Comptes Rendus
Demain l'énergie – Séminaire Daniel-Dautreppe, Grenoble, France, 2016
“Smart buildings” integrated in “smart grids”: A key challenge for the energy transition by using physical models and optimization with a “human-in-the-loop” approach
Comptes Rendus. Physique, Demain l’énergie, Volume 18 (2017) no. 7-8, pp. 428-444.

The big challenge for the 21th century is to decrease fossil energy use and to increase renewable energies in the framework of the climate constraint. The paper will show that smart buildings, connected to smart grids, can significantly contribute to this objective. Indeed, buildings are, on one side, the biggest consumers of energy in the electrical grid and could be among the greatest producers of renewable energy, especially thanks to the concept of energy positive buildings, and this by offering at the same time high flexibility in energy demand. That is why the paper focuses on methodologies using physical models and optimization for smart design and smart supervision for valorizing those buildings energy properties and contribute thus to the emergence of the concept of smart buildings (SBs) integrated in smart grids (SGs): we will give an overview of the mathematical optimization method used and of the kind of physical models we have developed over 10 years of active research in order to propose by this way a smart software dedicated to those SBs integrated in SGs. We explain also our global research strategy for improving this smart software, by a so-called “human-in-the-loop” approach, in which we consider that they there will be no “smart building” without “smart users”. This means a complex multi-disciplinary research that we develop in a “living lab”, in which the inhabitants are involved as “pro'sumers”, i.e. as active and implicated designers and users.

L'enjeu du XXIe siècle est de faire décroître la consommation des énergies fossiles au profit des énergies renouvelables sous la pression climatique. Ce papier montre que les bâtiments intelligents (smart buildings), intégrés dans des réseaux intelligents (smart grids), peuvent significativement contribuer à cet objectif. En effet, les bâtiments sont, d'une part, les plus grands consommateurs d'énergie dans le réseau électrique et pourraient devenir l'un des plus grands producteurs d'énergie renouvelable, en particulier grâce au concept de bâtiment à énergie positive, et ceci en offrant dans le même temps un important gisement de « flexibilité » en demande énergétique. C'est pourquoi cet article se focalise sur des méthodologies utilisant des modèles physiques et l'optimisation pour une conception et une supervision « intelligentes », afin de valoriser les propriétés énergétiques de ces bâtiments et contribuer ainsi au concept de smart building intégré dans des smart grids : nous donnerons un aperçu des méthodes mathématiques d'optimisation utilisées et des types de modèles physiques que nous avons développés au cours d'une recherche qui s'est déroulée sur plus de dix ans, de manière à proposer ainsi des approches logicielles dédiées à ces smart buildings intégrés à des smart grids. Nous détaillerons aussi notre stratégie globale de recherche pour améliorer ce type de logiciel « intelligent », par une approche dite « humain dans la boucle » (human in the loop), dans laquelle nous considérons qu'il n'y aura pas de « bâtiments intelligents » sans « utilisateurs intelligents ». Ceci implique une recherche interdisciplinaire complexe, que nous développons dans un living lab dans lequel les usagers sont impliqués comme consom'acteurs (pro'sumers), c'est-à-dire comme concepteurs et usagers actifs.

Published online:
DOI: 10.1016/j.crhy.2017.09.007
Keywords: Smart building, Smart grid, Optimization for smart buildings, Physical models for smart buildings, “Living lab”, “Pro'sumer”, ADEME, ESP, ESOT, HVAC, MILP, PV, IOT, SB, SG, SQP, STEP, V2H
Mots-clés : Bâtiment intelligent, Réseau intelligent, Optimisation pour bâtiment intelligent, Modèles physiques pour bâtiments intelligents, « Living lab », « Consom'acteurs »

Frédéric Wurtz 1; Benoît Delinchant 1

1 Université Grenoble Alpes, CNRS, Grenoble INP, G2Elab, 38000 Grenoble, France
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Frédéric Wurtz; Benoît Delinchant. “Smart buildings” integrated in “smart grids”: A key challenge for the energy transition by using physical models and optimization with a “human-in-the-loop” approach. Comptes Rendus. Physique, Demain l’énergie, Volume 18 (2017) no. 7-8, pp. 428-444. doi : 10.1016/j.crhy.2017.09.007. https://comptes-rendus.academie-sciences.fr/physique/articles/10.1016/j.crhy.2017.09.007/

[1] M.L. Tuballa; M.L. Abundo A review of the development of smart grid technologies, Renew. Sustain. Energy Rev., Volume 59 (2016), pp. 710-725 http://www.sciencedirect.com/science/article/pii/S1364032116000393 | DOI

[2] C. Benoît, Models for investigation of flexibility benefits in unbalanced low volt age smart grids. Electric power, PhD thesis, Université Grenoble Alpes, 2015. English. <NNT:2015GREAT056>. <tel-01223369>, https://tel.archives-ouvertes.fr/tel-01223369/.

[3] Y.H. Said Prise en compte de la complexité de modélisation dans la gestion énergétique des bâtiments, Université Grenoble Alpes, 20 July 2016 (PhD thesis)

[4] Chiffres cles climat air énergie 2014, 2014 http://www.ademe.fr/chiffres-cles-climat-air-energie-2014 http://www.ademe.fr/sites/default/files/assets/documents/ademe-climat-energie-web.pdf (rapport ADEME and 2015:)

[5] “Bilan énergétique de la France pour 2014”, observations and statistics from the French government, but the data exist up to 2016 http://www.statistiques.developpement-durable.gouv.fr/donnees-densemble/1925/2019/ensemble-bilans-lenergie-france.html

[6] Vers un mix électrique 100% renouvelable en 2050 http://www.ademe.fr/mix-electrique-100-renouvelable-analyses-optimisations (Rapport ADEME, France)

[7] A. Dargahi Gestion des flux multi-énergie pour les systèmes V2H, Université de Grenoble, France, 2017 https://tel.archives-ouvertes.fr/tel-01111994 (PhD thesis)

[8] A. Dargahi; S. Ploix; A. Soroudi; F. Wurtz Optimal household energy management using V2H flexibilities, Compel, Volume 33 (2014) no. 3, pp. 777-792 http://www.emeraldinsight.com/doi/full/10.1108/COMPEL-10-2012-0223 (see) | DOI

[9] CRE (Commission de régulation de l'énergie), Étude des avantages que l'effacement procure à la collectivité et de leur intégration dans un dispositif de prime, 2013. [Online]. Available: http://www.cre.fr/documents/publications/etudes/etude-sur-la-valeur-des-flexibilites-pour-la-gestion-et-le-dimensionnement-des-reseaux-de-distribution, (Accessed 22 March 2017).

[10] RTE Valorisation socio-économique des réseaux électriques intelligents – Synthèse, RTE France, 24 July 2015 http://www.rte-france.com/fr/document/valorisation-socio-economique-des-reseaux-electriques-intelligents-synthese ([Online]. Available:, Accessed 2017-3-22)

[11] M.-N. Battistel; Y. Jégo; F. Barbier; D. Baupin Rapport d'information sur les enjeux et impacts de l'effacement électrique diffus n° 3690 [9] http://www.assemblee-nationale.fr/14/rap-info/i3690.asp ([Online]. Available:, Accessed 2017-3-22)

[12] Systèmes électriques intelligents: premiers résultats des démonstrateurs http://www.ademe.fr/systemes-electriques-intelligents-premiers-resultats-demonstrateurs (ADEME, France [Online]. Available:, Accessed 2017-3-21)

[13] C. Clastres; T.T. Ha Pham; F. Wurtz; S. Bacha Ancillary services and optimal household energy management with photovoltaic production, Energy, Volume 35 (2010) no. 1, pp. 55-64 | DOI

[14] T.T. Ha Pham; C. Clastres; F. Wurtz; S. Bacha; E. Zamai Optimal household energy management and economic analysis: from sizing to operation scheduling, Adv. Appl. Mech. Eng. Technol., Volume 1 (2010) no. 1, pp. 35-68 https://halshs.archives-ouvertes.fr/halshs-00323581 (publié dans)

[15] D. Tenfen; E.C. Finardi; B. Delinchant; F. Wurtz Lithium-ion battery modelling for the energy management problem of microgrids, IET Gener. Transm. Distrib., Volume 10 ( 18 February 2016 ) no. 3, pp. 576-584 (Print ISSN 1751-8687, Online ISSN 1751-8695) | DOI

[16] D. Tenfen; B. Delinchant; F. Wurtz; E.C. Finardi; J. Rolim; R.C. Fernandes Load demand, batteries, and electric vehicles modelling to the energy management of microgrids, Magdebourg, Allemagne, 28–29 octobre (2014) http://www.elecon.ipp.pt/images/Workshop2/Papers/Load_Demand_Batteries_and_Electric_Vehicles_Modelling_to_the_Energy_Management_of_Microgrids.pdf

[17] Van Binh Dinh; B. Delinchant; F. Wurtz The importance of derivatives for simultaneous optimization of sizing and operation strategies: application to buildings and Hvac systems, BSO 2016, Great North Museum, Newcastle, 12–14 September (2016) http://www.ibpsa.org/proceedings/BSO2016/p1043.pdf

[18] V.-B. Dinh; B. Delinchant; F. Wurtz Optimal sizing of a complex energy system integrating management strategies for a grid-connected building, Hyderabad, India, 7–9 December (2015) http://www.ibpsa.org/proceedings/BS2015/p2141.pdf

[19] F. Wurtz; J. Pouget; X. Brunotte; M. Gaulier; Y. Rifonneau; S. Ploix; B. L'Hénoret Sketch systemic optimal design integrating management strategy, thermal insulation, production and storage energy systems (thermal and electrical): application to an energy-positive train station, Chambéry, France, August (2013) http://www.ibpsa.org/proceedings/BS2013/p_2376.pdf

[20] V.-B. Dinh; B. Delinchant; F. Wurtz On the sizing of building envelope and energy system integrating management strategy in sketch phase, Hyderabad, India, 7–9 December (2015) http://www.ibpsa.org/proceedings/BS2015/p2142.pdf

[21] H.-A. Dang; B. Delinchant; F. Wurtz Toward autonomous photovoltaic building energy management: modeling and control of electrochemical batteries, Chambéry, France, August (2013) http://www.ibpsa.org/proceedings/BS2013/p_2095.pdf

[22] W. Visser Dynamic Aspects of Design Cognition: Elements for a Cognitive Model of Design, March 2004 (INRIA, Rapport de recherche No. 5144 116 p)

[23] K. Deb; A. Pratap; S. Agarwal; T. Meyarivan A fast elitist multi-optimal objective genetic algorithm: NSGA-II, IEEE Trans. Evol. Comput., Volume 6 (2002) no. 2, pp. 182-197

[24] R. Evins A review of computational optimisation methods applied to sustainable building design, Renew. Sustain. Energy Rev., Volume 22 (2013), pp. 230-245

[25] K. Gram-Hanssen Households' energy use – which is the more important: efficient technologies or user practices?, WREC 2011, Linköping, Sweden (2011)

[26] O.G. Santin; L. Itard; H. Visscher The effect of occupancy and building characteristics on energy use for space and water heating in Dutch residential stock, Energy Build., Volume 41 (2009), pp. 1223-1232

[27] K. Steemers; G.Y. Yun Household energy consumption: a study of the role of occupants, Build. Res. Inf., Volume 37 (2009) no. 5, pp. 625-637

[28] M. Vellei; S. Natarajan; B. Biri; J. Padget; I. Walker The effect of real-time context-aware feedback on occupants' heating behaviour and thermal adaptation, Energy Build., Volume 123 (2016), pp. 179-191 | DOI

[29] Z.M. Gill; M.J. Tierney; I.M. Pegg; N. Allan Measured energy and water performance of an aspiring low energy/carbon affordable housing site in the UK, Energy Build., Volume 43 (2011), pp. 117-125

[30] M.-C. Zélem; C. Besla; R. Gournet Mutation écologique et transition énergétique. Vers la ville intelligente ?, Urbia, Volume 15 (2013), pp. 45-60

[31] M.-C. Zélem; C. Besla; R. Gournet, Les Cahiers du Développement Urbain Durable (2013), pp. 45-59

[32] S. Gyamfi; S. Krumdieck Price, environment and security: exploring multi-modal motivation in voluntary residential peak demand response, Energy Policy, Volume 39 (2011), pp. 2993-3004 | DOI

[33] J. Rifkin La nouvelle société du coût marginal zéro, Éditions Les liens qui Libèrent, 2014 https://en.wikipedia.org/wiki/The_Third_Industrial_Revolution_(book) (see also) (ISBN: 979-10-209-0175-0)

[34] G. Debizet (2016), p. 200 (La Documentation française 978-2-11-010025-2)

[35] M. Trčka; J.L.M. Hensen Overview of HVAC system simulation, Autom. Constr., Volume 19 (2010) no. 2, pp. 93-99 http://www.sciencedirect.com/science/article/pii/S0926580509001897 | DOI

[36] Q. Nguyen-Hong; A. Le Mounier; V.-B. Dinh; B. Delinchant; S. Ploix; F. Wurtz Meta-optimization and scattering parameters analysis for improving on site building model identification for optimal operation, IBPSA 2017, San Fancisco, 7–9 August (2017)

[37] K. Buchanan; R. Russo; B. Anderson The question of energy reduction the problem(s) with feedback, Energy Policy, Volume 77 (2015) no. 0, pp. 89-96 | DOI

[38] H. Chenailler; F. Wurtz; S. Ploix From technical to usage energy efficiency in buildings: application to a heated room, IBPSA 2012, 14–16 November 2012, Sydney, Australia (2011) http://www.ibpsa.org/proceedings/BS2011/P_1595.pdf

[39] A. Faruqui; S. Sergici Household response to dynamic pricing of electricity: a survey of 15 experiments, J. Regul. Econ., Volume 38 (2010) no. 2, pp. 193-225

[40] B. Delinchant; F. Wurtz; S. Ploix; J.-L. Schanen; Y. Maréchal GreEn-ER living lab – a green building with energy aware occupants, Rome, Italy, 23–25 April (2016), pp. 316-323 (ISBN: 978-989-758-184-7) | HAL

[41] B. Delinchant; F. Wurtz The Grenoble PREDIS – building platform: a living lab and experimental lab for the study of energy and comfort in smart-buildings http://www.elecon.ipp.pt/images/Workshop3/Presentations/Elecon3.pdf (in: Third ELECON Workshop)

[42] J. Cheng; D. Qi; L. (Leon) Wang; A. Athienitis Whole-building simulation of hybrid ventilation based on full-scale measurements in an institutional high-rise building for predictive control, IBPSA 2017, San Francisco, CA, USA, Aug. 7–9 (2017)

[43] I. Bianchi; A. Faria Neto; B. Delinchant; F. Wurtz; S. Alabrach Energy saving using ceiling fans in environmental comfort systems, Grenoble, France, 17–18 November (2015) http://www.elecon.ipp.pt/images/Workshop3/Presentations/Elecon9.pdf

[44] H.-A. Dang; S. Gaaloul; B. Delinchant; F. Wurtz Building simulation of energy consumption and ambient temperature: application to the predis platform, Chambéry, France, August (2013) http://www.ibpsa.org/proceedings/BS2013/p_2096.pdf

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