LEADER 03455nam 2200469 450 001 9910483996103321 005 20210330191024.0 010 $a3-030-66211-X 024 7 $a10.1007/978-3-030-66211-0 035 $a(CKB)4100000011758317 035 $a(DE-He213)978-3-030-66211-0 035 $a(MiAaPQ)EBC6476924 035 $a(PPN)253859905 035 $a(EXLCZ)994100000011758317 100 $a20210330d2021 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep energy retrofit - a guide for decision makers /$fAlexander Zhivov, Ru?diger Lohse 205 $a1st ed. 2021. 210 1$aCham, Switzerland :$cEBC :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (XXI, 84 p. 22 illus., 19 illus. in color.) 225 1 $aSpringerBriefs in applied sciences and technology 311 $a3-030-66210-1 327 $aChapter 1. Introduction -- Chapter 2. Deep Energy Retrofit In Public Buildings -- Chapter 3. What Is Deep Energy Retrofit? -- Chapter 4. Deep Energy Retrofit vs Shallow Renovation -- Chapter 5. Major Renovation And Deep Energy Retrofit -- Chapter 6. Product Delivery Quality Assurance Process -- Chapter 7. How To Make Der Cost Effective? -- Chapter 8. Business Models For Der -- Chapter 9. Der Financing -- Chapter 10. Lessons Learned From Pilot Projects -- Chapter 11. Conclusions -- References -- Acronyms and Abbreviations. 330 $aMany governments worldwide are setting more stringent targets for reductions in energy use in government/public buildings. Buildings constructed more than 10 years ago account for a major share of energy used by the building stock. However, the funding and ?know-how? (applied knowledge) available for owner-directed energy retrofit projects has not kept pace with new requirements. With typical retrofit projects, reduction of energy use varies between 10 and 20%, while actual executed renovation projects show that energy use reduction can exceed 50%, and can cost-effectively achieve the Passive House standard or even approach net zero-energy status (EBC Annex 61 2017a, Hermelink and Müller 2010; NBI 2014; RICS 2013; Shonder and Nasseri 2015; Miller and Higgins 2015; Emmerich et al. 2011). Building energy efficiency (EE) ranks first in approaches with resource efficiency potential with a total resource benefit of approximately $700 billion until 2030. EE is by far the cheapest way to cut CO2 emissions (McKinsey 2011, IPCC 2007). However, according to an IEA study (IEA 2014a), more than 80% of savings potential in building sector remains untapped. Thus, the share of deployed EE in the building sector is lower than in the Industry, Transport, and Energy generation sectors. Estimates for the deep renovation potentials show: ?600-900bn investment potential, ?1000-1300bn savings potential, 70% energy-saving potential, and 90% CO2 reduction potential. 410 0$aSpringerBriefs in applied sciences and technology. 606 $aBuildings$xEnergy conservation 615 0$aBuildings$xEnergy conservation. 676 $a696 700 $aZhivov$b Alexander M.$01228623 702 $aLohse$b Ru?diger 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483996103321 996 $aDeep energy retrofit - a guide for decision makers$92852381 997 $aUNINA LEADER 03679nam 22008775 450 001 9910483702303321 005 20251226200625.0 010 $a3-319-11900-1 024 7 $a10.1007/978-3-319-11900-7 035 $a(CKB)3710000000249785 035 $a(SSID)ssj0001354290 035 $a(PQKBManifestationID)11893704 035 $a(PQKBTitleCode)TC0001354290 035 $a(PQKBWorkID)11322901 035 $a(PQKB)10687079 035 $a(DE-He213)978-3-319-11900-7 035 $a(MiAaPQ)EBC6302332 035 $a(MiAaPQ)EBC5596348 035 $a(Au-PeEL)EBL5596348 035 $a(OCoLC)891730660 035 $a(PPN)181352222 035 $a(EXLCZ)993710000000249785 100 $a20140919d2014 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aSimulation, Modeling, and Programming for Autonomous Robots $e4th International Conference, SIMPAR 2014, Bergamo, Italy, October 20-23, 2014. Proceedings /$fedited by Davide Brugali, Jan Broenink, Torsten Kroeger, Bruce MacDonald 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (XVI, 594 p. 268 illus.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v8810 300 $aIncludes index. 311 08$a3-319-11899-4 327 $aSimulation -- Modeling -- Programming -- Architectures -- Methods and Tools -- Systems and Applications. 330 $aThis book constitutes the refereed proceedings of the 4th International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2014, held in Bergamo, Italy, in October 2014. The 49 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on simulation, modeling, programming, architectures, methods and tools, and systems and applications. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v8810 606 $aArtificial intelligence 606 $aComputer simulation 606 $aUser interfaces (Computer systems) 606 $aHuman-computer interaction 606 $aComputer science 606 $aComputer networks 606 $aSoftware engineering 606 $aArtificial Intelligence 606 $aComputer Modelling 606 $aUser Interfaces and Human Computer Interaction 606 $aTheory of Computation 606 $aComputer Communication Networks 606 $aSoftware Engineering 615 0$aArtificial intelligence. 615 0$aComputer simulation. 615 0$aUser interfaces (Computer systems). 615 0$aHuman-computer interaction. 615 0$aComputer science. 615 0$aComputer networks. 615 0$aSoftware engineering. 615 14$aArtificial Intelligence. 615 24$aComputer Modelling. 615 24$aUser Interfaces and Human Computer Interaction. 615 24$aTheory of Computation. 615 24$aComputer Communication Networks. 615 24$aSoftware Engineering. 676 $a629.892 702 $aBrugali$b Davide$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aBroenink$b Jan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKroeger$b Torsten$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMacDonald$b Bruce$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483702303321 996 $aSimulation, Modeling, and Programming for Autonomous Robots$9774082 997 $aUNINA