• Title/Summary/Keyword: Cooling degree days(CDD)

Search Result 6, Processing Time 0.027 seconds

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

  • Kim, Ji-Hye;Suh, Seung-Jik
    • Journal of the Korean Solar Energy Society
    • /
    • v.26 no.3
    • /
    • pp.119-125
    • /
    • 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.

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

  • Wi, Young-Min
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.66 no.5
    • /
    • pp.745-749
    • /
    • 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.

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

  • Yoo, Byoung Hyun;Kim, Kwang Soo;Lee, Jihye
    • Korean Journal of Agricultural and Forest Meteorology
    • /
    • v.21 no.2
    • /
    • pp.97-109
    • /
    • 2019
  • Degree days have been determined using temperature data measured at nearby weather stations to a site of interest to produce information for supporting decision-making on agricultural production. Alternatively, the data products of Moderate Resolution Imaging Spectroradiometer (MODIS) can be used for estimation of degree days in a given region, e.g., Korean Peninsula. The objective of this study was to develop a simple tool for processing the MODIS product for estimating cooling degree days (CDD), which would help assessment of heat stress conditions for a crop as well as energy requirement for greenhouses. A set of scripts written in R was implemented to obtain temperature profile data for the region of interest. These scripts had functionalities for processing spatial data, which include reprojection, mosaicking, and cropping. A module to extract air temperature at the surface pressure level was also developed using R extension packages such as rgdal and RcppArmadillo. Random forest (RF) models, which estimate mean temperature and CDD with a different set of MODIS data, were trained at 34 sites in South Korea during 2009 - 2018. Then, the values of CDD were calculated over Korean peninsula during the same period using those RF models. It was found that the CDD estimates using the MODIS data explained >74% of the variation in the CDD measurements at the weather stations in North Korea as well as South Korea. These results indicate that temperature data derived from the MODIS atmospheric products would be useful for reliable estimation of CDD. Our results also suggest that the MODIS data can be used for preparation of weather input data for other temperature-based agro-ecological models such as growing degree days or chill units.

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

  • Yoo, Ho Chun;Noh, Kyoung Hwan
    • KIEAE Journal
    • /
    • v.9 no.4
    • /
    • pp.11-16
    • /
    • 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.

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

  • Oh, Hyungna
    • Environmental and Resource Economics Review
    • /
    • v.24 no.3
    • /
    • pp.551-572
    • /
    • 2015
  • Given the presence of global warming, the economic impact of climate changes on output sales has been discussed in the literature, but rarely with empirical evidences. In this present study, a simple log-model was employed to identify the economic impacts of weather changes in manufacturing and service sectors in Korea. For this empirical exercise, weather variables including the CDD (cooling degree days) and HDD (heating degree days) were computed using the Korea's meteorological records covering the period 1970-2012. According to estimation results, 26.7% (144 over 539) and 27.9% (64 over 229) of the manufacturing and service sectors, respectively, are found to be weather-sensitive.

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

  • Jeong, Jee-Hoon;Kim, Joo-Hong;Kim, Baek-Min;Kim, Jae-Jin;Yoo, Jin-Ho;Oh, Jong-Ryul
    • Atmosphere
    • /
    • v.24 no.4
    • /
    • pp.515-522
    • /
    • 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.