• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.17-22
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• 2007

Global average temperature rise accelerates by global warming in the three decades of the 20th century. But now we use heating degree days which was established 20 years ago. Therefore new heating degree days for 15 district areas of korea was determined using long-term measured data. Five different base temperatures ranging from 24 to $16^{\circ}C$ were chosen in the calculation of heating degree days. And yearly heating degree days were given in the tabular form.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.22 no.7
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• pp.436-441
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• 2010

The purpose of this study is to revise the HDD(Heating Degree-Days) of main cities of Korea because the outside temperature rise have been accelerated by global warming recently. Now our HDD(Heating Degree-Days) for the utility design of district heating system had been `established in 20 years ago. Therefore new heating degree days for main cities of korea had been required and determined using long-term measured outside weather temperature data during 30 years. For the analysis of HDD, five different base temperatures ranging from 24 to $16^{\circ}C$ were chosen in the calculation of heating degree days. And new yearly heating degree days of 15 cities of korea were given in the tabular form.

• Journal of Bio-Environment Control
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• v.23 no.3
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• pp.192-198
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• 2014

To establish the design criteria for seasonal heating load calculation in greenhouses, standard weather data are required. However, they are being provided only at seven regions in Korea. So, instead of using standard weather data, in order to find the method to build design weather data for seasonal heating load calculation, heating degree-hour and heating degree-day were analyzed and compared by methods of fundamental equation, Mihara's equation and modified Mihara's equation using normal and thirty years from 1981 to 2010 hourly weather data provided by KMA and standard weather data provided by KSES. Average heating degree-hours calculated by fundamental equation using thirty years hourly weather data showed a good agreement with them using standard weather data. The 24 times of heating degree-day showed relatively big differences with heating degree-hour at the low setting temperature. Therefore, the heating degree-hour was considered more appropriate method to estimate the seasonal heating load. And to conclude, in regions which are not available standard weather data, we suggest that design weather data should be analyzed using thirty years hourly weather data. Average of heating degree-hours derived from every year hourly weather data during the whole period can be established as environmental design standards, and also minimum and maximum of them can be used as reference data for energy estimation.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.943-948
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• 2008

Global average temperature rise accelerates by global warming in the three decades of the 20th century. But Current HDD ( Heating Degree-Days) which we are using has been established 20 years ago. Therefore new heating degree days for 15 district areas of korea was determined using long-term measured data. Five different base temperatures ranging from 24 to $16^{\circ}C$ were chosen in the calculation of heating degree days. And yearly heating degree days were given in the tabular form.

• 한국태양에너지학회:학술대회논문집
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• 2008.04a
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• pp.160-165
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• 2008

The concern in energy reduction in the field of architecture which takes up a big weight in domestic energy consumption is gradually increasing. For this reason, a lot of research work on this matter is being carried out. Particularly, it is generally required that currently used system in a structure for energy reduction should be maximized in its efficiency. In addition, research on several energy reduction typed systems is underway. Such a research work should not only include the one in time of the present but also keep up with the trend for future-oriented research. This research paper forecasted and analyzed the trend for global warming and demand of a structure for energy in the future by applying climate scenarios to cooling degree-day and heating degree-day. Also, this research found out the decrease in heating degree-days and increase in cooling degree-days until this moment due to the progress of global warming. In addition, as for heating degree-days in the future forecasted on the basis of HadCM3, it is estimated that the range of decrease could be ever bigger starting 2040 in case of Seoul and also starting 2010 in case of Ulsan ever after respectively. In case of cooling degree-days, it is estimated that its increase range could be bigger abruptly starting 2050, and after 2080, its increase range would be much bigger.

• Journal of Environmental Science International
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• v.13 no.3
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• pp.189-196
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• 2004

Characteristics of urban wanning phenomenon were studied using degree days for three big cities(Seoul, Busan, Daegu) adjacent to airport. Time variation of the cooling and heating degree days was analyzed using the daily mean air temperature data measured at the six meteorological observatory for long-term periods(25～43years). The results for the big cities are as followings: 1) It was found that the heating degree days trended to decrease from year to year. 2) The cooling degree days were nearly unchanged during the same analysis periods. 3) The number of days calling for air-heating also tended to decrease as time passes. 4) Those of air-cooling were nearly unchanged during the same time. It suggests that the change of air-heating condition owing to urbanization came in evidence in the winter season, but that of air-cooling condition was slight in the summer season. On the other hand, the long-term trends of degree days were very small in airport areas except for Kimhae airport. Hence, the gaps of degree days between big cities and rural airport areas are increasing.

• KIEAE Journal
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• v.13 no.4
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• pp.43-48
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• 2013

The effect of climate change has influenced humanity and ecosystem with tremendous changes in temperature. For the past 150 years, the national annual average temperature is 0.6 degree increased and the heating degree day reduced from April to November. However, December to January, the climate change was generated and the heating degree day increased. The blackout occured in 2011 and 2012 by increasing electricity consumption of heating and cooling equipment to the effects of climate change. That is because heating load accounted for 20% of building electric use. In this study, strengthening measures to reduce heating energy consumption is presented due to climate change in winter since 1980 to prevent blackout and reliable power supply for the building energy-saving design standards by Meteorological data provided by the National Weather Service were calculated using the heating degree days in order to present eighteen cities from 1980 to 2012. Insulation standards are presented to prevent black-out by the heating degree days. the heating energy demand was reduced almost 6% including 10% in Central, 5% in South and Jeju area based on strengthening of the insulation. It is applied to the entire country an annual economic effect of 250 billion won, and black-out can be prevented.

• Journal of the Korean Solar Energy Society
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• v.33 no.6
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• pp.77-84
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• 2013

Degree-day method is very simple but essential index to estimate heating and cooling energy demand in buildings. It has been neglected, however, for the simplicity so it is difficult to find any DB for south Korean cities. Even meteorological department of S. Korea doesn't report the data officially. In this study, current methods that are being used in many countries are investigated and used to calculate degree-days of 35 south Korean cities with 30 years(1981~2010) historical data. The calculation result indicates that the error among 4 major methods are dependent on how daily or hourly temperature are treated in the calculation and how balance point temperature is defined. The errors of the methods are no larger than 6% relative to hourly degree-day method.

• The Journal of Sustainable Design and Educational Environment Research
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• v.11 no.2
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• pp.19-27
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• 2012

This study was carried out in order to establish the estimation equation for school power consumption using regression analysis based on collected power consumption for two years of weather data and schools are located in Central Changwon and Masan district in Changwon city. (1) The power consumption estimation equation for Heating and cooling is calculated using power consumption per unit volume, the difference between actual power consumption and results of estimation equations is 4.1%. (2) The power consumption estimation equation for heating load is showed 2.6% difference compared to actual power consumption in Central Changwon and is expressed 2.9% difference compared to that in Masan district. Therefore, the power consumption prediction for each school using the power consumption estimation equation is possible. (3) The power consumption estimation equation for cooling load is showed 8.0% difference compared to actual power consumption in Central Changwon and is expressed 2.9% compared to that in Masan district. As the power consumption estimation equation for cooling load is expressed difference compared to heating load, it needs to investigate influence for cooling load.

• Journal of the Korean Solar Energy Society
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• v.26 no.3
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• pp.119-125
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• 2006

The impacts of climate changes on building energy demand were investigated by means of the degree-days method. Future trends for the 21st century was assessed based on climate change scenarios with 7 global climate models(GCMs). We constructed hourly weather data from monthly temperatures by Trnsys 16. A procedure to estimate heating degree-days (HDD) and cooling degree-days (CDD) from monthly temperature data was developed and applied to three scenarios for Inchon. In the period 1995-2080, HDD would fall by up to 70%. A significant increase in cooling energy demand was found to occur between 1995-2004(70% based on CDD). During 1995-2080, CDD would Increase by up to 120%. Our analysis shows widely varying shifts in future energy demand depending on season. Heating costs in winter will significantly decrease whereas more expensive electrical cooling energy will be needed.