Finally, the third order data can derive influential factors (base load, humidity) from the energy consumption pattern of a building, and thus propose an informed and practical energy-saving method to be applied in real time.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.757-768
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• 2003

Recently, the renewable energy resources play an important role as an energy resources of future due to an environmental pollution and lack of resources and so on. The development and diffusion of information systems related to renewable energy resources have been driven actively abroad. However, at domestic an efficient history management for renewable energy resource data and web retrieve service are not provided. Therefore, in this paper, we propose a history data management system for the renewable energy resources, which stores and manages vast history information of renewable energy resource data systematically. This system collects renewable energy resource data in the outside observation system and stores them in the history database. The stored Information is retrieved through the history query process and can be provided in various forms - table, graph, chart and counter line, etc. - on the internet. Especially, the proposed system manages the history data in real-time so the latest information is always provided to the users through the web interface.