Thesis
Reference
Cost-effective energy retrofit at national building stock level:
Data-driven archetype modelling of the techno-economic energy efficiency potential in the Swiss residential sector
STREICHER, Kai Nino
Abstract
Deep building energy retrofit can lead to a significant reduction of energy demand and environmental impacts, but national retrofit rates in Europe are currently below 1%/a. This thesis therefore aims for a better understanding of the cost-effectiveness of energy retrofit measures, considering technological, geospatial, stakeholder and temporal dimensions. For this, a comprehensive modelling framework for the Swiss residential building stock is developed, comprised of a statistical analysis of energy certificates, a physics-based bottom-up model, dynamic calculation of lifecycle costs and a scenario analysis of possible retrofit pathways. The results confirm: 1) the urgent need for substantial energy demand and impact reduction, 2) the high technical saving potential, 3) moderate to high current economic energy and GHG saving potential 4) high dynamic technical and moderate economic energy and GHG saving potential. This thesis ultimately demonstrates that early and deep energy retrofit can contribute both to the technical and economic potential.
STREICHER, Kai Nino. Cost-effective energy retrofit at national building stock level:
Data-driven archetype modelling of the techno-economic energy efficiency potential in the Swiss residential sector. Thèse de doctorat : Univ. Genève, 2020, no. Sc. 5537
URN : urn:nbn:ch:unige-1486110
DOI : 10.13097/archive-ouverte/unige:148611
Available at:
http://archive-ouverte.unige.ch/unige:148611
Disclaimer: layout of this document may differ from the published version.
UNIVERSITÉ DE GENÈVE FACULTÉ DES SCIENCES Département F.-A. Forel
des sciences de l’environnement et de l’eau Institut des sciences de l’environnement
Professeur M. K. Patel
Cost-effective energy retrofit at national building stock level
Data-driven archetype modelling of the techno-economic energy efficiency potential in the Swiss residential sector
THÈSE
Présentée à la Faculté des sciences de l’Université de Genève
Pour obtenir le grade de Docteur ès sciences, mention sciences de l’environnement
Par
Kai Nino STREICHER
de
Reutlingen (Allemagne)
Thèse N°5537
GENÈVE
Repromail – Université de Genève 2020
Acknowledgments
A CKNOWLEDGMENTS
”Ideas can only be useful, if they become alive in many minds.”
Alexander von Humboldt (1769–1859)
This Ph.D thesis is the result of an interdisciplinary research project over several years, which has only been possible thanks to the expertise, input, advice and support of a large number of organizations and individuals.
Firstly, I would like to thank my supervisor and professor of the Chair of Energy Efficiency at the University of Geneva, Martin K. Patel, whose advice, support and high expectations have given me the chance to always aim and eventually achieve my best results. I am especially grateful that he always kept the door open for all my many questions and for the countless, intense and sometimes almost brain-racking discussions and philosophical excursion on the fine details of all the methodological aspects.
All this work would have not been possible without the financial support and the infrastructure provided by the University of Geneva (UniGE) and the Institute of Environmental Science (ISE). Its staff, as well as the administration at the cantonal and federal level, has allowed and welcomed me to begin my scientific career here in Switzerland.
Furthermore, I would like to thank my colleagues Stefan Schneider, Kapil Narual, David Parra, Meinrad Bürer, and Jad Khury for sharing their specific expertise, as well as for their support and constructive feedback that enabled me to write and substantiality improve my papers. A special thanks to Jonathan Chambers, both for his scientific advice, but in particular for his tireless support of the server and software infrastructure that allowed me - and many others - to reach new levels in modelling and data science.
I am very grateful for the input and critical review of the external examiners of both my pre- doc exam and defence: Nikolaus Diefenbach from the Institute of Buildings and Environment (IWU) in Wuppertal, Germany, and Holger Wallbaum from the Sustainable Building group at Chalmers University, Sweden. Moreover, I would like to thank Claudia Binder and Philippe Thalmann from the École polytechnique fédérale de Lausanne (EPFL) for being part of the jury of my Ph.D. defence and for their interest in my work.
In the framework of this Ph.D. I had the opportunity to work and engage with different organizations and scholars. Among others, I would like to acknowledge Stefan Mennel and Matthias Berger from University of applied Science in Lucerne (HSLU) and Evangelos Panos from Paul-Scherer-Institute (PSI) for their collaboration and their substantial contribution to my different papers, Sabine Sulzer from HSLU for the possibility to present my work to a
Acknowledgments
wider audience, Achim Geißler and Karine Wesselmann from the University of Applied Science Nordwestschweiz (FHNW) for their access and support for the energy certificate data, Andreas Meyer Primavesi and Sabine von Stockar from MINERGIE Switzerland for their collaboration and access to the technical details of their energy retrofit system solutions, as well as Thomas Maurer from HSLU for the access to their heating system cost calculator.
I am very grateful for the scientific collaboration and exchange in the framework of the nationwide Scientific Competence Centre for Energy Research (SCCER), Energy, Society and Transition (CREST), Future Energy Efficient Buildings and Dwellings (FEEB&D) founded by the Swiss Innovation Agency (Innosuisse). A special thanks to Gianfranco Guidati and Adriana Marcucci from ETH Zürich for giving me the possibility to be part of the large-scale research programme Join Activity in Modelling and Simulation (JASM).
I am also taking this opportunity to acknowledge all the invisible heroes that contribute with their time and knowledge to the creation and support of open-source software that has been a crucial element of my work. Among others this concerns the teams of developers and volunteers of R, R-Studio, R-Markdown, Python, PostgreSQL, Q-GIS, Zotero and Stack Overflow. Representative for many, I would like to thank Hadley Wickham for his outstanding software applications and for providing a comprehensive and free online resource on the art of data science.
During this Ph.D. I had the chance to be among a group of fellow Ph.D. students, whose international and interdisciplinary background brought fruitful exchanges on the professional level, but especially in our lively discussions around our coffee table. I would like to mention Gaby and Haein with whom I not only shared the workplace but also a close friendship. A special thanks to my desk neighbour and close friend Stefano for his professional and moral support, and in particular to my colleague, housemate and best buddy Jibran who accompanied me all along my Ph.D. and to many adventures in and around Geneva. I would also like to thank Corinne Galland from the Welcome Center of UniGE for her support in the first months of my arrival, as well as Carole Liernur for offering some of my colleagues and myself our first home in Switzerland.
Finally, all along the way I was supported, encouraged and often visited by my parents, my family and my closest friends. And most importantly, over all these years I had my beloved Elodie by my side, and her unconditional love to follow and support me, as well as her strong belief in me and the pursuit of my lifelong dream to become a scientist.
Table of Contents
T ABLE OF C ONTENTS
MAIN PART
Acknowledgments ... 4
Table of Contents ... 6
Abstract ... 11
Resumé ... 13
List of Publications ... 15
Glossary & Abbreviations ... 17
1 Introduction ... 18
1.1 Context ... 18
1.2 Deep-energy building retrofit ... 20
1.3 Cost-effectiveness in building stocks ... 22
1.4 The Swiss case ... 25
1.5 Scope and outline of thesis ... 32
2 Literature review ... 34
2.1 Building stock modelling ... 34
2.1.1 Model structure & input data ... 35
2.1.2 Energy demand estimation ... 37
2.1.3 Stock dynamics & retrofit decisions ... 39
2.2 Techno-economic analysis ... 41
2.2.1 Economic assessment ... 42
2.2.2 Stakeholders ... 45
2.3 Summary ... 48
3 Methodology & datasets ... 51
3.1 Modelling framework ... 51
3.2 Statistical building stock generation ... 52
3.3 Building stock energy model ... 56
3.4 Techno-economic assessment ... 59
3.4.1 Life-cycle cost ... 60
3.4.2 Retrofit packages for the Swiss building stock ... 67
3.5 Building stock scenario development ... 69
3.5.1 Stock model ... 71
3.5.2 Cash flow and optimization model... 73
4 Results ... 76
4.1 Updates ... 76
4.2 Building stock composition ... 77
4.2.1 Basic statistics of buildings and element surfaces ... 77
Table of Contents
4.2.2 Representativeness of energy certificate data ... 78
4.3 Thermal performance of building elements ... 80
4.3.1 Thermal performance ... 81
4.3.2 Evaluation of the results ... 85
4.4 Energy demand of building stock ... 86
4.4.1 Energy balance and archetype values ... 87
4.4.2 Geospatial and element based distribution ... 91
4.4.3 Evaluation of the results ... 93
4.5 Cost-effectiveness of energy retrofit ... 95
4.5.1 Technical potential ... 96
4.5.2 Energy efficiency cost curves ... 98
4.5.3 Distribution of cost-effectiveness ... 100
4.5.4 Sensitivity and evaluation of the results ... 103
4.6 Retrofit pathways ... 107
4.6.1 Building stock development ... 108
4.6.2 Retrofit pathways ... 109
4.6.3 Retrofit strategies ... 112
4.6.4 Evaluation of the results ... 115
5 Discussion ... 117
5.1 Research questions ... 117
5.1.1 Question A: Origins of high demand and impacts ... 117
5.1.2 Question B: Energy and GHG reductions ... 120
5.1.3 Question C: Cost-effectiveness of energy retrofit ... 123
5.1.4 Question D: Large-scale implementation of energy retrofit ... 126
5.1.5 Summary 129 5.2 Potential of energy retrofit ... 130
5.2.1 Techno-economic saving potential ... 131
5.2.2 Comparison with related studies and policy goals ... 135
5.2.3 Energy retrofit and sustainability ... 137
5.2.4 Summary 146 5.3 Critical review ... 147
5.4 Implications... 153
5.4.1 Scientific implications ... 153
5.4.2 Policy implications ... 156
6 Conclusion ... 160
7 Future Work ... 162
8 References ... 164
Author’s credentials ... 172
Table of Contents
PAPER I
1 Introduction ... 176
2 Methods ... 180
2.1 Archetypes ... 181
2.2 Typical thermal performance ... 183
2.3 National building statistics ... 188
3 Results ... 190
3.1 Representativeness of the sample ... 190
3.2 Basic building data... 191
3.3 Thermal performance ... 192
3.4 Heating system ... 195
4 Discussion ... 197
4.1 Current state of the Swiss residential building stock ... 197
4.2 Potential improvement in the building stock ... 198
4.3 Transferability of the results for the Swiss residential building stock ... 200
5 Conclusion and future work ... 205
6 Appendix A. Results ... 207
7 Supplementary Material ... 211
7.1 CECB and archetype data ... 211
7.1.1 Urban typology... 211
7.1.2 CECB Data (Sample) ... 213
7.2 Typical Thermal Performance Class (TTPC) Determination ... 215
8 References ... 219
PAPER II
1 Introduction ... 2252 Methodology and input data ... 229
2.1 Input data ... 231
2.2 Energy model ... 232
3 Results ... 239
3.1 Energy supply ... 239
3.2 Current energy demand according to SwissRes model ... 240
4 Discussion ... 247
4.1 Energy demand hot spots ... 247
4.2 Model evaluation ... 248
4.3 Sensitivity analysis of input parameters ... 251
5 Conclusions ... 253
Table of Contents
6 Appendix A. Archetypes ... 255
7 Appendix B. Input Values ... 260
8 Appendix C. Sensitivity Analysis ... 264
8.1 Indoor and outdoor temperatures ... 266
8.2 Heating system efficiency ... 267
8.3 Building Envelope ... 267
8.4 Ventilation ... 268
8.5 Correction factor for ERA and occupation ... 268
9 References ... 269
PAPER III
1 Introduction ... 2741.1 Background ... 274
1.2 Techno-economic assessment approaches of building retrofit packages ... 275
1.3 Aims and objectives ... 277
2 Methods and datasets ... 279
2.1 Economic assessment of packages ... 279
2.2 Swiss residential building stock ... 284
1.1. Retrofit packages for Swiss residential building stock ... 285
3 Results ... 290
3.1 Savings and cost of energy retrofit ... 290
3.2 Cost-effectiveness of retrofit packages ... 291
3.3 Sensitivity analysis for economic potential ... 294
4 Discussion ... 297
4.1 Implications of the sensitivity analysis and practical considerations ... 297
4.2 Limitations ... 299
4.3 Comparison with other studies ... 300
5 Conclusions ... 303
6 Supplementary Material A. Definitions and input data ... 307
7 Supplementary Material B. Case study calculations ... 309
7.1 SwissRes energy model ... 309
7.2 Required retrofit actions ... 310
7.3 Energy and cost savings ... 312
7.4 Investment cost estimation ... 315
8 Supplementary Material C. Results... 321
8.1 Savings and cost of retrofit ... 321
1.2. Cost-effectiveness of retrofit ... 325
1.3. Sensitivity analysis ... 328
Table of Contents
9 Supplementary Material D. Comparison with related studies ... 329
9.1 Energy and GHG savings ... 331
9.2 Investment cost ... 332
10References ... 334
PAPER IV
1 Introduction ... 3421.1 Deep energy retrofit scenarios ... 342
1.2 Aims and objectives ... 346
2 Methods ... 347
3 Results ... 351
3.1 Building stock development ... 351
3.2 Retrofit pathways ... 354
4 Discussion ... 359
4.1 Evaluation of retrofit pathways ... 359
4.2 Retrofit strategies for the building stock transformation ... 360
4.3 Limitations & further research ... 364
5 Conclusions and policy implications ... 367
6 Supplementary Material A. Definitions and input data ... 370
7 Supplementary Material B. Methods ... 372
7.1 Stock model ... 374
7.2 Cash flow model ... 378
7.3 Optimization model ... 381
8 Supplementary Material C. Results... 384
8.1 Building stock development ... 384
8.2 Retrofit pathways ... 385
9 Supplementary Material D. Discussion ... 387
9.1 Evaluation of retrofit pathways ... 387
1.1. Policy interventions to enhance retrofit potential ... 393
10References ... 396
Abstract
A BSTRACT
Despite early warnings about devastating effects of overexploitation of natural resources by humanity, our modern lifestyle and its related greenhouse gas (GHG) emissions have brought many essential ecosystems to the brink of collapse. This has triggered a worldwide movement towards sustainable development, with more and more countries aiming towards a net zero emission society. Such a transition requires significant reductions in energy demand, mainly through the implementation of energy efficiency measures. In the European context, this concerns in particular the building stock, which alone accounts for 40% of the total final energy demand. Deep energy retrofit of the building envelope and heating system can lead to a significant reduction of energy demand for space heating and domestic hot water usage. Moreover, this often provides a range of benefits for the owner and occupants of the building that can lead to an overall reduction in cost and therefore economic benefits.
However, national retrofit rates in Europe are currently below 1%, reflecting the building owners’ preferences and/or severe economic constraints. This thesis therefore aims for a better understanding of the cost-effectiveness of energy retrofit measures at the national building stock level, which could be communicated to building owners and policy makers.
Such an analysis requires to incorporate the technological, geospatial, stakeholder and temporal dimensions of energy retrofit in great detail. Switzerland is used as a case study of a wealthy and high-tech country that has set itself very ambitious environmental targets for its building stock, which are, however, currently impeded by structural and economic constraints for deep energy retrofit. This thesis proposes a comprehensive modelling framework comprised of a statistical analysis of energy certificate data, a physics-based bottom-up energy model, dynamic calculation of lifecycle costs and impacts as well as an explorative scenario analysis of possible retrofit pathways. This framework is used to answer research questions concerning (A) the origins of the energy demand and environmental impacts, (B) the energy and GHG reduction potential, (C) the cost-effectiveness and (D) the large-scale implementation of energy retrofit.
Based on the updated and harmonized results of four related journal papers, these questions are addressed in great detail for a large range of archetype buildings and geospatial contexts.
This is complemented by three distinctive economic assessment approaches representing different preferences of building owners, thereby considering: 1) full investment cost and energy savings (FULL), 2) only the cost of energy efficiency improvement (IMP) and 3) additionally accounting for the depreciation of each building element (DEP).
It is shown that the high energy demand and environmental impacts in the stock can be traced back to regions with colder climate in the north-east and south of Switzerland, to older buildings with low performance of their exterior walls or other envelope elements and in
Abstract
particular to inefficient and/or GHG intensive fossil fuel based or direct electric heating systems. Energy retrofit of the entire building stock could currently reduce the total energy demand by up to 86% and up to 92% for the GHG emissions. The related current economic potential of energy and GHG reduction is very low for the FULL (2%, 1%), moderate for the DEP (30%, 42%) and high for the IMP approach (62%, 80%). The scenario analysis showed that despite a switch from older to new buildings and a warmer climate, only an early and deep energy retrofit pathway, as presented by the DEP approach, could lead to cost-optimal (least-cost) and effective cumulated energy and GHG savings in the future. In this regard, the maximum saving pathway could reduce GHG emissions by 90% until 2050, requiring high investment cost and leading to significant trade-offs in economic viability. In contrast, the cost-optimal pathway could still reduce GHG emissions by around 70%.
The results of this thesis for the Swiss residential building stock therefore confirm: 1) the urgent need for substantial energy demand and environmental impact reduction, 2) the high technical saving potential of energy retrofit, 3) moderate to high current economic energy and GHG saving potential for DEP and IMP 4) high dynamic technical energy and GHG saving potential with significant economic trade-offs in contrast to moderate trade-offs in energy and GHG savings for the cost-optimal pathway. In view of these insights, this thesis demonstrates that early and deep energy retrofit can contribute both to a reduction in the high cumulated impacts (energy, GHG) as well as to higher cost savings. To reach these savings, a widespread use of the DEP approach for economic decisions is required that would then follow the cost-optimal trajectory. However, according to the established boundaries for the national techno-economic potential of energy retrofit, this will not be sufficient to reach the ambitious Swiss GHG reduction targets in particular due to the current economic constraints.
Considering these findings and given that energy retrofit at the national building stock level would offer significant additional economic and social benefits, it is recommended to consider substantial financial incentives for deep energy retrofit, which could not only stimulate economic growth and job creation in times of deep recession due to the global pandemic, but could also ensure a transition towards a more sustainable future.
Resumé
R ESUMÉ
Malgré les alertes répétées sur les effets dévastateurs de la surexploitation des ressources naturelles par l'humanité, notre mode de vie moderne et les émissions de gaz à effet de serre (GES) qu’il induit ont amené de nombreux écosystèmes essentiels au bord de l'effondrement.
Ce constat a déclenché un mouvement mondial en faveur du développement durable, conduisant de nombreux pays à prendre des mesures visant la neutralité carbone. Une telle transition nécessite des réductions significatives des besoins énergétiques, principalement par l’implémentation de mesures d'efficience énergétique. Dans le contexte européen, cela concerne en particulier le parc immobilier qui représente à lui seul 40 % du total de la consommation énergétique finale. Dans ce cadre, une rénovation énergétique en profondeur de l'enveloppe du bâtiment et du système de chauffage peut entraîner une réduction significative des besoins énergétiques requis pour le chauffage des locaux et la consommation d'eau chaude sanitaire. En outre, une telle rénovation procure souvent au propriétaire et aux occupants du bâtiment une série d'avantages qui peut conduire à une réduction globale des coûts et donc, à un gain économique.
Cependant, les taux nationaux de rénovation en Europe sont actuellement inférieurs à 1 %, principalement en raison de préférences personnelles des propriétaires et/ou de fortes contraintes économiques. Cette thèse vise donc à mieux comprendre le rapport coût- efficacité des mesures de rénovation énergétique au niveau du parc immobilier national ; une information qui pourrait ensuite être communiquée aux propriétaires de bâtiments ainsi qu’aux décideurs politiques. Une telle analyse nécessite d'intégrer de manière très détaillée l’intérêt des parties prenantes ainsi que les dimensions technologiques, géospatiales et temporelles de la rénovation énergétique. La Suisse est ici utilisée comme cas d’étude d'un pays riche, disposant d’un haut niveau de technologie, qui s’est donné de très ambitieux objectifs environnementaux pour son parc immobilier, lesquels sont actuellement entravés par les contraintes structurelles et économiques de la rénovation énergétique. Cette thèse propose un système de modélisation exhaustif comprenant une analyse statistique de données issues des certificats énergétiques, un modèle énergétique ascendant basé sur la physique des bâtiments, un calcul dynamique des coûts et des impacts du cycle de vie, ainsi qu'une analyse de scénarios exploratoires des voies de rénovations possibles. Cette modélisation est utilisée pour répondre aux questions de recherche concernant (A) les origines des besoins énergétiques et impacts environnementaux, (B) l'énergie et les réductions des GES, (C) le rapport coût-efficacité et (D) la mise en œuvre à grande échelle de la rénovation énergétique.
Sur la base de résultats actualisés de quatre articles scientifiques, ces questions sont abordées de manière détaillée au travers d’une analyse portant sur un large éventail de bâtiments archétypes et de contextes géospatiaux, et suivant trois approches d'évaluation économique distinctes – représentant les préférences des propriétaires de bâtiments – basées sur : 1) le coût total de l'investissement et les économies d'énergie (FULL), 2)
Resumé
uniquement le coût de l'amélioration de l'efficience énergétique (IMP) et 3) additionnellement à ceci, la prise en compte de la dépréciation de chaque élément du bâtiment (DEP).
Il est démontré que les besoins énergétiques et l’impact environnemental élevés du parc immobilier peuvent être imputés aux régions au climat plus froid du nord-est et du sud de la Suisse, aux bâtiments anciens dont les murs extérieurs ou d'autres éléments de l'enveloppe sont peu performants et, en particulier, aux systèmes de chauffage électrique direct ou à base de combustibles fossiles inefficients et/ou à forte intensité de GES. La rénovation énergétique de l'ensemble du parc immobilier pourrait aujourd’hui réduire jusqu’à 86 % des besoins totaux en énergie et jusqu’à 92% des émissions de GES. Le potentiel économique actuel de réduction de l'énergie et des GES est très faible pour l’approche FULL (2 %, 1 %), modéré pour la DEP (30 %, 42 %) et élevé pour l'IMP (62 %, 80 %). L’analyse de scénarios montre que, malgré le remplacement de bâtiments anciens par des nouveaux et un climat plus chaud, seule une voie de rénovation énergétique précoce et approfondie – telle que celle présentée par l'approche DEP – pourrait conduire à des économies d'énergie et de GES cumulées optimales (à coûts minimaux) et efficaces à l'avenir. La voie de l'économie maximale pourrait réduire les émissions de GES de 90 % d’ici à 2050, ce qui nécessiterait cependant un coût d'investissement élevé et générerait des désavantages importants en termes de viabilité économique. En revanche, la voie du coût optimal pourrait tout de même permettre de réduire les GES d’environ 70 %.
Les résultats de cette thèse pour le parc immobilier résidentiel suisse confirment dès lors : 1) l’urgente nécessité d'une réduction substantielle des besoins énergétiques et de l'impact environnemental, 2) le potentiel technique élevé d’économie de la rénovation énergétique, 3) l’actuel potentiel économique modéré à élevé de cette rénovation pour les approches DEP et IMP 4) le potentiel technique dynamique élevé de la rénovation énergétique impliquant de substantiels compromis économiques, par opposition aux compromis modérés de la réduction des besoins énergétiques pour le scenario du coût optimal. Sur base de ces conclusions, cette thèse démontre qu'une rénovation énergétique précoce et approfondie peut contribuer à la fois à une réduction des impacts cumulés élevés sur l’environnement, ainsi qu’à la réduction des coûts qui y sont liés. Une telle voie nécessiterait l’utilisation généralisée de l'approche DEP pour les prises de décisions économiques qui suivraient alors la trajectoire du coût optimal. Toutefois, selon les limites nationales établies pour le potentiel techno-économique de la rénovation énergétique, cette stratégie ne suffira pas pour atteindre les ambitieux objectifs suisses de réduction des GES, notamment en raison des contraintes économiques actuelles.
À la lumière de ces conclusions, et compte-tenu du fait que la rénovation énergétique du parc immobilier national offrirait des avantages économiques et sociaux significatifs, il est recommandé d’envisager des incitations financières substantielles pour encourager la rénovation énergétique en profondeur; ce qui contribuerait non seulement à stimuler la croissance économique et la création d’emplois en ces temps de profonde récession due à la pandémie, mais assurerait également une transition vers un futur plus durable.
List of Publications
L IST OF P UBLICATIONS
This Ph.D. thesis is based on the following papers:
Paper I : K.N. Streicher, P. Padey, D. Parra, M.C. Bürer, M.K. Patel (2018), Assessment of the current thermal performance level of the Swiss residential building stock:
statistical analysis of energy performance certificates, Energy and Buildings 178, 360–378.
https://doi.org/10.1016/j.enbuild.2018.08.032
Paper II : K.N. Streicher, P. Padey, D. Parra, M.C. Bürer, S. Schneider, M.K. Patel (2019), Analysis of space heating demand in the Swiss residential building stock: element- based bottom-up model of archetype buildings, Energy and Buildings 184, 300–322.
https://doi.org/10.1016/j.enbuild.2018.12.011
Paper III : K.N. Streicher, S. Mennel, J. Chambers, D. Parra, M.K. Patel (2020), Cost- effectiveness of large-scale deep energy retrofit packages for residential buildings under different economic assessment approaches, Energy and Buildings 215, 109870.
https://doi.org/10.1016/j.enbuild.2020.109870
Paper IV : K.N. Streicher, M. Berger, E. Panos, K. Narula, M.K. Patel (forthcoming), Optimal building retrofit pathways considering stock dynamics and climate change impacts, submitted to Energy Policy.
In addition, the following publications were authored and co-authored by Kai Nino Streicher in the scope of the Ph.D.:
K.N. Streicher, D. Parra, M.C. Buerer, M.K. Patel (2017), Techno-economic potential of large-scale energy retrofit in the Swiss residential building stock, Energy Procedia 122, 121–126.
https://doi.org/10.1016/j.egypro.2017.07.314
K.N. Streicher, M. Berger, J. Chambers, S. Schneider, M.K. Patel (2019), Combined geospatial and techno-economic analysis of deep building envelope retrofit, Journal of Physics.
https://doi.org/10.1088/1742-6596/1343/1/012028
K. Narula, J. Chambers, K.N. Streicher, M.K. Patel (2019), Strategies for decarbonising the Swiss heating system, Energy. 169, 1119–1131. https://doi.org/10.1016/j.energy.2018.12.082
T. Schluck, K.N. Streicher, S. Mennel (2019), Statistical modelling of the energy reference area based on the Swiss building stock, J. Phys.: Conf. Ser. 1343, 012031. https://doi.org/10.1088/1742- 6596/1343/1/012031
List of Publications
K.N. Streicher, S. Schneider, M.K. Patel (2020), Estimation of load curves for large-scale district heating networks, IOP: Conf. Ser.: Earth Environ. Sci. 588, 052032. https://doi.org/10.1088/1755- 1315/588/5/052032
A.Rinaldi, M.C. Soini, K.N. Streicher, M.K. Patel, D. Parra (2021), Decarbonising heat with optimal PV and storage investments: a detailed sector coupling modelling framework with flexible heat pump operation, Applied Energy 282, 116110. https://doi.org/10.1016/j.apenergy.2020.116110
R. Gupta, A. Pena Bello, K.N. Streicher, C. Roduner, D. Thöni, M.K. Patel, D. Parra (2021), Spatial analysis of distribution grid capacity and costs to enable massive deployment of PV, electric mobility and electric heating, Applied Energy 287, 116504. https://doi.org/10.1016/j.apenergy.2021.116504 M.J.S. Zuberi, K. Narula, S. Klinke, J. Chamber, K.N. Streicher, M.K. Patel (forthcoming), Potential and costs of decentralized heat pumps and thermal networks in Swiss residential areas, submitted to International Journal of Energy Research.
J. Chambers, K.N. Streicher, X. Li, M.K. Patel (forthcoming), Retrofit or heat networks for thermal energy supply decarbonisation: a high-resolution geospatial model, in preparation.
K.N. Streicher, James Allan, Andrew Bollinger (forthcoming), Energy Efficiency Improvement in Buildings. Report for Joint Activity Simulation and Modelling (JASM), in preparation.
M. Meier, H. Ramírez, A. Rinaldi, B. Schroeteler, K.N. Streicher, M. Troxler, H. Weigt (forthcoming), Energy storage in Switzerland. A household model approach linking heat and electricity, in preparation.
Glossary & Abbreviations
G LOSSARY & A BBREVIATIONS
Glossary cost-
effectiveness
Relates the (lifecycle) cost of a project to the expected effectiveness to reach a certain goal by dividing the cost by the effect. In this thesis, “cost-effective retrofit” refers to the cost- effectiveness of measures, which entails an analysis of both the cost-benefit (economic viability) in relation to the achievable effect.
retrofit Energy related constructional change to the building envelope (e.g., additional insulation) or replacement of current heating technology that leads to a significant improvement in energy efficiency.
refurbishment Non-energy related cosmetic change to the building envelope or renewal of existing heating technology to ensure functionality of the building without major improvement of the energy efficiency.
Abbreviations
CECB Cantonal Energy Certificate for Buildings CHF Swiss francs (currency)
DEP Economic assessment approach considering depreciation
DH District Heating
DHW Domestic Hot Water
EE Energy Efficiency
EECC Energy Efficiency Cost Curve EPG Energy Performance Gap
ERA Energy Reference Area (heated area)
FULL Economic assessment approach considering full cost and savings FRBD Swiss Federal Register of Buildings and Dwellings
FSO Swiss Federal Statistical Office GHG Greenhouse gas (emissions) HDD Heating Degree Days
HP Heat Pump
HVACR Heating, ventilation, air conditioning and refrigeration
IMP Economic assessment approach considering improvement cost and savings MFA Material Flow Analysis
MFH Multi Family House NPV Net Present Value SFH Single Family House
SFOE Swiss Federal Office of Energy
SwissRes Swiss Residential Building Stock Model
TTPC Typical Thermal Performance Class (U-Value range)
Introduction
1 I NTRODUCTION
In this section, the context and motivation of the thesis is provided, together with the background of cost-effective energy retrofit. This is complemented by an overview of the Swiss case. Based on this review, the scope and outline of the thesis is defined.
1.1 Context
Tucked away in the Arizona Deserts, stands an enormous glass-and-steel structure that marks the end of a visionary scientific endeavour to recreate the earth’s ecosystem in an artificial enclosure, aiming for the development of a self- sustaining life support system for human space exploration [1,2]. Despite large funding from a Texas oil magnate and euphoric support from top-edge scientists, the $150 million high-tech project called “biosphere 2” could not sustain a fully isolated ecosystem for more than a year, with high drops in oxygen levels requiring the injection of fresh oxygen from “biosphere 1”, our earth, to keep the natural and human population of eight “biospherians” alive [3]. After two attempts and several technical and administrative complications, the project had to be abandoned altogether and successful projects of similar scale have not yet materialized [4].
The lesson that can be drawn from this experiment is that a complete technological re-creation of the ecosystem services of our planet (such as atmospheric regulation, water purification, pollination and soil formation) is, if not impossible, at least a very challenging and costly undertaking1 [5,6]. This is in so far remarkable, since humanity has not only taken ecosystem services that allow life on this planet for granted, but are actually jeopardizing their ability to regenerate themselves.
Already as early as 1819, the German scientist and explorer Alexander von Humboldt warned about the devastating effects of deforestation and drying of marshlands on the micro climate that will have an effect on future generations [7,8]. Modern science has shown that our impacts on nature have even global effects and it is estimated that we crossed at least three out of seven planetary boundaries already (i.e, rate of biodiversity loss, nitrogen cycle and climate change) [9–12]. The highly influential report “Our Common Future” published by the World Commission on Environment and Development in 1987 (also known as
1 A scientific study estimated that the economic value of the world’s ecosystem services are in the range of 16-54$ trillion per year, which they consider as the minimum case [5]
Introduction
the “Brundtland report”), argues for a change and limitations in human activities that ensure a sustainable development that “meets the needs of present without compromising the ability of future generations to meet their own needs” [13]. This leads to the so called triple bottom approach that aims to strikes for a balance between the environment, the economy and the (social) equity, which served as the basis for the formulation of the 17 Sustainable Development Goals proposed by the United Nations [14]. Recent years have seen the creation of a worldwide movement of citizens demanding for a more sustainable future, with more and more countries aiming towards a net zero emission society with binding obligations introduced into their national laws [15–18].
According to the theoretical framework of the American environmentalist Paul Ehrlich2, a general reduction of our environmental impacts can be achieved by either a decrease in population (number of people), decrease in affluence (degree of usage of goods and services per capita), decrease in technological impact (to provide good or service) or in any combination of all three factors [19,20]. With population growth reaching unprecedented levels of additional 80 million per year, an actual reduction of the world’s population seems inevitable in the future but very challenging to realize in the next decades [21]. And so is a reduction in affluence, with the industrialized countries being keen on (at least) keeping their high living standards, while the developing world is rightfully asking for a fair raise of their low living standards, with millions being deprived from even the most basic needs [19].
Given this dilemma, the only feasible lever towards lower environmental impacts at hand currently seems to be the technology side. Here, one of the key aspect is the access to affordable and clean energy, with the energy system sector currently being the dominant contributor to climate change, accounting for at least 60% of the total global greenhouse gas (GHG) emissions [22]. This is due to a very high share of fossil fuels of almost 80% on the total primary energy supply for the OECD countries [23]. Therefore, in order to substantially lower emissions and other environmental impacts, a switch of the existing energy systems, based mainly on fossil fuels, to renewable energy sources is foreseen in many European national energy transition strategies [24]. As for renewable energy sources in Europe, this concerns in particular the development of solar and wind power. However, given
2 The so-called Ehrlich identity is formulated in the following way:
𝐼𝑚𝑝𝑎𝑐𝑡 = 𝑃𝑜𝑝𝑢𝑙𝑎𝑡𝑖𝑜𝑛 ⋅ 𝐴𝑓𝑓𝑙𝑢𝑒𝑛𝑐𝑒 ⋅ 𝑇𝑒𝑐ℎ𝑛𝑜𝑙𝑜𝑔𝑦
Which divided by itself gives the relative change of impact for a relative change in any of the factors.
Introduction
their intermittent availability, balancing of the energy system with high shares of renewables would require high overcapacities and/or large investments for storage, demand side management and network extension, which can themselves lead to high environmental impacts or be subjected to severe social constraints or resistance [25,26]. It is hence important to lower the current energy demand as much as possible to reduce the required capacities and decrease the stress on the energy system infrastructure.
In order to ensure a comparable level of goods and services (as in the industrialized part of the world), while at the same time reducing the energy consumption in the future, the key is Energy Efficiency (EE). This is sometimes also regarded as the “best energy”, since it is actually energy that is not used. The main advantage of EE measures is that they not only allow to fulfil the same functionality with a reduced energy consumption and often lower environmental impacts, but that this - most of the time - also directly translates into a significant reduction of fuel cost [27]. Compared to the existing state, this means that EE measures can lead to a significant saving potential both in environmental and economic terms [28–30]. The International Energy Agency estimates that about 165 Mt oil imports in the world’s major economies has been avoided thanks to a steady increase in EE from 2000 to 2018 [31]. For all the IEA countries combined this accounts for an annual cost reduction in oil-equivalent imports in the range of
$50 billion.
1.2 Deep-energy building retrofit
In the European context, a special focus for energy demand reduction is put on the built environment, which is estimated to account for 40% of the total final energy demand [32]. Two thirds of the building stock do not yet fulfil minimum energy performance standards, which means that in principle substantial energy savings could be achieved in the stock [32]. In this regard, a decrease in thermal energy demand related to space heating and Domestic Hot Water (DHW) seems in particular promising, since this form of demand allows for a more flexible supply that can be more easily stored on a daily basis compared to the electricity demand [30].
The key towards thermal energy demand reduction is deep-energy building retrofit, which usually entails a reduction of transmission and ventilation losses by improvement of the thermal performance of the envelope through increased
Introduction
insulation and more energy efficient windows, as well as the replacement of the current heating, ventilation, air conditioning and refrigeration (HVACR) system with a more energy efficient technology, hence reducing significantly the conversion losses.3 Here, it should be noted that reducing the overall demand does not only mean a subsequent reduction in the energy bill, but might also lead to a smaller required capacity of the heating system and therefore an additional cost reduction compared to the current state. Moreover, studies have shown that almost 50% of all deep-energy retrofit measures can be seen as value-added, which means that a comparable house with low energy demand can generate a premium of up to 9% on the housing market [29,34].
Next to pure economic advantages, there are other additional benefits of energy efficiency investments in buildings as stated by the International Energy Agency:
“improved durability, reduced maintenance, greater comfort, increased habitable space, increased productivity, and improved health and safety“ [35]. In contrast, low thermal efficiency of housing contributes to fuel poverty and cold homes, which can have serious health and other types of impacts on their inhabitants [36,37]. As one example, estimates in the UK show that there is a two-fold increase in probability to develop respiratory problems for children living in cold homes, together with an increased risk for other cardio-vascular and mental diseases [38].
In the extreme cases, around 20% of the total excess winter deaths in England have been traced back to cold homes, accounting for roughly 6,000 losses of lives related to low thermal efficiency in buildings in 2012-2013 [39]. This illustrates well that energy efficiency improvements in buildings are not only a question of environmental or economic aspects, but it can also increases social equity and well-being and might therefore be seen as a crucial element towards a more sustainable future.
However, despite the clear advantages of deep-energy retrofit on a large-scale, the current national retrofit rates per year in Europe are usually below 1% [40].
There are several reasons that might hamper the implementation of energy retrofit measures, ranging from personal (e.g., no information, time or interest to plan and implement a large retrofit project) to severe economic constraints. The latter concerns in general the usually very high required investment cost that need to be provided upfront to pay the deep-energy retrofit measures, as well as the usually
3 Although there is no official definition, the International Energy Agency suggests that a deep-energy retrofit should results in at least a 50% demand reduction [33].
Introduction
very long time spans of more than 20 years to compensate the investment cost by the realized energy cost savings [41]. However, on a long term perspective it has been argued that the implementation of energy efficiency measures can lead to substantial overall cost savings for building owners and would therefore be considered as economically viable [42]. This is particularly true if it is taken into account that buildings anyway have to undergo periodically non-energy related refurbishment4 if their overall functionality is to be preserved [43]. Yet, these long term perspectives are not always understood by or available for building owners.
1.3 Cost-effectiveness in building stocks
Given the implementation gap identified in the previous section, it seems crucial to get a better understanding of the cost-effectiveness of deep-energy retrofit measures at the national building stock level that could be communicated to building owners or policy makers. In this context, a cost-effectiveness analysis relates the (lifecycle) cost of a project to its expected effectiveness to reach a certain goal by dividing the cost by the effect [44]. 5 This might for instance refer to the lifecycle cost that is required to save 1 kWh of energy with a given EE measure.
Such an analysis would necessarily combine technical and socio-economic aspects, and subsequently allow to get a better understanding of the techno- economic saving potential of diverse EE measures [27]. In this way, a comprehensive analysis of the retrofit potential should provide an understanding of [41,42,45,46]:
1) the origins of the high demand
2) how much energy could be saved in different cases 3) in which case this would be economically viable 4) how this could be implemented
Full energy system models (such as TIMES), often incorporate the building stock’s energy demand and possibly respective energy demand reductions based on
4 “Refurbishment” in this study is defined as non-energy related cosmetic change to the building envelope or renewal of existing heating technology to ensure functionality of the building without major improvement of the energy efficiency.
5 Note that “cost-effective” (as an adjective) can be used as a synonym of “profitable”. However,
“profitable” refers to a cost-benefit analysis of cash flows showing an overall cost saving, which does not consider the effectiveness of reaching a goal with these lifecycle costs. In this thesis, “cost- effective retrofit” refers to the consideration of cost-effectiveness, which entails an analysis of the cost-benefit (profitability) in relation to the achievable effect.
Introduction
exogenous statistics or econometric relations, without detailed representation of technological aspects or stock diversification [47–50]. Such models are therefore well suited to examine the interrelations of different energy sectors (including the building stock), but they lack the details to identify the specific origins of high demand as well as the cost-effectiveness of specific EE measures [51].
In contrast, a large number of studies have looked at one or several of these aspects based on the example of detailed case studies ranging from single buildings as well as districts [52–59], to individual cities or regions [43,60–68] or a specific type of building out of a larger stock [69]. These case studies provide very valuable information on the potentials and barriers of deep energy retrofit in their specific context. However their results are not always applicable to the entire (national) stock due to technological and geospatial differences [70–72]. Studies with a representative national scale often neglect the diversity of the different stakeholders that are involved in decision making, which is a crucial element for the implementation of such large-scale projects [44,73,74]. Furthermore, many existing studies omit the temporal dimension and dynamics of implementing EE measures, which however plays an important role when it comes to the assessment of energy transitions in national building stocks [53,75,76].
Against this background, a reliable analysis on cost-effective energy retrofit in large-scale building stocks needs to account for the technological, geospatial, temporal and stakeholder dimensions if questions about demand, economic viability, implementation and policy are to be addressed. As illustrated in Fig. 1.3.1, such an analysis consists then of a wide range of different aspects, with the level of detail at which they can be addressed limited by the acceptable workload or (model) performance [77]. This refers both to each individually dimension as well as to the combination of all dimensions together
From a techno-economic perspective, a comprehensive analysis of the demand and impacts entails a detailed analysis of the building and element characteristics and physics, the technological choices together with their properties (cost, impacts) as well as the spatial distribution and differences [70]. Only a few studies have also accounted for the distribution and probability of already implemented measures [78,79]. However, such a detailed subdivision of the building stock into building components of different age, allows to identify technological solutions among a range of different buildings and can thereby help to significantly reduce environmental impacts and/or lead to overall cost savings. As for the stakeholder
Introduction
dimension, the main aspects are the specific perspective, preferences and conditions that govern the decision process [44,74,80]. These aspects have been considered in scenario building for full energy systems or in evaluation of EE programmes [73,81,82], but are rarely applied in detailed building energy models to estimate the economic viability and subsequently cost-effectiveness of different EE measures.
Fig. 1.3.1 Main dimensions and aspects of cost-effective energy retrofit in large-scale building stocks. Combining the different dimensions (clockwise) allows an analysis of demand and impacts, economic viability, implementation and eventually policy considerations. The level of detail for each and all of the dimensions is limited by the acceptable workload or performance requirements of the analysis.
In terms of temporal dimension, the main aspect is the consideration of dynamics in the building stock, which consist of projecting demolition and new constructions in the future [76,83]. In a few studies this has been extended by the consideration of (naturally) occurring cycles of refurbishment, which is central for an adequate timing of retrofit actions [43,78]. Both aspects allow then to investigate the implementation of energy retrofit on a large-scale. Here, It is important to not just present a future state (e.g., expected energy demand in 2050), but to also consider their evolution of cumulative impacts involved in reaching this state, which will differ between early action, steady implementation and late action [84]. This is done by incorporating step-by-step decisions into the modelling process, which help to identify lock-in effects and non-consistent model decisions. Such pathway
geospatial temporal
technologicalstakeholder
• Building stock
• Building elements
• Physics
• Technologies
• Climate
• Context
• Density
• Perspectives
• Preferences
• Conditions
• Dynamics
• Timings
• Pathways
Workload / performance limits
Cost-effective energy retrofit in
large-scale building stocks
Introduction
studies have been conducted for the transition of full energy systems [26,85,86], but are lacking for of large-scale energy retrofitting.
In conclusion, Fig. 1.3.1 indicates that only a combination of all the four main dimensions with their specific aspects allow a full assessment of the cost- effectiveness of energy retrofit in a large-scale building stock. However, it is neither feasible nor useful to extend all these dimension into infinitely disaggregated details for such large scales. Hence, a trade-off between scope and workload/performance is required. In Section 2, the implications of this constraint are addressed in more detail to determine which available modelling and assessment techniques provide the best trade-off for an analysis of the potential of cost-effectiveness of energy retrofitting in at the national building stock level.
This thesis examines this potential at the example of the Swiss residential building stock. As explained in more detail in the next section, Switzerland provides an interesting case study of a wealthy and high-tech country that has set itself very ambitious environmental targets for its building stock, which are currently hindered by structural and economic constraints for deep energy retrofit, making the trade- off between cost and environmental aspects more challenging.
1.4 The Swiss case
As a consequence of the nuclear accident of Japan in 2011, Switzerland decided to phase out all its nuclear power (representing 34% of the domestic electricity production) and replace it by renewable energy [18]. This gradual decarbonisation and transformation of the national energy system follows the legally binding Energy Strategy 2050, which foresees a significant reduction of final energy demand by 54% from 2000 until 2050 [18]. The Energy Strategy also aims at reducing annual GHG emission levels to 1.5 t CO2eq per capita, which is currently under revision to adopt a net zero GHG emission policy for 2050 [87].
According to the official statistics provided by the Swiss Federal Office of Energy (SFOE), the Energy Strategy 2050 concerns next to transportation in particular the building stock, since buildings contribute around 40%-46% (100 TWh/a) of the total final annual energy demand, making it the largest single consumer [88]. Space heating and domestic hot water (DHW) consumption needs to be mainly targeted, since they accounts for 33.8 % of the total final energy demand from 2012 to 2018 (see Fig. 1.4.1) and is mainly sourced by fossil fuels such as in oil and gas boilers
Introduction
[88]. The largest share of space heating and DHW demand is related to the residential sector, which is the main focus of this thesis.
Fig. 1.4.1 Development of the total final energy demand in Switzerland from 2012 to 2018 by sector and application [88]. Shares of sector and usage that are below 1% of the total are not shown.
Table 1.4.1 shows the development of the energy demand for space heating and DHW, the Energy Reference Area (heated surface – ERA) and the Heating Degree Days (HDD) for the Swiss residential building stock [88]. Since 2000, Switzerland was able to reduce the total demand in the stock by around 11%, even though the ERA was increasing significantly by 35% in the same time frame. This was enabled by a clear reduction in specific demand of roughly 35% from 2000 to 2018. If these numbers are corrected for the change in climate (represented by a 6% decrease of the HDD of 2000) [89], the savings slightly decreases, while still indicating a successful reduction of specific demand in the range of 30% compared to 2000.
However, while the demand reduction from 2000 to 2018 seem large, the average annual change (compared to the current climate corrected specific demand of 2018) decreased significantly over the last years, reaching even an increase of 2.2% from 2017 to 2018 (see Table 1.4.1). At the same time, the average annual change of the total demand is increasing significantly in the last years (i.e., higher reduction over time) to -7% p.a. in 2017 to 2018. Yet, in view of the building stock targets of 54% reduction from 2000 to 2018, the last two decades have seen a
1.8%
4.4%
10.6%
17.7%
4.2%
3.9%
7.2%
2.2%
1.4%
1.4%
2.1%
38.4%
industry residential services transport
2012 2014 2016 2018 2012 2014 2016 2018 2012 2014 2016 2018 2012 2014 2016 2018 0
25 50 75
year
Final energy demand [TWh/a]
application
cooking dhw
hvacr_applicances information_communication lighting
misc processes space heating transport
