Abstract
The building sector contributes significantly to global energy consumption and CO2 emissions. It is urgent to reduce them through the retrofit of the current building stock and improvements in new building designs. The energy performance contracts that can deliver energy consumption savings must have an attractive rate of return to make financial sense for public and private sector buildings. These contracts must also have a wide uptake in the market to improve significantly the energy performance of the building stock. This paper develops a hybrid bottom up and system dynamics modelling framework to: (1) explore the diffusion of energy performance contracts and its effect on operational building energy consumption and (2) facilitate integration into policy making. The bottom up modelling component is used to provide estimates of potential operational building energy use savings. The estimates are the input to the system dynamics diffusion model which is used to explore diffusion pathways of energy performance contracts. The framework will facilitate scenario and policy analysis for the diffusion of the contracts on the building stock and their potential impact on energy consumption and associated CO2 emissions.
Similar content being viewed by others
Notes
The author would like to thank a reviewer for raising this point.
The supply side refers to factors that influence the operation of the building and associated energy use, and the demand side refers to factors that alter the behaviour of the occupants and their energy use.
For example, heating set point use of energy-efficient lighting and limited use of building premises after office work hours.
The author thanks a reviewer for suggesting this phrasing.
References
Allcott, H., & Mullainathan, S. (2010). Behavior and energy policy. Science, 327, 1204–1205.
Augenbroe, G., Castro, D., & Ramkrishnan, K. (2009). Decision model for energy performance improvements in existing buildings. Journal of Engineering, Design and Technology, 7(1), 21–36.
Azar, E., & Menassa, C. C. (2012). A comprehensive analysis of the impact of occupancy parameters in energy simulation of office buildings. Energy and Buildings, 55, 841–853.
Azar, E., & Menassa, C. C. (2014). A comprehensive framework to qualify energy savings potential from improved operations of commercial building stocks. Energy Policy, 67, 459–472.
Azar, E., & Menassa, C. C. (2015). Optimizing the performance of energy-intensive commercial buildings: occupancy-focused data collection and analysis approach. Journal of Computing in Civil Engineering, 30(5), C4015002.
Backlund, S., & Eidenskog, M. (2013). Energy service collaborations-it is a question of trust. Energy Efficiency, 6(3), 511–521.
Ballarini, I., Corgnati, S. P., & Corrado, V. (2014). Use of reference buildings to assess the energy saving potential of the residential building stock: the experience of TABULA project. Energy Policy, 68, 273–284.
Barney, J., & Clark, D. N. (2007). Resource-based theory: creating and sustaining competitive advantage. Oxford: Oxford University Press.
Bertoldi, P., & Boza-Kiss, B. (2017). Analysis of barriers and drivers for the development of the ESCO markets in Europe. Energy Policy, 107, 345–355.
Bloomberg, N. E. F. (2019). Energy efficiency trends report 26, 4th quarter.
Broin, E. O., Mata, E., Goransson, E., & Johnsson, F. (2013). The effect of improved efficiency on energy savings in EU-27 buildings. Energy, 57, 134–148.
Cabinet Office. (2011). Behaviour change and energy use. London, UK: UK Government.
Capelo, C., Diaz, J. F., & Pereira, R. (2018). A system dynamics approach to analyse the impact of energy efficiency policy on ESCO ventures in European Union countries: a case study of Portugal. Energy Efficiency, 11, 893–925.
Caron, F., Fumagalli, M., & Rigamonti, A. (2007). Engineering and contracting projects: a value at risk based approach to portfolio balancing. International Journal of Project Management, 25, 569–578.
Carrico, A. R., & Riemer, M. (2011). Motivating energy conservation in the workplace: an evaluation of the use of group-level feedback and peer education. Journal of Environmental Psychology, 31, 1–13.
Chan, Y., & Kantamaneni, R. (2015). Study on energy efficiency and energy saving potential in industry and on possible policy mechanisms. Report prepared for European Commission Directorate-general energy. London, UK: ICF Consulting Ltd..
Colmenar-Santos, A., de Lober, L. N. T., Borge-Diez, D., & Castro-Gil, M. (2013). Solutions to reduce energy consumptionin the manatement of large buildings. Energy and Buildings, 56, 66–77.
Committee on Climate Change (2019). https://www.theccc.org.uk/our-impact/reducing-the-uks-emissions/ (Accessed 31 Dec 2019).
Committee on Climate Change (CCC). (2008). Building a low-carbon economy – The UK’s contribution to tackling climate change. London: The Stationery Office.
Dangerfield, B., Green, S., & Austin, S. (2010). Understanding construction competitiveness: the contribution of system dynamics. Construction Innovation, 10(4), 408–420.
Daouas, N. (2011). A study on optimum insulation thickness in walls and energy savings in Tunisian buildings based on analytical calculation of cooling and heating transmission loads. Applied Energy, 88, 156–164.
Davies, H. A., & Chan, E. K. (2001). Experience of energy performance contracting in Hong Kong. Facilities, 19(7/8), 261–268. https://doi.org/10.1108/02632770110390694.
Davies, M., & Oreszczyn, T. (2012). The unintended consequences of decarbonising the built environment: a UK case study. Energy and Buildings, 46, 80–85.
De Wilde, P. (2014). The gap between predicted and measured energy performance of buildings: a framework for investigation. Automation in Construction, 14, 40–49.
De Wilde, P., Tian, W., & Augenbroe, G. (2011). Longitudinal prediction of the operational energy use of buildings. Building and Environment, 46, 1670–1680.
Delmas, M. A., & Pekovic, S. (2015). Resource efficiency strategies and market conditions. Long Range Planning, 48, 80–94.
Delmastro, C., Mutani, G., & Corgnati, S. P. (2016). A supporting method for selecting cost-optimal energy retrofit policies for residential buildings at the urban scale. Energy Policy, 99, 42–56.
Deng, Q., Zhang, L., Cui, Q., & Jiang, X. (2014). A simulation-based decision model for designing contract period in building energy performance contracting. Building and Environment, 71, 71–80.
Dineen, D., Rogan, F., & Gallachoir, B. P. (2015). Improved modelling of thermal energy savings potential in the existing residential stock using a newly available data source. Energy, 90, 759–767.
Dyner, I., Smith, R. A., & Pena, G. E. (1995). System dynamics modelling for residential energy efficiency analysis and management. Journal of the Operational Research Society, 46(10), 1163–1173.
Eleftheriadis, G., & Hamdy, M. (2017). Impact of building envelope and mechanical component degradation on the whole building performance: a review paper. Energy Procedia, 132, 321–326.
Elias, A. A. (2008). Energy efficiency in New Zealand’s residential sector: a systemic analysis. Energy Policy, 36, 3278–3285.
Escrivá-Escrivá, G., Segura-Heras, I., & Alcázar-Ortega, M. (2010). Application of an energy management and control system to assess the potential of different control strategies in HVAC systems. Energy and Buildings, 42, 2258–2267.
Espinoza, R. D. (2014). Separating project risk from the time value of money: a step toward integration of risk management and valuation of infrastructure investments. International Journal of Project Management, 32(6), 1056–1072.
Espinoza, R. D., & Morris, J. W. F. (2013). Decoupled NPV: a simple, improved method to value infrastructure investments. Journal of Construction Management and Economics, 31, 471–496.
Espinoza, R. D., & Rojo, J. (2015). Using DNPV for valuing investments in the energy sector: a solar project case study. Renewable Energy, 75, 44–49.
EU Directive (2012). Directive 2012/27/EU of the European Parliament and of the Council. Official Journal of the European Union L 315/1.
EU Directive 844 2018. Amending Directive 2010/31/EU on the energy performance of buildings and Directive 2012/27/EU on energy efficiency. Official Journal of the European Union L156/75.
European Commission, (2018). Buildings. https://ec.europa.eu/energy/en/topics/energy-efficiency/buildings (accessed 14 Sept 2018).
Fennell, P., Ruyssevelt, P., & Smith, A. Z. P. (2016). Financial viability of school retrofit projects for clients and ESCOs. Building Research and Information, 44(8), 889–906.
Gliedt, T., Hoicka, C. E., & Jackson, N. (2018). Innovation intermediaries accelerating environmental sustainability transitions. Journal of Cleaner Production, 174, 1247–1261.
Goldman, C. A., Hopper, N. C., & Osborn, J. G. (2005). Review of US ESCO industry market trends: an empirical analysis of project data. Energy Policy, 33(3), 387–405.
Granderson, J., Piette, M. A., & Ghatikar, G. (2011). Building energy information systems: user case studies. Energy Efficiency, 4(1), 17–30.
Henze, G. P. (2001). Building energy management as continuous quality. Journal of Architectural Engineering, 7, 97–106.
Heo, Y., Augenbroe, G., Choudhary, R. (2011). Risk analysis of energy-efficiency projects based on Bayesian calibration of building energy models. Proceedings of 12th conference of international building performance simulation association, Sydney, 14–16 November. http://ibpsa.org/proceedings/BS2011/P_1799.pdf.
Hoes, P., Hensen, J. L. M., Loomans, M. G. L. C., de Vries, B., & Bourgeois, D. (2009). User behavior in whole building simulation. Energy and Buildinds, 41(3), 295–302.
Holck-Sandberg, N., Sartori, I., Heindrich, O., Dawson, R., Dascalaki, E., Dimitriou, S., Vimmr, T., Filippidou, F., Stegnar, G., Sijanec-Zavrl, M., & Bratebo, H. (2016). Dynamic building stock modelling: application to 11 European countries to support the energy efficiency and retrofit ambitions of the EU. Energy and Buildings, 132(15), 26–38.
Holtz, G., Alkemade, F., de Haan, F., Köhler, J., Trutnevyte, E., Luthe, T., et al. (2015) Prospects of transition modelling: Position paper of the transition modelling community. Environmental Innovation and Societal Transitions 17, 41–58.
International Energy Agency (IEA) (2018). Energy efficiency report: analysis and outlooks to 2040.
IPCC (2014). Core Writing Team. In R. K. Pachauri & L. A. Meyer (Eds.), Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Geneva: IPCC.
IPCC (2018). Global warming of 1.5C: summary for policymakers. https://www.ipcc.ch (Accessed 31 Dec 2018).
Jackson, J. (2010). Promoting energy efficiency investments with risk management decision tools. Energy Policy, 38(8), 3865–3873.
Jennings, A. M., Hirst, N., & Gambhir, A. (2011). Reduction of carbon dioxide emissions in the global building sector to 2050. Grantham Institute for Climate Change: London, UK.
Karlsen, R., Papachristos, G., & Rehmatulla, N. (2019). An agent-based model of climate-energy policies to promote wind propulsion technology in shipping. Environmental Innovation and Societal Transitions, 31, 33–53.
Kavgic, M., Mavrogianni, A., Mumovic, D., Summerfield, A., Stevanovic, Z., & Djurovic-Petrovic, M. (2010). A review of bottom-up building stock models for energy consumption in the residential sector. Building and Environment, 45, 1683–1697.
Kivimaa, P., Boon, W., Hyysalo, S., & Klerkx, L. (2019). Towards a typology of intermediaries in sustainability transitions: a systematic review and a research agenda. Research Policy, 48(4), 1062–1075.
Klepeis, N. E., Nelson, W. C., Ott, W. R., Robinson, J. P., Tsang, A. M., Switzer, P., Behar, J. V., Hern, S. C., & Engelmann, W. H. (2001). The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. Journal of Exposure Science & Environmental Epidemiology, 11, 231–252.
Knoop, K., & Lechtenböhmer, S. (2017). The potential for energy efficiency in the EU Member States - a comparison of studies. Renewable and Sustainable Energy Reviews, 68, 1097–1105.
Köhler, J., de Haan, F., Holtz, G., Kubeczko, K., Moallemi, E.A., Papachristos, G., et al. (2018) Modelling sustainability transitions: An assessment of approaches and challenges. Journal of Artificial Societies and Social Simulation 21(1), 8.
Lant, T., & Shapira, Z. (2008). Managerial reasoning about aspirations and expectations. Journal of Economics Behavior & Organization, 66, 60–73.
Larsen, P. H., Goldman, C. A., & Satchwell, A. (2012). Evolution of the U.S. energy service company industry: market size and project performance from 1990-2008. Energy Policy, 50, 802–820.
Lee, P., Lam, P. T. I., & Lee, W. I. (2015). Risks in energy performance contracting EPC projects. Energy and Buildings, 92, 116–127.
Levine, M., Urge-Vorsatz, D., 2007. Residential and commercial buildings. In: Climate change 2007: mitigation. Cambridge University Press, Cambridge.
Lopes, M. A. R., Antunes, C. H., & Martins, N. (2012). Energy behaviours as promoters of energy efficiency: a 21st century review. Renewable Sustainable Energy Reviews, 16(6), 4095–4104.
Ma, Z., Cooper, O., Daly, D., & Ledo, L. (2012). Existing building retrofits: methodology and state of the art. Energy and Buildings, 55, 889–902.
Marino, A., Bertoldi, P., Rezessy, S., & Boza-Kiss, B. (2011). A snapshot of the European market in 2010 and policy recommendations to foster a further market development. Energy Policy, 39, 6190–6198.
Masoso, O. T., & Grobler, L. J. (2010). The dark side of occupants’ behaviour on building energy use. Energy and Buildings, 42(2), 173–177.
Mata, E., Kalagasidis, S. A., & Johnsson, F. (2013). Energy usage and technical potential for energy saving measures in the Swedish residential building stock. Energy Policy, 55, 404–414.
Mata, E., Kalagasidis, S. A., & Johnsson, F. (2014). Building-stock aggregation through archetype buildings: France, Germany, Spain and the UK. Building and Environment, 81, 270–282.
Mata, E., Kalagasidis, A. S., & Johnsson, F. (2018). Contributions of building retrofitting in five member states to EU targets for energy savings. Renewable and Sustainable Energy Reviews, 93(2018), 759–774.
McKenna, R., Merkel, E., Fehrenbach, D., Mehne, S., & Fichtner, W. (2013). Energy efficiency in the German residential sector: a bottom-up building-stock-model-based analysis in the context of energy-political targets. Building and Environment, 62, 77–88.
Menassa, C. C. (2011). Evaluating sustainable retrofits in existing buildings under uncertainty. Energy and Buildings, 43, 3576–3583.
Menassa, C. C., & Mora, F. P. (2007). An option pricing model to evaluate ADR investments in AEC projects. Journal of Construction Engineering and Management, 135(3), 156–168.
Mills, E., Kromer, S., Weiss, G., & Mathew, P. A. (2006). From volatility to value: analysing and managing financial and performance risk in energy savings projects. Energy Policy, 34(2), 188–199.
Moezzi, M. (2009). Are Comfort Expectations of Building Occupants Too High? Building Research and Information, 37(1), 79–83.
Motawa, I., & Oladokun, M. (2015). A model for the complexity of household energy consumption. Energy and Buildings, 87, 313–323.
Neto, A. H., & Fiorelli, F. A. S. (2008). Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption. Energy and Buildings, 40, 2169–2176.
Nolden, C., & Sorrell, S. (2016). The UK market for energy service contracts in 2014-2015. Energy Efficiency, 9, 1405–1420.
Nolden, C., Sorrell, S., & Polzin, F. (2016). Catalysing the energy service market: the role of intermediaries. Energy Policy, 98, 420–430.
Oldewurtel, F., Parisio, A., Jones, C. N., Gyalistras, D., Gwerder, M., Stauch, V., Lehmann, B., & Morari, M. (2012). Use of model predictive control and weather forecasts for energy efficient building climate control. Energy and Buildings., 45, 15–27.
Olsthoorn, M., Schleich, J., & Hirzel, S. (2017). Adoption of energy efficiency measures for non-residential buildings: technological and organizational heterogeneity in the trade, commerce and services sector. Ecological Economics, 136, 240–254.
Oreszczyn, T., & Lowe, R. (2010). Challenges for energy and buildings research: objectives, methods and funding mechanisms. Building Research & Information, 38(1), 107–122.
Österbring, M., Mata, E., Thuvander, L., Mangold, M., Johnsson, F., & Wallbaum, H. (2016). A differentiated description of building-stocks for a georeferenced urban bottom-up building-stock model. Energy and Buildings, 120, 78–84.
Papachristos, G. (2011). A system dynamics model of socio-technical regime transitions. Environmental Innovation and Societal Transitions, 1(2), 202–233.
Papachristos G. (2012). Case study and system dynamics research: complementarities, pluralism and evolutionary theory development. 30th International conference of the System Dynamics Society, St Gallen, Switzerland online proceedings.
Papachristos, G. (2014). Towards multi-system sociotechnical transitions: why simulate. Technology Analysis and Strategic Management, 26(9), 1037–1055.
Papachristos, G. (2015). Household electricity consumption and CO2 emissions in the Netherlands: a model-based analysis. Energy and Buildings, 86, 403–414.
Papachristos, G. (2018a). The low carbon transition in the UK building sector must make financial sense: a hybrid system dynamics and bottom up modelling framework. In Proceedings of the 36th international system dynamics conference, 6th-10th August, Reykjavik, Iceland.
Papachristos, G. (2018b). A mechanism based transition research methodology: bridging analytical approaches. Futures, 98, 57–71. https://doi.org/10.1016/j.futures.2018.02.006.
Papachristos, G. (2019). System dynamics modelling and simulation for sustainability transition research. Environmental Innovation and Societal Transitions, 31, 248–261. https://doi.org/10.1016/j.eist.2018.10.001.
Papachristos, G. (2020). Platform competition: a review and research outline for modelling and simulation research. Journal of Engineering and Technology Management, 56, 101567.
Papachristos, G., & Struben, J. (2019). System dynamics methodology and research: opportunities for transitions research. In E. A. Moallemi & F. J. de Haan (Eds.), Modelling transitions: virtues, vices, visions of the future (pp. 119–138). Routledge: Taylor & Francis Group.
Papachristos, G., & Van de Kaa, G. (2018). Understanding platform competition through simulation: a research outline. Technology Analysis and Strategic Management, 30(12), 1409–1421.
Papachristos, G., Jain, J., Burman, E., Zimmerman, N., Mumovic, D., Davies, M. (2018a). Towards the low carbon transition in the construction industry: a multi-method framework of project management operations and total building performance. In Proceedings of the 36th international system dynamics conference, 6th-10th August, Reykjavik, Iceland.
Papachristos, G., Jain, J., Burman, E., Zimmerman, N., Mumovic, D., Davies, M. (2018b). Project management operations and building performance in the construction industry: a multi method approach applied in a UK public office building. In Proceedings of the 36th international system dynamics conference, 6th-10th August, Reykjavik, Iceland.
Papachristos, G., Jain, J., Burman, E., Zimmerman, N., Mumovic, D., & Davies, M. (2020a). Low carbon building performance: a multi-method approach of project management operations and building energy use applied in a UK public office building. Energy and Buildings, 206, 109609. https://doi.org/10.1016/j.enbuild.2019.109609.
Papachristos, G., Jain, J., Burman, E., Zimmerman, N., Mumovic, D., & Davies, M. (2020b). Low carbon building performance in the construction industry: a multi-method approach of system dynamics and building performance modelling. Construction Management and Economics. https://doi.org/10.1080/01446193.2020.1748212.
Peng, C., Yan, D., Wu, R., Wang, C., Zhou, X., & Jiang, Y. (2012). Quantitative description and simulation of human behavior in residential buildings. Building Simulation, 5, 85–94.
Ramesh, T., Prakash, R., & Shukla, K. K. (2010). Life cycle energy analysis of buildings: an overview. Energy and Buildings, 42(10), 1592–1600.
Remer, D. S., & Nieto, A. P. (1995). A compendium and comparison of 25 project evaluation techniques. Part 1: net present value and rate of return methods. International Journal of Production Economics, 42, 79–96.
Rogers, E., (2003). The diffusion of innovations, 5th edition, Free Press.
Rosenow, J., Cowart, R., Bayer, E., & Fabbri, M. (2017). Assessing the European Union’s energy efficiency policy: will the winter package deliver on ‘Efficiency First’? Energy Research & Social Science, 26, 72–79.
Rysanek, A., & Choudhary, R. (2013). Optimum building energy retrofits under technical and economic uncertainty. Energy Buildings, 57, 324–337.
Sanchez, M., Webber, C., Brown, R., Busch, J., Pinckard, M., Roberson, J., (2007). Space heaters, computers, cell phone chargers: how plugged in are commercial buildings? In: 2006 ACEEE summer study on energy efficiency in buildings, less is more, en route to zero energy buildings, Berkeley, CA.
Shrubsole, C., Hamilton, I. G., Zimmermann, N., Papachristos, G., Broyd, T., Burman, E., Mumovic, D., Zhu, Y., Lin, B., & Davies, M. (2019). Bridging the gap: the need for a system thinking approach in understanding and addressing energy and environmental performance in buildings. Indoor Building Environment, 28(1), 100–117.
Sorrell, S., (2005). The contribution of energy service contracting to a low carbon economy. Tyndall Centre for Climate Change Research http://www.tyndall.ac.uk/sites/default/files/t3_21.pdf.
Sorrell, S. (2007). The economics of energy service contracts. Energy Policy, 35, 507–521.
Staats, H., Van Leeuwen, E., & Wit, A. (2000). A longitudinal study of informational interventions to save energy in an office building. Journal of Applied Behavior Analysis, 33(1), 101–104.
Sterman, J. D. (1987). Expectation formation in behavioral simulation models. Behavioral Science, 32, 190–211.
Sterman, J. D. (2000). Business dynamics: systems thinking and modelling for a complex world. New York: McGraw Hill.
Stuart, E., Carvallo, J. P., Larsen, P. H., Goldman, C. A., & Gilligan, D. (2018). Understanding recent market trends of the US ESCO industry. Energy Efficiency, 11, 1303–1324.
Sudong, Y., & Tiong, R. L. K. (2000). NPV-at-risk method in infrastructure project investment evaluation. Journal of Construction Engineering and Management, 126(3), 227–223.
Summerfield, A. J., & Lowe, R. (2012). Challenges and future directions for energy and buildings research. Building Research Information, 40, 391–400.
Swan, L. G., & Ugursal, V. I. (2009). Modeling of end-use energy consumption in the residential sector: a review of modeling techniques. Renewable and Sustainable Energy Reviews, 13, 1819–1835.
Thomas, A., Menassa, C. C., & Kamar, V. R. (2016). System dynamics framework to study the effect of material performance on a building’s lifecycle energy requirements. Journal of Computing in Civil Engineering, 30(6), 1–15.
Tuominen, P., Holopainen, R., Eskoila, L., Jokisall, J., & Airaksinen, M. (2014). Calculation method and tool for assessing energy consumption in the building stock. Building and Environment, 75, 153–160.
Ucci, M., Domenech, T., Ball, A., Whitley, T., Wright, C., Mason, D., Corrin, K., Milligan, A., Rogers, A., Fitzsimons, D., Gaggero, C., & Westaway, A. (2014). Behaviour change potential for energy saving in non-domestic buildings: development and pilot-testing of a benchmarking tool. Building Services Engineering Research Technologies, 36(1), 1–17.
Urge-Vorsatz, D., Novikova, A., Köppel, S., & Boza-Kiss, B. (2009). Bottom–up assessment of potentials and costs of CO2 emission mitigation in the buildings sector: insights into the missing elements. Energy Efficiency, 2, 293–316.
US Environmental Protection Agency (EPA). (2010). ENERGY STAR s and other climate protection partnerships—2010 annual report. Washington, DC: EPA.
Vásquez, F., Løvik, A. N., Holck Sandberg, N., & Müller, D. B. (2016). Dynamic type-cohort-time approach for the analysis of energy reductions strategies in the building stock. Energy and Buildings, 111, 37–55.
Webber, C. A., Roberson, J. A., McWhinney, M. C., Brown, R. E., Pinckard, M. J., & Busch, J. F. (2006). After-hours power status of office equipment in the USA. Energy, 31, 2823–2838.
Whitty, J.L., Colville, O. (2013). Building efficiency: reducing energy demand in the commercial sector. A report by the Westminster Sustainable Business Forum and Carbon Connect.
Wu, X., Borong, L., Papachristos, G., Liu, P., & Zimmermann, N. (2020). A holistic approach to evaluate building performance gap of green office buildings: a case study in China. Building and Environment, 106819.
Yoon, J., Lee, E. J., & Claridge, D. E. (2003). Calibration procedure for energy performance simulation of a commercial building. Journal of Solar Energy Engineering, 125(3), 251–257.
Zervos, A., Lins, C., Muth, J. (2010). Rethinking 2050: a 100% renewable energy vision for the European Union. European Renewable Energy Council.
Funding
The authors gratefully acknowledge the financial support from ‘The ‘Total Performance’ of Low Carbon Buildings in China and the UK’ (‘TOP’) project funded by the UK EPSRC (grant code: EP/N009703/1). The corresponding research carried out in China is funded by NSFC China (51561135001).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author declares that he has no conflict of interest.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Papachristos, G. A modelling framework for the diffusion of low carbon energy performance contracts. Energy Efficiency 13, 767–788 (2020). https://doi.org/10.1007/s12053-020-09866-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12053-020-09866-4