Abstract
This chapter introduces an innovative approach that combines the deductive method used to construct normative energy-economy models and the inductive method of social sciences. Consumer behavior is described via technological attributes and used in virtual process technologies in an energy optimization framework. The main finding is that it is possible to evaluate consumer information and behavior together with technological progress and integrate them on the same modeling platform. The approach eliminates the systematic error on the demand side where the efficiency of demand-side management measures is over optimistic, which may lead to inaccurate decisions and poor policies. Thus, this method paves the way to a new stream in energy modeling.
Research supported by SNF research grant IZERZ0_142217.
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Bhattacharyya SC, Timilsina GR (2010) A review of energy system models. Int J Energy Sect Manage 4(4):494–518
Bottrill C (2007) Internet-based carbon tools for behaviour change. Oxford University Centre for the Environment, Oxford
Fragnière E (1995) Choix énergétiques et environnementaux pour le canton de Genève. thèse de doctorat, SES 412, Université de Genève
Fragnière E, Haurie A (1996) A stochastic programming model for energy/environment choices under uncertainty. Int J Environ Pollut 6(4–6):587–603
Fragnière E, Haurie A, Kanala R (1999) A GIS-based regional energy-environment policy mode. Int J Glob Energy Issues 12(1–6):159–167
Fragnière E, Kanala R, Lavigne D, Moresino F, Nguene G (2010) Behavioral and technological changes regarding lighting consumptions: A MARKAL case study. Low Carbon Econ 1(1):8–17
Gyberg P, Palm J (2009) Influencing households’ energy behaviour – how is this done and on what premises? Energy Policy 37(7):2807–2813
Hondo H, Baba K (2010) Socio-psychological impacts of the introduction of energy technologies: change in environmental behavior of households with photovoltaic systems. Appl Energy 87(1):229–235
Loulou R, Lavigne D (1996) MARKAL model with elastic demands: application to GHG emission control. In: Carraro C, Haurie A (eds) Operations research and environmental engineering. Kluwer Academic Publishers, Dordrecht/Boston/London, pp 201–220
Manne AS, Wene CO (1992) MARKAL-MACRO: a linked model for energy-economy analysis, Brookhaven National Laboratory, BNL-47161, Brookhaven National Laboratory, Upton
Nakata T (2004) Energy-economic models and the environment. Prog Energy Combust Sci 30(4). Retrieved from http://linkinghub.elsevier.com/retrieve/pii/S0360128504000140
Nguene G, Fragnière E, Kanala R, Lavigne D, Moresino F (2011) Socio-markal (Somarkal): first modeling attempts in the Nyon residential and commercial sectors taking into account behavioural uncertainties. Energy Sustain Dev 15(1):73–83
Nye M, Burgess J (2008) Promoting durable change in household waste and energy use behaviour. Retrieved from http://globalactionplanorguk.site.securepod.com/upload/resource/UEA%20EcoTeams%20Research%20Report%20Feb%202008.pdf
Ouyang J, Hokao K (2009) Energy-saving potential by improving occupants’ behavior in urban residential sector in Hangzhou City, China. Energy Build 41(7):711–720
Räthzel N, Uzzell D (2009) Changing relations in global environmental change. Global Environ. doi:10.1016/j.gloenvcha.2009.05.001
Rice RE, Paisley WJ (1981) Campaigns to affect energy behaviour. Public communication campaigns. Sage, Beverly Hills
Rydin Y, Moore S, Nye M (2007) Using ecological footprints as a policy driver: the case of sustainable construction planning policy in London. Local Environ 12(1):1–15
Turton H, Barreto L (2006) Long-term security of energy supply and climate change. Energy Policy 34:2232–2250
UNEP (2008) SBCI buildings and climate change report. Division of Technology, Industry, and Economics, Paris. Retrieved from www.unep.org/Documents.Multilingual/Default.Print.asp?DocumentID=502&ArticleID=5545&l=en
Weber S, Baranzini A, Fragnière E (2009) Consumers’ choices among alternative electricity programs in Geneva: an empirical analysis. Int J Global Energy Issues 31(3/4):295–309
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Kanala, R., Turin, N., Fragnière, E. (2013). An Energy Optimization Framework for Sustainability Analysis: Inclusion of Behavioral Parameters as a Virtual Technology in Energy Optimization Models. In: Luo, Z. (eds) Mechanism Design for Sustainability. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5995-4_6
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