에너지경제연구 Korean Energy Economic Review Volume, Number, June 2015 : pp. GCAM-EML 을이용한대형상업용건물에너지 효율변화의장기영향분석
1) < 부표 1> 참조
건축물에너
6) 에너지서비스수요는최종에너지사용량과에너지효율의곱으로정의되고, 일정수준으로점근적으로수렴하는포화함수 (Saturation function) 의형태이다. 따라서특정한에너지서비스수요로의점
근적변화과정에서최종에너지사용량은감소하면서에너지효율은증가하는형태를띤다. 7) 제외된특수용도의건물관련내용은부록참조
8) GCAM 은 JGCRI (Joint Global Change Research Institute, Pacific Northwest National Lab.) 에서개발, 운용하고있는통합평가모형으로 IPCC 5 차보고서작성시 RCP (Representative Concentration Pathway) 4.5 시나리오분석에사용된통합평가모형이다. 미국 Climate Change s Science Program 시나리오분석과 Climate Change Technology Program, Energy Modeling Forum, 기업의기후변화전략과관련한연구, EIA s Climate Economic Model (Integrated Assessment), 그리고 EPA (Environmental Protection Agency) 에서사용되고있다. EML(Energy Modeling Lab,) 은아주대에너지학과의모형연구실을의미하며, GCAM-EML 은 GCAM 모형을소스코드레벨에서확인하고, 새로운데이터구조를정의하여반영할수있는유연한구조의 UI 를추가한프로그램으로국내에너지시스템모형을건물부문, 산업, 수송부문으로세분화한모형이다. ( 참조 : http://eml.ajou.ac.kr/eml/?page_id=692) 9) GCAM 의기후시스템 MAGICC (Model for the Assessment of Greenhouse-Gas Induced Climate Change) 은 Mini-Climate Assessment Model 을개선한프로그램으로각모형에대한자세한정보는각각 https://wiki.umd.edu/gcam/index.php/main_page 와 Brenkert et al., 2003 에서참고할수있다.
< 표 1> GCAM 과 GCAM-EML 의모형세분화 10) 세부내용은 https://wiki.umd.edu/gcam/ 참조
11) Keepin 외 (Nature, 1984) 참조 12) 관련내용은본문에서해당부문모형설명시추가설명을확인할수있다. 13) 대형건물데이터는전수조사자료이며, 건물부문이외에도최종에너지시스템중산업은산업부문은 Yurnaidi et al. (2014) 에상세화작업내용이제시되어있으며, 수송부문은국내자료와 Mishra et al. (2013) 의연구를참고하여상세화하였다.
16) 관련정보는국내조사된값을찾지못하였으나, 최종기준년도값으로보정단계에서식 (1) 의 값을통해기준년도값이보정됨을알수있다.
ln
[ 그림 1] 포화수요를계산하기위한총건물면적, 인구, 노동참여인구의추이 20) Eom 외 (2012) 의 Figure 7, 8 (pp.14. 15) 참조
22) 국내건축물유형별총면적전수의추이에관한자료는국토부건축물대장으로부터확인할수있을것으로보이지만, 현재 raw data 나정리된관련자료가없어확인이불가능하다. 23) 각년도별총조사보고서는전년도의실적에대한조사결과이므로, 이하본연구에서표기할때는각각 2010, 2007, 2004 년도로실적년도기준으로표기함을밝힌다.
< 표 2> 기준년도건물면적 (2010 년 )
< 표 3> 대형상업용건물의단위면적당년간에너지사용량분포추이
kwh
[ 그림 2] 대형상업용건물단위면적당연간에너지사용량 (kwh/ 년 ) 분포
, < 표 4> 대형상업용건물에적용하는 27 개시나리오의내용
31) 각주 15) 의내용을감안하면과도한시나리오라고보기어렵다고사료된다. Yurnaidi (2015). 33) 지식경제부 에너지관리공단 (2010) 에는백열구와형광등의점유율비교자료에서전체를 100 으로볼때 1999 년에는백열구의점유율이 88.8% 이던것이 2009 년에는 37.1% 로하락하였음을보여주고있다. 제시하는대표적인백열전구 (60W) 와형광등 (15W) 을근거로간단한계산을통해, 주어진에너지서비스요구량 100 을충족시키는과정에서필요로하는최종에너지의변화를통해조명부문의효율개선이연평균 5.5% 로계산됨을알수있다.
< 표 5> 시나리오구성요소입력값
±
[ 그림 3] 단위면적당 1 차에너지소비량변화 (2015~2055, ),
[ 그림 4] 기준안대비년도별건물총에너지절감량및누적량 ( 단위 : Bil. KWh, MTOE)
< 표 6> 에너지소비량측면에서본조명기술의시장점유율변화
접수일 (2015 년월일 ), 수정일 (2015 년월일 ), 게재확정일 (2015 년월일 )
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< 부표 1> 에너지총조사부문별에너지소비량 < 부표 2> kwh 이상제외된표본의내용 (2011 년기준 )
< 부표 3> 시나리오별단위면적당 1 차에너지 (kwh/m2) 저감효과
ABSTRACT While various energy efficiency improvement programs with specific energy saving targets are being proposed by governments, the feasibility of those programs and targets are properly assessed in quantitative manner. This research focuses on the enhanced building shell efficiency, efficiency improvement of lighting appliances to reduce cooling energy demand via 9 scenarios discussed in this article using GCAM-EML. Provided in this process of research are quantification of such policy impacts on energy system through scenario simulation results. The results show that this energy efficiency of large buildings are evaluated to be improved at maximum of 4.1% and 8.5% by 2030 and 2055 compared to the reference case. Although this improvement does not seem be large enough, it should be noted that the cumulative energy savings up to 2030 is estimated to be 2.36MTOE and it is 1.16 times of large commercial building energy consumption of 2010 reported by energy survey conducted on 2011. A further detailed research with a more realistic scenarios would better describe how various energy efficiency improvement programs currently deployed affect the overall building s energy efficiency in the future, and this information could be better utilized for the detailed design of various ongoing energy efficiency programs. Key Words:Building Energy Labels or Certificates, Large Commercial Building, Energy Consumption Survey, Energy Efficiency, GCAM-EML