• 제목/요약/키워드: Cooling degree days(CDD)

검색결과 6건 처리시간 0.019초

기후 온난화의 영향에 의한 건물의 냉.난방에너지 수요량 예측 (The Demand Expectation of Heating & Cooling Energy in Buildings According to Climate Warming)

  • 김지혜;서승직
    • 한국태양에너지학회 논문집
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    • 제26권3호
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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.

냉난방도일을 이용한 기준부하추정 방법에 관한 연구 (A Study on the Baseline Load Estimation Method using Heating Degree Days and Cooling Degree Days Adjustment)

  • 위영민
    • 전기학회논문지
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    • 제66권5호
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    • pp.745-749
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    • 2017
  • Climate change and energy security are major factors for future national energy policy. To resolve these issues, many countries are focusing on creating new growth industries and energy services such as smartgrid, renewable energy, microgrid, energy management system, and peer to peer energy trading. The financial and economic evaluation of new energy services basically requires energy savings estimation technologies. This paper presents the baseline load estimation method, which is used to calculate energy savings resulted from participating in the new energy program, using moving average model with heating degree days (HDD) and cooling degree days (CDD) adjustment. To demonstrate the improvement of baseline load estimation accuracy, the proposed method is tested. The results of case studies are presented to show the effectiveness of the proposed baseline load estimation method.

MODIS 대기자료를 활용한 남북한 기상관측소에서의 냉방도일 추정 (The use of MODIS atmospheric products to estimate cooling degree days at weather stations in South and North Korea)

  • 유병현;김광수;이지혜
    • 한국농림기상학회지
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    • 제21권2호
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    • pp.97-109
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    • 2019
  • 적산 온도는 작물 재배 의사결정 지원을 위해 대상지역 주변 기상 관측소의 자료를 활용하여 산정되어 왔다. 한편 Moderate Resolution Imaging Spectroradiometer (MODIS) 자료로부터 공간적인 온도 자료를 바탕으로 특정 지점의 적산 온도 자료를 생산할 수 있다. 본 연구의 목적은 MODIS 자료를 처리하는 도구를 개발하고 이를 바탕으로 작물의 고온 피해도 및 시설의 냉방 요구도 분석에 활용될 수 있는 냉방도일을 계산하고자 하였다. R 스크립트를 사용하여 특정지역의 MODIS 기온자료를 생성하는 모듈들을 작성하였다. 해당 스크립트들은 격자자료의 좌표계 변환과 자료들의 공간적인 통합 기능들을 가지고 있었다. 온도 수직 분포 자료로부터 지표 기압에 해당하는 온도를 추출하는 기능은 rgdal과 RcppArmadillo등의 패키지를 활용하여 구현되었다. 또한 냉방도일 및 일평균온도 추정을 위해 MODIS 기온 자료, day of year, 및 위도를 입력 자료로 사용하는 random forest (RF) 모형을 남한 지역의 24개 지점에 대하여 훈련하였다. 인공위성 자료 별로 훈련된 RF 모형을 사용하여 한반도 지역의 일별 냉방도일을 계산하였다. 특히, 북한지역에 24개 지점에 대해 검증한 결과, MODIS 자료를 바탕으로 추정된 지역별 평균 연간 냉방도일은 관측값 변이의 96%를 설명할 수 있었다. 이러한 결과는 MODIS 자료로부터 유효적산온도 및 난방도일 등 다른 농림 기상 모형의 입력자료 생산을 지원할 수 있다는 것을 암시하였다.

서울과 여수지역에 HadCM3를 적용한 냉」난방도일의 변화량 분석 (Analysis of the cooling and heating degree days in the Seoul and Yeosu, where HadCM3 is applied)

  • 유호천;노경환
    • KIEAE Journal
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    • 제9권4호
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    • pp.11-16
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    • 2009
  • To act and respond to the climate changes and to bring about power-saving in buildings, the changes in the atmospheric data in Korea are recorded and assessed. For the two regions representative of Korea, the data obtained from HadCM3 and actual data are compared and analyzed so as to concretely evaluate and confirm the changes taking place in the cooling and heating degree days in Korea. For the past 40 years, from 1996 to 2005, the number of heating degree days was on the decline and in the two representative regions, between 1980's and 1990's, the number of decrease in the heating degree days had been quite large. The number of cooling degree days showed a trend of increase since the 1970's and just as in the case of heating degree days, the extent of increase was quite large between the 1980's and the 1990's. The results of comparison of the number of heating and cooling degree days, one obtained from the "Korea Meteorological Administration" and another from the HadCM3 data (E127.5,N37.5,E127.5,N35), which is one of the ways of predicting the climate, showed similar trends in the number of heating degree days in the Yeosu area. However, in the case of the number of heating degree days in Seoul and the number of cooling degree days both in Seoul and Yeosu, the differences in the number ranged from a minimum of 300 days to a maximum of 1500 days. This could be attributed to the grid points used in the HadCM3, the differences in the values of latitudes and longitudes of these two locations considered in this study, topographical differences, heat island effect caused by population density etc. and while using the HadCM3, these variables factors must be taken into consideration.

제조업과 서비스 부문 기후 리스크 측정 (Measuring the Weather Risk in Manufacturing and Service Sectors in Korea)

  • 오형나
    • 자원ㆍ환경경제연구
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    • 제24권3호
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    • pp.551-572
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    • 2015
  • 지구 온난화와 그에 따라 발생빈도가 늘어난 이상기온 현상으로 인해 제조업과 서비스 업종에서 감당해야 할 기후위험 역시 증가하는 추세에 있다. 본 연구는 Pardo et al. (2002)이 이용한 간단한 실증모델 추정을 통해 품목별 기후리스크를 측정한다. 실증분석의 결과, 제조업 품목의 26.7%, 서비스 업종의 27.9%가 날씨여건에 따라 판매량이나 경영성과에 유의미한 변화를 경험하고 있는 것으로 나타났다.

미래 기후변화에 따른 가정 및 상업 부문 에너지수요 변화 추정 (Estimation of Energy Use in Residential and Commercial Sectors Attributable to Future Climate Change)

  • 정지훈;김주홍;김백민;김재진;유진호;오종열
    • 대기
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    • 제24권4호
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    • pp.515-522
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    • 2014
  • In this study it is attempted to estimate the possible change in energy use for residential and commercial sector in Korea under a future climate change senario. Based on the national energy use and observed temperature data during the period 1991~2010, the optimal base temperature for determining heating and cooling degree days (HDD and CDD) is calculated. Then, net changes in fossil fuel and electricity uses that are statistically linked with a temperature variation are quantified through regression analyses of HDD and CDD against the energy use. Finally, the future projection of energy use is estimated by applying the regression model and future temperature projections by the CMIP5 results under the RCP8.5 scenario. The results indicate that, overall, the net annual energy use will decrease mostly due to a large decrease in the fossil fuel use for heating. However, a clear seasonal contrast in energy use is anticipated in the electricity use; there will be an increase in a warm-season demand for cooling but a decrease in a cold-season demand for heating.