Methods for benchmarking building energy consumption against its past or intended performance: An overview
•This paper reviews up to date methods for building energy benchmarking.•This paper summarizes the major characteristics of these methods.•This paper recommends a flow chart for reader to choose a proper method. Building sector consumes a significant portion of energy worldwide. One of the reasons i...
Saved in:
Published in | Applied energy Vol. 124; pp. 325 - 334 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Kidlington
Elsevier Ltd
01.07.2014
Elsevier |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | •This paper reviews up to date methods for building energy benchmarking.•This paper summarizes the major characteristics of these methods.•This paper recommends a flow chart for reader to choose a proper method.
Building sector consumes a significant portion of energy worldwide. One of the reasons is that the performance of building and its components degrades over the years. It is found that by improving the performance of existing systems through continuous commissioning, significant energy saving can be achieved. In a continuous commissioning process, energy benchmarking is extremely important for tracking, monitoring and detecting abnormal energy consumption behavior of a building. In this paper, up to date methods and tools available for energy benchmarking purpose are reviewed. It is hoped that with this paper, researchers and building operators are more confident in choosing a proper method (or tool) during the commissioning process. |
---|---|
AbstractList | Building sector consumes a significant portion of energy worldwide. One of the reasons is that the performance of building and its components degrades over the years. It is found that by improving the performance of existing systems through continuous commissioning, significant energy saving can be achieved. In a continuous commissioning process, energy benchmarking is extremely important for tracking, monitoring and detecting abnormal energy consumption behavior of a building. In this paper, up to date methods and tools available for energy benchmarking purpose are reviewed. It is hoped that with this paper, researchers and building operators are more confident in choosing a proper method (or tool) during the commissioning process. •This paper reviews up to date methods for building energy benchmarking.•This paper summarizes the major characteristics of these methods.•This paper recommends a flow chart for reader to choose a proper method. Building sector consumes a significant portion of energy worldwide. One of the reasons is that the performance of building and its components degrades over the years. It is found that by improving the performance of existing systems through continuous commissioning, significant energy saving can be achieved. In a continuous commissioning process, energy benchmarking is extremely important for tracking, monitoring and detecting abnormal energy consumption behavior of a building. In this paper, up to date methods and tools available for energy benchmarking purpose are reviewed. It is hoped that with this paper, researchers and building operators are more confident in choosing a proper method (or tool) during the commissioning process. |
Author | Xu, Peng Li, Zhengwei Han, Yanmin |
Author_xml | – sequence: 1 givenname: Zhengwei orcidid: 0000-0001-5941-5874 surname: Li fullname: Li, Zhengwei email: zhengwei_li@tongji.edu.cn – sequence: 2 givenname: Yanmin surname: Han fullname: Han, Yanmin – sequence: 3 givenname: Peng surname: Xu fullname: Xu, Peng |
BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28475777$$DView record in Pascal Francis |
BookMark | eNqFkc1u1DAUhS3USkxbXgF5g8QmqX8ydoxYUFVAkYq6KWvLca6nHjJ2sD2t-vY4TLthMyvfxTnn-n7nDJ2EGACh95S0lFBxuW3NDAHS5rllhHYt4S1h5A1a0V6yRlHan6AV4UQ0TFD1Fp3lvCWEMMrICm1_QnmIY8YuJjxAsA87k377sMHD3k_jMhyysY0h73dz8TFgszE-5IJ9yXg2dahmHwqEEUY8Q6phOxMsfMJXAcdHSI8eni7QqTNThncv7zn69e3r_fVNc3v3_cf11W1jO9KXhjpFmKLO9B01ggsjlO3WarCS930n13I0pAPGnLRyAOfo2gkrQPLB8GHsGD9HHw-5c4p_9pCL3vlsYZpMgLjPmlVqnEul5FEpXXeE8b4Tqko_vEhNtmZyqd7ns56Tr8CeNfv3NblEfj7obIo5J3Da-mIWaiUZP2lK9NKa3urX1vTSmiZc19aqXfxnf91w1PjlYISKtuJOOltf-4TRJ7BFj9Efi_gLsme5ag |
CODEN | APENDX |
CitedBy_id | crossref_primary_10_1016_j_adapen_2022_100084 crossref_primary_10_1016_j_enbuild_2022_112307 crossref_primary_10_1016_j_enbuild_2021_110886 crossref_primary_10_1016_j_apenergy_2018_10_025 crossref_primary_10_1016_j_enbuild_2020_109810 crossref_primary_10_1016_j_jobe_2019_02_003 crossref_primary_10_3390_buildings15060879 crossref_primary_10_15377_2409_5818_2018_05_3 crossref_primary_10_3390_ijerph17228354 crossref_primary_10_3390_su16030964 crossref_primary_10_1016_j_knosys_2022_108970 crossref_primary_10_1016_j_enbuild_2021_111219 crossref_primary_10_1080_19401493_2024_2444334 crossref_primary_10_1061__ASCE_ME_1943_5479_0000741 crossref_primary_10_2139_ssrn_4180073 crossref_primary_10_1016_j_jobe_2023_106148 crossref_primary_10_1016_j_segan_2018_05_004 crossref_primary_10_1016_j_jclepro_2022_131040 crossref_primary_10_1080_23744731_2019_1693208 crossref_primary_10_1016_j_enbuild_2023_113195 crossref_primary_10_1016_j_tsep_2023_101835 crossref_primary_10_1016_j_jobe_2023_108287 crossref_primary_10_1016_j_jclepro_2019_04_064 crossref_primary_10_1016_j_enbuild_2018_08_031 crossref_primary_10_1016_j_tust_2022_104655 crossref_primary_10_1016_j_enbuild_2021_111208 crossref_primary_10_1016_j_apenergy_2017_08_153 crossref_primary_10_1016_j_apenergy_2016_03_083 crossref_primary_10_1016_j_applthermaleng_2016_01_154 crossref_primary_10_1016_j_rser_2017_09_108 crossref_primary_10_1051_e3sconf_202235601031 crossref_primary_10_1016_j_apenergy_2015_06_043 crossref_primary_10_1016_j_seta_2020_100770 crossref_primary_10_1016_j_enbuild_2016_11_037 crossref_primary_10_1016_j_apenergy_2016_04_035 crossref_primary_10_1016_j_enbuild_2021_111683 crossref_primary_10_1016_j_jobe_2022_105468 crossref_primary_10_1016_j_rser_2017_04_095 crossref_primary_10_1016_j_ijrefrig_2022_12_027 crossref_primary_10_3390_atmos10120743 crossref_primary_10_1016_j_apenergy_2017_07_100 crossref_primary_10_3390_en11030631 crossref_primary_10_1016_j_enbuild_2019_04_029 crossref_primary_10_1016_j_energy_2015_02_014 crossref_primary_10_1016_j_energy_2017_05_148 crossref_primary_10_1016_j_enbuild_2018_07_039 crossref_primary_10_1016_j_apenergy_2020_114614 crossref_primary_10_3390_en14133900 crossref_primary_10_1016_j_enbuild_2023_112920 crossref_primary_10_1016_j_enbuild_2018_03_066 crossref_primary_10_1016_j_enbenv_2019_11_003 crossref_primary_10_1177_1420326X211054429 crossref_primary_10_1016_j_apenergy_2019_113500 crossref_primary_10_1016_j_scs_2024_105844 crossref_primary_10_1088_1757_899X_609_7_072006 crossref_primary_10_1016_j_apenergy_2016_02_030 crossref_primary_10_1016_j_enbuild_2020_110238 crossref_primary_10_1016_j_rser_2022_113045 crossref_primary_10_1016_j_enbuild_2020_110635 crossref_primary_10_1186_s40327_018_0064_7 crossref_primary_10_1016_j_enbuild_2020_110230 crossref_primary_10_1016_j_scs_2019_101835 crossref_primary_10_3390_en15051741 crossref_primary_10_1016_j_enbuild_2018_06_056 crossref_primary_10_1016_j_apenergy_2016_07_043 crossref_primary_10_1016_j_enbuild_2016_07_018 crossref_primary_10_1016_j_enbuild_2022_112502 crossref_primary_10_1016_j_jclepro_2018_04_270 crossref_primary_10_1016_j_enbuild_2024_114803 crossref_primary_10_1016_j_energy_2022_123161 crossref_primary_10_1109_JPROC_2016_2520638 crossref_primary_10_1016_j_enpol_2016_01_012 crossref_primary_10_1007_s12053_017_9582_8 crossref_primary_10_1016_j_enbuild_2022_112508 crossref_primary_10_1016_j_jobe_2017_01_005 crossref_primary_10_1002_gch2_201900065 crossref_primary_10_1016_j_energy_2016_08_028 crossref_primary_10_1016_j_enbuild_2014_07_028 crossref_primary_10_3390_data10030035 crossref_primary_10_1016_j_apenergy_2017_09_060 crossref_primary_10_1016_j_apenergy_2020_115413 crossref_primary_10_3390_technologies10060131 crossref_primary_10_1016_j_enbuild_2021_111486 crossref_primary_10_1016_j_enbuild_2022_112238 crossref_primary_10_3390_en16196879 crossref_primary_10_1016_j_scs_2020_102101 crossref_primary_10_1007_s12053_018_9717_6 crossref_primary_10_1016_j_proeng_2015_09_097 crossref_primary_10_1016_j_eswa_2021_116293 crossref_primary_10_1016_j_comcom_2019_12_020 crossref_primary_10_1016_j_apenergy_2018_05_023 crossref_primary_10_1016_j_enbuild_2019_07_012 crossref_primary_10_1016_j_apenergy_2017_05_052 crossref_primary_10_1016_j_eswa_2022_117649 crossref_primary_10_1016_j_buildenv_2019_04_016 crossref_primary_10_1016_j_rser_2016_01_086 crossref_primary_10_1016_j_rser_2025_115471 crossref_primary_10_3390_en14164850 crossref_primary_10_1016_j_ijrefrig_2018_10_017 crossref_primary_10_1016_j_energy_2015_02_084 crossref_primary_10_1016_j_apenergy_2017_08_237 crossref_primary_10_1016_j_jclepro_2020_125623 crossref_primary_10_1016_j_rser_2016_11_132 crossref_primary_10_1016_j_enbuild_2020_110304 crossref_primary_10_1016_j_apenergy_2019_113548 crossref_primary_10_1016_j_apenergy_2022_119989 crossref_primary_10_1016_j_enbuild_2018_08_040 crossref_primary_10_1007_s10586_022_03573_8 crossref_primary_10_1016_j_egypro_2015_11_754 crossref_primary_10_3390_app10186489 crossref_primary_10_1016_j_autcon_2020_103188 crossref_primary_10_1016_j_enbuild_2023_113419 crossref_primary_10_1016_j_ijepes_2021_106916 crossref_primary_10_1016_j_apenergy_2017_09_116 crossref_primary_10_1016_j_autcon_2020_103344 crossref_primary_10_1002_er_7376 crossref_primary_10_1016_j_jobe_2023_105915 crossref_primary_10_1108_BIJ_02_2023_0099 crossref_primary_10_3390_buildings13112685 crossref_primary_10_1016_j_enbuild_2022_112761 crossref_primary_10_1016_j_enbuild_2015_04_017 crossref_primary_10_1016_j_jobe_2022_104103 crossref_primary_10_1016_j_apenergy_2021_117960 crossref_primary_10_1016_j_enbuild_2024_114581 crossref_primary_10_1016_j_energy_2019_116552 crossref_primary_10_3390_land11111986 crossref_primary_10_1016_j_apenergy_2019_02_056 crossref_primary_10_3390_en17020376 crossref_primary_10_3390_w14030473 crossref_primary_10_3992_1943_4618_14_3_1 crossref_primary_10_1016_j_enbuild_2021_111149 crossref_primary_10_3390_en13195171 crossref_primary_10_1007_s12053_018_9639_3 crossref_primary_10_1016_j_aej_2020_08_022 crossref_primary_10_1061__ASCE_LA_1943_4170_0000532 crossref_primary_10_1016_j_jobe_2023_108185 crossref_primary_10_1016_j_apenergy_2023_121165 crossref_primary_10_5327_z2176_947820200722 crossref_primary_10_1016_j_energy_2022_123341 crossref_primary_10_1016_j_buildenv_2024_112366 crossref_primary_10_1016_j_proeng_2017_10_055 crossref_primary_10_1016_j_apenergy_2015_02_048 crossref_primary_10_1016_j_jobe_2021_102837 crossref_primary_10_1016_j_rser_2016_04_052 crossref_primary_10_1016_j_apenergy_2015_04_036 crossref_primary_10_1109_ACCESS_2019_2906311 |
Cites_doi | 10.1016/j.enbuild.2011.05.020 10.1016/j.buildenv.2007.11.004 10.1016/j.enconman.2008.08.033 10.1016/j.rser.2012.02.049 10.2172/787155 10.1016/j.energy.2006.11.010 10.1080/10789669.2007.10390952 10.1016/j.enbuild.2013.02.050 10.1016/j.apenergy.2012.09.005 10.1016/j.apenergy.2013.05.040 10.1016/j.apenergy.2006.04.002 10.1016/j.enconman.2007.03.018 10.1016/j.enbuild.2010.07.027 10.1016/j.enbuild.2013.03.035 10.1109/59.99410 10.1016/j.rser.2007.11.007 10.1016/j.ijthermalsci.2005.06.009 10.1016/j.enbuild.2010.11.002 10.1016/j.enbuild.2011.12.029 10.1080/10789669.2002.10391290 10.1016/j.enbuild.2012.08.038 10.1016/j.buildenv.2006.10.027 10.1016/S0378-7788(01)00137-2 10.1016/S0378-7788(01)00092-5 10.1016/j.apenergy.2003.12.006 10.1016/j.apenergy.2012.10.031 10.1016/j.apenergy.2010.11.022 10.1080/19401490903414454 10.1016/j.simpat.2010.11.002 10.1016/S0360-1323(00)00026-3 10.1016/j.rser.2008.03.006 10.1016/j.enbuild.2005.11.005 10.1016/j.enbuild.2004.09.009 10.1016/j.apenergy.2013.08.093 10.1016/j.enbuild.2010.04.006 10.1080/0961321042000325327 10.1016/j.apenergy.2008.11.035 10.1016/j.enbuild.2012.06.024 |
ContentType | Journal Article |
Copyright | 2014 Elsevier Ltd 2015 INIST-CNRS |
Copyright_xml | – notice: 2014 Elsevier Ltd – notice: 2015 INIST-CNRS |
DBID | AAYXX CITATION IQODW 7ST 7U6 C1K SOI 7S9 L.6 |
DOI | 10.1016/j.apenergy.2014.03.020 |
DatabaseName | CrossRef Pascal-Francis Environment Abstracts Sustainability Science Abstracts Environmental Sciences and Pollution Management Environment Abstracts AGRICOLA AGRICOLA - Academic |
DatabaseTitle | CrossRef Environment Abstracts Sustainability Science Abstracts Environmental Sciences and Pollution Management AGRICOLA AGRICOLA - Academic |
DatabaseTitleList | AGRICOLA Environment Abstracts |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering Environmental Sciences Applied Sciences |
EISSN | 1872-9118 |
EndPage | 334 |
ExternalDocumentID | 28475777 10_1016_j_apenergy_2014_03_020 S0306261914002505 |
GroupedDBID | --K --M .~1 0R~ 1B1 1~. 1~5 23M 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AABNK AACTN AAEDT AAEDW AAHCO AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARJD AAXUO ABJNI ABMAC ABXDB ABYKQ ACDAQ ACGFS ACRLP ADBBV ADEZE ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHIDL AHJVU AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AXJTR BELTK BJAXD BKOJK BLXMC CS3 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FDB FIRID FNPLU FYGXN G-Q GBLVA IHE J1W JARJE JJJVA KOM LY6 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RIG ROL RPZ SDF SDG SES SPC SPCBC SSR SST SSZ T5K TN5 ~02 ~G- AAHBH AAQXK AATTM AAXKI AAYOK AAYWO AAYXX ABEFU ABFNM ABWVN ACNNM ACRPL ACVFH ADCNI ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AFXIZ AGCQF AGQPQ AGRNS AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP ASPBG AVWKF AZFZN BNPGV CITATION FEDTE FGOYB G-2 HVGLF HZ~ R2- SAC SEW SSH WUQ ZY4 ABTAH IQODW 7ST 7U6 C1K SOI 7S9 L.6 |
ID | FETCH-LOGICAL-c408t-1f90291fa841a636a69c459bc73884757da04e22f7c7beff15f6c6e73ba3bd423 |
IEDL.DBID | .~1 |
ISSN | 0306-2619 |
IngestDate | Thu Jul 10 17:45:23 EDT 2025 Fri Jul 11 06:38:42 EDT 2025 Wed Apr 02 07:25:22 EDT 2025 Tue Jul 01 03:05:23 EDT 2025 Thu Apr 24 23:02:03 EDT 2025 Fri Feb 23 02:36:56 EST 2024 |
IsPeerReviewed | true |
IsScholarly | true |
Keywords | Building Overview Energy benchmarking Energy consumption Performance Buildings |
Language | English |
License | CC BY 4.0 |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c408t-1f90291fa841a636a69c459bc73884757da04e22f7c7beff15f6c6e73ba3bd423 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ORCID | 0000-0001-5941-5874 |
PQID | 1540238469 |
PQPubID | 23462 |
PageCount | 10 |
ParticipantIDs | proquest_miscellaneous_2101337997 proquest_miscellaneous_1540238469 pascalfrancis_primary_28475777 crossref_citationtrail_10_1016_j_apenergy_2014_03_020 crossref_primary_10_1016_j_apenergy_2014_03_020 elsevier_sciencedirect_doi_10_1016_j_apenergy_2014_03_020 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2014-07-01 |
PublicationDateYYYYMMDD | 2014-07-01 |
PublicationDate_xml | – month: 07 year: 2014 text: 2014-07-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | Kidlington |
PublicationPlace_xml | – name: Kidlington |
PublicationTitle | Applied energy |
PublicationYear | 2014 |
Publisher | Elsevier Ltd Elsevier |
Publisher_xml | – name: Elsevier Ltd – name: Elsevier |
References | Li, Meng, Cai (b0135) 2009; 86 Curtin JM. The development and testing of an automated building commissioning analysis tool (ABCAT), Master thesis, Texas A&M University, College Station, U.S.; 2007. Li, Meng, Cai (b0140) 2009; 50 Lee, Braun (b0210) 2008; 43 Saltelli, Chan, Scott (b0330) 2000 Papalexopoulos, Hesterberg (b0115) 1990; 5 Chung (b0060) 2011; 88 Katipamula, Pratt, Chassin (b0095) 1999; 105 Claridge DE, Culp CH, Liu M, et al. Campus-wide continuous commissioning of university buildings, ACEEE 2000 Summer Study on Energy Efficiency in Buildings, Pacific Grove, U.S., August 20–25, 2000. Reddy, Maor, Panjapornpon (b0280) 2007; 13 Santos J, Brightbill L. Automated diagnostics from DDC data – PACRAT. In: Proceedings of the 8th National conference on building commissioning, Kansas City, U.S., May 3–5, 2000. 2013. Wang, Greenberg, Flegel (b0270) 2013; 102 Lin, Hong (b0265) 2013; 111 O’Neill Z, Shashanka M, Pang X et al. Real time model-based energy diagnostics in buildings. In: 12th IBPSA Conference, Sydney, Australia, November 14–16, 2011. Raftery, Keane, O’Nonnell (b0285) 2011; 43 Heo, Choudhary, Augenbroe (b0075) 2012; 47 Holcomb, Li, Seshia (b0305) 2009 Li X, Lu J, Ding L et al. Building cooling load forecasting model based on LS-SVM. In: Asia-Pacific conference on information processing, Shenzhen, China, July 18–19, 2009. Wang, Xu (b0200) 2006; 45 Lee SH, Zhao F, Augenbroe G. The use of normative energy calculation beyond building performance rating systems. In: 12th IBPSA Conference, Sydney, Australia, November 14–16, 2011. Fumo, Mago, Luck (b0260) 2010; 42 Djuric, Novakovic (b0030) 2009; 13 Mui, Wong, Law (b0085) 2007; 84 Augenbroe, Park (b0070) 2005; 33 Mihalakakou, Santamouris, Tsangrassoulis (b0170) 2002; 34 CEN, EN 15241:2007, Ventilation for buildings. Calculation methods for energy losses due to ventilation and infiltration in buildings; 2007. ISO, ISO 13789:2007, Thermal performance of buildings – Transmission and ventilation heat transfer coefficients – calculation method; 2007. Li, Huang (b0120) 2013; 62 Bynum, Claridge, Curtin (b0240) 2012; 55 Jacob, Dietz, Komhard (b0125) 2010; 3 Yiu, Wang (b0130) 2007; 48 Braun, Chaturvedi (b0205) 2002; 8 Lv, Lu, Kibert (b0230) 2014; 114 Knebel DE. Simplified energy analysis using the modified bin method – prepared for the American Society of Heating, Refrigerating and Air-Conditioning Engineers, ASHRAE, Atlanta, GA; 1983. Crawley, Lawrie, Pedersen (b0040) 2000; 42 Tso, Yau (b0185) 2007; 32 ASHRAE, ASHRAE Guideline 14: measurement of energy and demand savings, American Society of Heating, Refrigerating, and Air-conditioning Engineers Inc., Atlanta, GA, 2002. Friedman H, Piette MA. Comparative guide to emerging diagnostic tools for large commercial HVAC systems, Lawrence Berkeley National Laboratory Report (No. 48629); 2001. Federal Energy Management Program (FEMP). Continuous Commissioning Guidebook for Federal Managers. Federspiel, Zhang, Arens (b0080) 2002; 34 Roth, Llana, Westphalen (b0055) 2005; 47 Chidiac, Catania, Morofsky (b0255) 2011; 43 Magoules, Zhao, Elizondo (b0180) 2013; 62 Philp Haves. Fault modelling in component-based HVAC simulation. In: Fifth international IBPSA conference, Prague, Czech, September 8–10, 1997. Crawley, Hand, Kummert (b0090) 2008; 43 Torrens, Keane, Costa (b0250) 2011; 19 IEA, Key world energy statistics; 2009. Zhao, Magoules (b0065) 2012; 16 Manfren, Aste, Moshksar (b0160) 2013; 103 Yu, Haghighat, Fung (b0190) 2010; 42 Aydinalp, Ugursal, Fung (b0165) 2004; 79 Heo, Zavala (b0155) 2012; 53 Tarlow D, Peterman A, Schwegler BR, et al. Automatically calibrating a probabilistic graphical model of building energy consumption. In: 11th IBPSA Conference, Glasgow, Scotland, July 27–30, 2009. Al-Homoud (b0050) 2001; 36 Facility dynamics. Dong, Cao, Lee (b0150) 2005; 37 Karatasou, Santamouris, Geros (b0175) 2006; 38 Xiao, Wang (b0015) 2009; 13 Mui (10.1016/j.apenergy.2014.03.020_b0085) 2007; 84 Li (10.1016/j.apenergy.2014.03.020_b0140) 2009; 50 Li (10.1016/j.apenergy.2014.03.020_b0120) 2013; 62 Heo (10.1016/j.apenergy.2014.03.020_b0075) 2012; 47 10.1016/j.apenergy.2014.03.020_b0320 Fumo (10.1016/j.apenergy.2014.03.020_b0260) 2010; 42 Zhao (10.1016/j.apenergy.2014.03.020_b0065) 2012; 16 10.1016/j.apenergy.2014.03.020_b0315 Raftery (10.1016/j.apenergy.2014.03.020_b0285) 2011; 43 Dong (10.1016/j.apenergy.2014.03.020_b0150) 2005; 37 Reddy (10.1016/j.apenergy.2014.03.020_b0280) 2007; 13 Yiu (10.1016/j.apenergy.2014.03.020_b0130) 2007; 48 Karatasou (10.1016/j.apenergy.2014.03.020_b0175) 2006; 38 Chung (10.1016/j.apenergy.2014.03.020_b0060) 2011; 88 Lee (10.1016/j.apenergy.2014.03.020_b0210) 2008; 43 Crawley (10.1016/j.apenergy.2014.03.020_b0090) 2008; 43 Braun (10.1016/j.apenergy.2014.03.020_b0205) 2002; 8 Saltelli (10.1016/j.apenergy.2014.03.020_b0330) 2000 Wang (10.1016/j.apenergy.2014.03.020_b0270) 2013; 102 10.1016/j.apenergy.2014.03.020_b0310 10.1016/j.apenergy.2014.03.020_b0110 Djuric (10.1016/j.apenergy.2014.03.020_b0030) 2009; 13 10.1016/j.apenergy.2014.03.020_b0105 Xiao (10.1016/j.apenergy.2014.03.020_b0015) 2009; 13 10.1016/j.apenergy.2014.03.020_b0225 Federspiel (10.1016/j.apenergy.2014.03.020_b0080) 2002; 34 Roth (10.1016/j.apenergy.2014.03.020_b0055) 2005; 47 Jacob (10.1016/j.apenergy.2014.03.020_b0125) 2010; 3 Katipamula (10.1016/j.apenergy.2014.03.020_b0095) 1999; 105 Chidiac (10.1016/j.apenergy.2014.03.020_b0255) 2011; 43 Augenbroe (10.1016/j.apenergy.2014.03.020_b0070) 2005; 33 Li (10.1016/j.apenergy.2014.03.020_b0135) 2009; 86 Bynum (10.1016/j.apenergy.2014.03.020_b0240) 2012; 55 10.1016/j.apenergy.2014.03.020_b0145 Heo (10.1016/j.apenergy.2014.03.020_b0155) 2012; 53 10.1016/j.apenergy.2014.03.020_b0025 10.1016/j.apenergy.2014.03.020_b0300 10.1016/j.apenergy.2014.03.020_b0220 10.1016/j.apenergy.2014.03.020_b0100 Lin (10.1016/j.apenergy.2014.03.020_b0265) 2013; 111 Yu (10.1016/j.apenergy.2014.03.020_b0190) 2010; 42 Tso (10.1016/j.apenergy.2014.03.020_b0185) 2007; 32 Manfren (10.1016/j.apenergy.2014.03.020_b0160) 2013; 103 Wang (10.1016/j.apenergy.2014.03.020_b0200) 2006; 45 10.1016/j.apenergy.2014.03.020_b0290 10.1016/j.apenergy.2014.03.020_b0295 10.1016/j.apenergy.2014.03.020_b0010 Al-Homoud (10.1016/j.apenergy.2014.03.020_b0050) 2001; 36 10.1016/j.apenergy.2014.03.020_b0325 10.1016/j.apenergy.2014.03.020_b0005 Holcomb (10.1016/j.apenergy.2014.03.020_b0305) 2009 Aydinalp (10.1016/j.apenergy.2014.03.020_b0165) 2004; 79 Torrens (10.1016/j.apenergy.2014.03.020_b0250) 2011; 19 Magoules (10.1016/j.apenergy.2014.03.020_b0180) 2013; 62 Lv (10.1016/j.apenergy.2014.03.020_b0230) 2014; 114 Mihalakakou (10.1016/j.apenergy.2014.03.020_b0170) 2002; 34 Crawley (10.1016/j.apenergy.2014.03.020_b0040) 2000; 42 Papalexopoulos (10.1016/j.apenergy.2014.03.020_b0115) 1990; 5 |
References_xml | – reference: IEA, Key world energy statistics; 2009. – volume: 47 start-page: 550 year: 2012 end-page: 560 ident: b0075 article-title: Calibration of building energy models for retrofit analysis under uncertainty publication-title: Energy Build – volume: 5 start-page: 1535 year: 1990 end-page: 1547 ident: b0115 article-title: A regression-based approach to short-term system load forecasting publication-title: IEEE Trans Power Syst – reference: Facility dynamics. < – volume: 53 start-page: 7 year: 2012 end-page: 18 ident: b0155 article-title: Gaussian process modelling for measurement and verification of building energy savings publication-title: Energy Build – reference: Curtin JM. The development and testing of an automated building commissioning analysis tool (ABCAT), Master thesis, Texas A&M University, College Station, U.S.; 2007. – reference: ASHRAE, ASHRAE Guideline 14: measurement of energy and demand savings, American Society of Heating, Refrigerating, and Air-conditioning Engineers Inc., Atlanta, GA, 2002. – reference: Philp Haves. Fault modelling in component-based HVAC simulation. In: Fifth international IBPSA conference, Prague, Czech, September 8–10, 1997. – volume: 102 start-page: 1382 year: 2013 end-page: 1390 ident: b0270 article-title: Monitoring-based HVAC commissioning of an existing office building for energy efficiency publication-title: Appl Energy – volume: 33 start-page: 159 year: 2005 end-page: 172 ident: b0070 article-title: Quantification methods of technical building performance publication-title: Build Res Inf – reference: Friedman H, Piette MA. Comparative guide to emerging diagnostic tools for large commercial HVAC systems, Lawrence Berkeley National Laboratory Report (No. 48629); 2001. – reference: Tarlow D, Peterman A, Schwegler BR, et al. Automatically calibrating a probabilistic graphical model of building energy consumption. In: 11th IBPSA Conference, Glasgow, Scotland, July 27–30, 2009. – volume: 105 start-page: 555 year: 1999 end-page: 567 ident: b0095 article-title: Automated fault detection and diagnostics for outdoor-air ventilation systems and economizers: methodology and results from field testing publication-title: ASHRAE Trans – volume: 47 start-page: 82 year: 2005 end-page: 84 ident: b0055 article-title: Automated whole building diagnostics publication-title: ASHRAE J – volume: 114 start-page: 91 year: 2014 end-page: 103 ident: b0230 article-title: A novel dynamic modelling approach for predicting building energy performance publication-title: Appl Energy – volume: 45 start-page: 419 year: 2006 end-page: 432 ident: b0200 article-title: Simplified building model for transient thermal performances estimation using GA-based parameter identification publication-title: Int J Therm Sci – volume: 13 start-page: 1144 year: 2009 end-page: 1149 ident: b0015 article-title: Progress and methodologies of lifecycle commissioning of HVAC systems to enhance building sustainability publication-title: Renew Sustain Energy Rev – volume: 37 start-page: 545 year: 2005 end-page: 553 ident: b0150 article-title: Applying support vector machines to predict building energy consumption in tropical region publication-title: Energy Build – volume: 34 start-page: 727 year: 2002 end-page: 736 ident: b0170 article-title: On the energy consumption in residential buildings publication-title: Energy Build – volume: 88 start-page: 1470 year: 2011 end-page: 1479 ident: b0060 article-title: Review of building energy-use performance benchmarking methodologies publication-title: Appl Energy – volume: 16 start-page: 3586 year: 2012 end-page: 3592 ident: b0065 article-title: A review on the prediction of building energy consumption publication-title: Renew Sustain Energy Rev – reference: >; 2013. – volume: 34 start-page: 203 year: 2002 end-page: 214 ident: b0080 article-title: Model-based benchmarking with application to laboratory buildings publication-title: Energy Build – volume: 13 start-page: 486 year: 2009 end-page: 492 ident: b0030 article-title: Review of possibilities and necessities for building lifetime commissioning publication-title: Renew Sustain Energy Rev – volume: 62 start-page: 442 year: 2013 end-page: 449 ident: b0120 article-title: Re-evaluation of building cooling load prediction models for use in humid subtropical area publication-title: Energy Build – volume: 3 start-page: 53 year: 2010 end-page: 62 ident: b0125 article-title: Black-box models for fault detection and performance monitoring of buildings publication-title: J Build Perform Simul – year: 2000 ident: b0330 article-title: Sensitivity analysis – volume: 43 start-page: 2356 year: 2011 end-page: 2364 ident: b0285 article-title: Calibrating whole building energy models: an evidence-based methodology publication-title: Energy Build – volume: 43 start-page: 661 year: 2008 end-page: 673 ident: b0090 article-title: Contrasting the capabilities of building energy performance simulation programs publication-title: Build Environ – volume: 103 start-page: 627 year: 2013 end-page: 641 ident: b0160 article-title: Calibration and uncertainty analysis for computer models – a meta-model based approach for integrated building energy simulation publication-title: Appl Energy – volume: 79 start-page: 159 year: 2004 end-page: 178 ident: b0165 article-title: Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks publication-title: Appl Energy – volume: 43 start-page: 1755 year: 2008 end-page: 1768 ident: b0210 article-title: Development of methods for determining demand-limiting setpoint trajectories in buildings using short-term measurements publication-title: Build Environ – volume: 42 start-page: 1637 year: 2010 end-page: 1646 ident: b0190 article-title: A decision tree method for building energy demand modelling publication-title: Energy Build – reference: > ; 2013. – volume: 19 start-page: 1258 year: 2011 end-page: 1265 ident: b0250 article-title: Multi-criteria optimisation using past, real time and predictive performance benchmarks publication-title: Simul Model Pract Theory – year: 2009 ident: b0305 article-title: Algorithms for green buildings: learning-based techniques for energy prediction and fault diagnosis, UCB/EECS-2009-138 – reference: Knebel DE. Simplified energy analysis using the modified bin method – prepared for the American Society of Heating, Refrigerating and Air-Conditioning Engineers, ASHRAE, Atlanta, GA; 1983. – reference: O’Neill Z, Shashanka M, Pang X et al. Real time model-based energy diagnostics in buildings. In: 12th IBPSA Conference, Sydney, Australia, November 14–16, 2011. – volume: 36 start-page: 421 year: 2001 end-page: 433 ident: b0050 article-title: Computer-aided building energy analysis techniques publication-title: Build Environ – volume: 62 start-page: 133 year: 2013 end-page: 138 ident: b0180 article-title: Development of an RDP neural network for building energy consumption fault detection and diagnosis publication-title: Energy Build – volume: 84 start-page: 89 year: 2007 end-page: 98 ident: b0085 article-title: An energy benchmarking model for ventilation systems of air-conditioned offices in subtropical climates publication-title: Appl Energy – volume: 48 start-page: 2276 year: 2007 end-page: 2285 ident: b0130 article-title: Multiple ARMAX modelling scheme for forecasting air conditioning system performance publication-title: Energy Convers Manage – reference: Santos J, Brightbill L. Automated diagnostics from DDC data – PACRAT. In: Proceedings of the 8th National conference on building commissioning, Kansas City, U.S., May 3–5, 2000. – volume: 13 start-page: 221 year: 2007 end-page: 241 ident: b0280 article-title: Calibrating detailed building energy simulation programs with measured data – part I: general methodology (RP-1051) publication-title: HVAC&R Res – reference: Federal Energy Management Program (FEMP). Continuous Commissioning Guidebook for Federal Managers. < – reference: ISO, ISO 13789:2007, Thermal performance of buildings – Transmission and ventilation heat transfer coefficients – calculation method; 2007. – volume: 32 start-page: 1761 year: 2007 end-page: 1768 ident: b0185 article-title: Predicting electricity energy consumption: a comparison of regression analysis, decision tree and neural network publication-title: Energy – reference: CEN, EN 15241:2007, Ventilation for buildings. Calculation methods for energy losses due to ventilation and infiltration in buildings; 2007. – volume: 50 start-page: 90 year: 2009 end-page: 96 ident: b0140 article-title: Predicting hourly cooling load in the building: a comparison of support vector machine and different artificial neural networks publication-title: Energy Convers Manage – volume: 8 start-page: 73 year: 2002 end-page: 99 ident: b0205 article-title: An inverse gray-box model for transient building load prediction publication-title: HVAC&R Res – reference: Lee SH, Zhao F, Augenbroe G. The use of normative energy calculation beyond building performance rating systems. In: 12th IBPSA Conference, Sydney, Australia, November 14–16, 2011. – volume: 43 start-page: 614 year: 2011 end-page: 620 ident: b0255 article-title: A screening methodology for implementing cost effective energy retrofit measures in Canadian office buildings publication-title: Energy Build – volume: 42 start-page: 49 year: 2000 end-page: 56 ident: b0040 article-title: Energy plus: energy simulation program publication-title: ASHRAE J. – volume: 111 start-page: 515 year: 2013 end-page: 528 ident: b0265 article-title: On variations of space-heating energy use in office buildings publication-title: Appl Energy – volume: 42 start-page: 2331 year: 2010 end-page: 2337 ident: b0260 article-title: Methodology to estimate building energy consumption using EnergyPlus benchmark models publication-title: Energy Build – volume: 86 start-page: 2249 year: 2009 end-page: 2256 ident: b0135 article-title: Applying support vector machine to predict hourly cooling load in the building publication-title: Appl Energy – volume: 55 start-page: 607 year: 2012 end-page: 617 ident: b0240 article-title: Development and testing of an Automated Building Commissioning Analysis Tool (ABCAT) publication-title: Energy Build – reference: Li X, Lu J, Ding L et al. Building cooling load forecasting model based on LS-SVM. In: Asia-Pacific conference on information processing, Shenzhen, China, July 18–19, 2009. – reference: Claridge DE, Culp CH, Liu M, et al. Campus-wide continuous commissioning of university buildings, ACEEE 2000 Summer Study on Energy Efficiency in Buildings, Pacific Grove, U.S., August 20–25, 2000. – volume: 38 start-page: 949 year: 2006 end-page: 958 ident: b0175 article-title: Modeling and predicting building’s energy use with artificial neural networks: methods and results publication-title: Energy Build – ident: 10.1016/j.apenergy.2014.03.020_b0225 – volume: 43 start-page: 2356 year: 2011 ident: 10.1016/j.apenergy.2014.03.020_b0285 article-title: Calibrating whole building energy models: an evidence-based methodology publication-title: Energy Build doi: 10.1016/j.enbuild.2011.05.020 – volume: 43 start-page: 1755 year: 2008 ident: 10.1016/j.apenergy.2014.03.020_b0210 article-title: Development of methods for determining demand-limiting setpoint trajectories in buildings using short-term measurements publication-title: Build Environ doi: 10.1016/j.buildenv.2007.11.004 – volume: 50 start-page: 90 year: 2009 ident: 10.1016/j.apenergy.2014.03.020_b0140 article-title: Predicting hourly cooling load in the building: a comparison of support vector machine and different artificial neural networks publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2008.08.033 – volume: 16 start-page: 3586 year: 2012 ident: 10.1016/j.apenergy.2014.03.020_b0065 article-title: A review on the prediction of building energy consumption publication-title: Renew Sustain Energy Rev doi: 10.1016/j.rser.2012.02.049 – ident: 10.1016/j.apenergy.2014.03.020_b0110 doi: 10.2172/787155 – ident: 10.1016/j.apenergy.2014.03.020_b0320 – year: 2009 ident: 10.1016/j.apenergy.2014.03.020_b0305 – volume: 32 start-page: 1761 year: 2007 ident: 10.1016/j.apenergy.2014.03.020_b0185 article-title: Predicting electricity energy consumption: a comparison of regression analysis, decision tree and neural network publication-title: Energy doi: 10.1016/j.energy.2006.11.010 – volume: 13 start-page: 221 year: 2007 ident: 10.1016/j.apenergy.2014.03.020_b0280 article-title: Calibrating detailed building energy simulation programs with measured data – part I: general methodology (RP-1051) publication-title: HVAC&R Res doi: 10.1080/10789669.2007.10390952 – year: 2000 ident: 10.1016/j.apenergy.2014.03.020_b0330 – volume: 62 start-page: 133 year: 2013 ident: 10.1016/j.apenergy.2014.03.020_b0180 article-title: Development of an RDP neural network for building energy consumption fault detection and diagnosis publication-title: Energy Build doi: 10.1016/j.enbuild.2013.02.050 – volume: 102 start-page: 1382 year: 2013 ident: 10.1016/j.apenergy.2014.03.020_b0270 article-title: Monitoring-based HVAC commissioning of an existing office building for energy efficiency publication-title: Appl Energy doi: 10.1016/j.apenergy.2012.09.005 – ident: 10.1016/j.apenergy.2014.03.020_b0145 – volume: 111 start-page: 515 year: 2013 ident: 10.1016/j.apenergy.2014.03.020_b0265 article-title: On variations of space-heating energy use in office buildings publication-title: Appl Energy doi: 10.1016/j.apenergy.2013.05.040 – ident: 10.1016/j.apenergy.2014.03.020_b0315 – volume: 84 start-page: 89 year: 2007 ident: 10.1016/j.apenergy.2014.03.020_b0085 article-title: An energy benchmarking model for ventilation systems of air-conditioned offices in subtropical climates publication-title: Appl Energy doi: 10.1016/j.apenergy.2006.04.002 – volume: 48 start-page: 2276 year: 2007 ident: 10.1016/j.apenergy.2014.03.020_b0130 article-title: Multiple ARMAX modelling scheme for forecasting air conditioning system performance publication-title: Energy Convers Manage doi: 10.1016/j.enconman.2007.03.018 – volume: 42 start-page: 2331 year: 2010 ident: 10.1016/j.apenergy.2014.03.020_b0260 article-title: Methodology to estimate building energy consumption using EnergyPlus benchmark models publication-title: Energy Build doi: 10.1016/j.enbuild.2010.07.027 – volume: 62 start-page: 442 year: 2013 ident: 10.1016/j.apenergy.2014.03.020_b0120 article-title: Re-evaluation of building cooling load prediction models for use in humid subtropical area publication-title: Energy Build doi: 10.1016/j.enbuild.2013.03.035 – volume: 5 start-page: 1535 year: 1990 ident: 10.1016/j.apenergy.2014.03.020_b0115 article-title: A regression-based approach to short-term system load forecasting publication-title: IEEE Trans Power Syst doi: 10.1109/59.99410 – volume: 13 start-page: 486 year: 2009 ident: 10.1016/j.apenergy.2014.03.020_b0030 article-title: Review of possibilities and necessities for building lifetime commissioning publication-title: Renew Sustain Energy Rev doi: 10.1016/j.rser.2007.11.007 – ident: 10.1016/j.apenergy.2014.03.020_b0100 – volume: 45 start-page: 419 year: 2006 ident: 10.1016/j.apenergy.2014.03.020_b0200 article-title: Simplified building model for transient thermal performances estimation using GA-based parameter identification publication-title: Int J Therm Sci doi: 10.1016/j.ijthermalsci.2005.06.009 – volume: 43 start-page: 614 year: 2011 ident: 10.1016/j.apenergy.2014.03.020_b0255 article-title: A screening methodology for implementing cost effective energy retrofit measures in Canadian office buildings publication-title: Energy Build doi: 10.1016/j.enbuild.2010.11.002 – volume: 47 start-page: 82 year: 2005 ident: 10.1016/j.apenergy.2014.03.020_b0055 article-title: Automated whole building diagnostics publication-title: ASHRAE J – volume: 47 start-page: 550 year: 2012 ident: 10.1016/j.apenergy.2014.03.020_b0075 article-title: Calibration of building energy models for retrofit analysis under uncertainty publication-title: Energy Build doi: 10.1016/j.enbuild.2011.12.029 – volume: 8 start-page: 73 year: 2002 ident: 10.1016/j.apenergy.2014.03.020_b0205 article-title: An inverse gray-box model for transient building load prediction publication-title: HVAC&R Res doi: 10.1080/10789669.2002.10391290 – ident: 10.1016/j.apenergy.2014.03.020_b0220 – volume: 55 start-page: 607 year: 2012 ident: 10.1016/j.apenergy.2014.03.020_b0240 article-title: Development and testing of an Automated Building Commissioning Analysis Tool (ABCAT) publication-title: Energy Build doi: 10.1016/j.enbuild.2012.08.038 – ident: 10.1016/j.apenergy.2014.03.020_b0005 – volume: 43 start-page: 661 year: 2008 ident: 10.1016/j.apenergy.2014.03.020_b0090 article-title: Contrasting the capabilities of building energy performance simulation programs publication-title: Build Environ doi: 10.1016/j.buildenv.2006.10.027 – volume: 34 start-page: 727 year: 2002 ident: 10.1016/j.apenergy.2014.03.020_b0170 article-title: On the energy consumption in residential buildings publication-title: Energy Build doi: 10.1016/S0378-7788(01)00137-2 – ident: 10.1016/j.apenergy.2014.03.020_b0290 – volume: 105 start-page: 555 year: 1999 ident: 10.1016/j.apenergy.2014.03.020_b0095 article-title: Automated fault detection and diagnostics for outdoor-air ventilation systems and economizers: methodology and results from field testing publication-title: ASHRAE Trans – volume: 34 start-page: 203 year: 2002 ident: 10.1016/j.apenergy.2014.03.020_b0080 article-title: Model-based benchmarking with application to laboratory buildings publication-title: Energy Build doi: 10.1016/S0378-7788(01)00092-5 – ident: 10.1016/j.apenergy.2014.03.020_b0105 – volume: 79 start-page: 159 year: 2004 ident: 10.1016/j.apenergy.2014.03.020_b0165 article-title: Modeling of the space and domestic hot-water heating energy-consumption in the residential sector using neural networks publication-title: Appl Energy doi: 10.1016/j.apenergy.2003.12.006 – ident: 10.1016/j.apenergy.2014.03.020_b0295 – volume: 103 start-page: 627 year: 2013 ident: 10.1016/j.apenergy.2014.03.020_b0160 article-title: Calibration and uncertainty analysis for computer models – a meta-model based approach for integrated building energy simulation publication-title: Appl Energy doi: 10.1016/j.apenergy.2012.10.031 – volume: 88 start-page: 1470 year: 2011 ident: 10.1016/j.apenergy.2014.03.020_b0060 article-title: Review of building energy-use performance benchmarking methodologies publication-title: Appl Energy doi: 10.1016/j.apenergy.2010.11.022 – volume: 3 start-page: 53 year: 2010 ident: 10.1016/j.apenergy.2014.03.020_b0125 article-title: Black-box models for fault detection and performance monitoring of buildings publication-title: J Build Perform Simul doi: 10.1080/19401490903414454 – ident: 10.1016/j.apenergy.2014.03.020_b0010 – ident: 10.1016/j.apenergy.2014.03.020_b0025 – ident: 10.1016/j.apenergy.2014.03.020_b0300 – volume: 19 start-page: 1258 year: 2011 ident: 10.1016/j.apenergy.2014.03.020_b0250 article-title: Multi-criteria optimisation using past, real time and predictive performance benchmarks publication-title: Simul Model Pract Theory doi: 10.1016/j.simpat.2010.11.002 – volume: 36 start-page: 421 year: 2001 ident: 10.1016/j.apenergy.2014.03.020_b0050 article-title: Computer-aided building energy analysis techniques publication-title: Build Environ doi: 10.1016/S0360-1323(00)00026-3 – ident: 10.1016/j.apenergy.2014.03.020_b0325 – volume: 13 start-page: 1144 year: 2009 ident: 10.1016/j.apenergy.2014.03.020_b0015 article-title: Progress and methodologies of lifecycle commissioning of HVAC systems to enhance building sustainability publication-title: Renew Sustain Energy Rev doi: 10.1016/j.rser.2008.03.006 – volume: 42 start-page: 49 year: 2000 ident: 10.1016/j.apenergy.2014.03.020_b0040 article-title: Energy plus: energy simulation program publication-title: ASHRAE J. – volume: 38 start-page: 949 year: 2006 ident: 10.1016/j.apenergy.2014.03.020_b0175 article-title: Modeling and predicting building’s energy use with artificial neural networks: methods and results publication-title: Energy Build doi: 10.1016/j.enbuild.2005.11.005 – volume: 37 start-page: 545 year: 2005 ident: 10.1016/j.apenergy.2014.03.020_b0150 article-title: Applying support vector machines to predict building energy consumption in tropical region publication-title: Energy Build doi: 10.1016/j.enbuild.2004.09.009 – volume: 114 start-page: 91 year: 2014 ident: 10.1016/j.apenergy.2014.03.020_b0230 article-title: A novel dynamic modelling approach for predicting building energy performance publication-title: Appl Energy doi: 10.1016/j.apenergy.2013.08.093 – ident: 10.1016/j.apenergy.2014.03.020_b0310 – volume: 42 start-page: 1637 year: 2010 ident: 10.1016/j.apenergy.2014.03.020_b0190 article-title: A decision tree method for building energy demand modelling publication-title: Energy Build doi: 10.1016/j.enbuild.2010.04.006 – volume: 33 start-page: 159 year: 2005 ident: 10.1016/j.apenergy.2014.03.020_b0070 article-title: Quantification methods of technical building performance publication-title: Build Res Inf doi: 10.1080/0961321042000325327 – volume: 86 start-page: 2249 year: 2009 ident: 10.1016/j.apenergy.2014.03.020_b0135 article-title: Applying support vector machine to predict hourly cooling load in the building publication-title: Appl Energy doi: 10.1016/j.apenergy.2008.11.035 – volume: 53 start-page: 7 year: 2012 ident: 10.1016/j.apenergy.2014.03.020_b0155 article-title: Gaussian process modelling for measurement and verification of building energy savings publication-title: Energy Build doi: 10.1016/j.enbuild.2012.06.024 |
SSID | ssj0002120 |
Score | 2.5009859 |
SecondaryResourceType | review_article |
Snippet | •This paper reviews up to date methods for building energy benchmarking.•This paper summarizes the major characteristics of these methods.•This paper... Building sector consumes a significant portion of energy worldwide. One of the reasons is that the performance of building and its components degrades over the... |
SourceID | proquest pascalfrancis crossref elsevier |
SourceType | Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 325 |
SubjectTerms | Applied sciences Building Energy Energy benchmarking energy conservation Exact sciences and technology monitoring Overview |
Title | Methods for benchmarking building energy consumption against its past or intended performance: An overview |
URI | https://dx.doi.org/10.1016/j.apenergy.2014.03.020 https://www.proquest.com/docview/1540238469 https://www.proquest.com/docview/2101337997 |
Volume | 124 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELaqcgEhBIWK5bEyEtd0E9uJY26rqtUCai9QqTdrnMSwq5JGJL32t3fGcbqtAPXAMZZHGXk8M5_teTD2EQoHpnaQQO19ogyeWcEZkTjUPOcFgCspd_jktFidqS_n-fkOO5xyYSisMtr-0aYHax1HFnE1F916vfhGaJfwPx4RgiOnDHalaZcfXG_DPEQszYiTE5p9J0t4cwBdEzLsKMRLhWKn1Pf77w7qaQc9Lpsf-138YbqDPzp-zp5FIMmXI68v2E7T7rEnd8oL7rH9o20WG06Naty_ZJuT0De654hYucPBn78g3JlzF7tk85FjXoUMzWBWOPyANYJJvh56jlwOHImp2gTdofNum4DwiS9bTpGh9Orwip0dH30_XCWx6UJSqbQcksybVJjMQ6kyKGQBhalUblylZYmeLNc1pKoRwutKu8b7LPdFVTRaOpCuRnC2z3bby7Z5zXhqfFl6PIHpChRI4UQNlc9LAGW89GLG8mmlbRUrklNjjAs7hZ5t7CQhSxKyqbQooRlb3NJ1Y02OBynMJEh7b3dZdBwP0s7vSf72lyIsh9Yz9mHaChZ1kx5coG0ur3qL8JQgkSrMv-fgkTuTUhuj3_wHk2_ZY_oa44jfsd3h91XzHtHS4OZBHebs0fLz19XpDUJnGZE |
linkProvider | Elsevier |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3NTxUxEG8QD0qIUZT4QLEmXpe323a3W26EQJ7K4yIk3Jppd4vvRZcNu1z92512uzyIGg5eu53spNOZ-bWdD0I-QWFAVQYSqJxLhMIzKxjFEoOaZxwDMKXPHZ6fFbML8eUyv1wjR2MujA-rjLZ_sOnBWseRaVzNabtYTL95tOvxPx4RgiN_Qp4KVF_fxmD_1yrOg8XajDg78dPvpQkv96GtQ4qdj_ESodqpb_z9dw-12UKH6-aGhhd_2O7gkE5ekhcRSdLDgdlXZK1utsjGvfqCW2T7eJXGhlOjHnevyXIeGkd3FCErNTj4_SeES3NqYptsOnBMbUjRDHaFwhUsEE3SRd9R5LKnSOzLTfhLdNquMhAO6GFDfWiof3Z4Qy5Ojs-PZknsupBYkZZ9kjmVMpU5KEUGBS-gUFbkyljJS3RluawgFTVjTlppauey3BW2qCU3wE2F6GybrDfXTf2W0FS5snR4BJMWBHBmWAXW5SWAUI47NiH5uNLaxpLkvjPGDz3Gni31KCHtJaRTrlFCEzK9o2uHohyPUqhRkPrB9tLoOR6l3Xsg-btfsrAcUk7Ix3EraFRO_-ICTX1922nEpx4TiUL9ew6euTPOpVJy5z-Y_ECezc7np_r089nXXfLcfxmCit-R9f7mtn6P0Kk3e0E1fgN__xsf |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Methods+for+benchmarking+building+energy+consumption+against+its+past+or+intended+performance%3A+An+overview&rft.jtitle=Applied+energy&rft.au=Li%2C+Zhengwei&rft.au=Han%2C+Yanmin&rft.au=Xu%2C+Peng&rft.date=2014-07-01&rft.pub=Elsevier+Ltd&rft.issn=0306-2619&rft.eissn=1872-9118&rft.volume=124&rft.spage=325&rft.epage=334&rft_id=info:doi/10.1016%2Fj.apenergy.2014.03.020&rft.externalDocID=S0306261914002505 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0306-2619&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0306-2619&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0306-2619&client=summon |