Abstract
Energy management in buildings is addressed in this paper. The energetic impact of buildings in the current energetic context is first depicted. Then the studied optimization problem is defined as the optimal management of production and consumption activities in houses. A scheduling problem is identified to adjust the energy consumption to both the energy cost and the inhabitant’s comfort. The available flexibilities of the services provided by domestic appliances are used to compute optimal energy plans. These flexibilities are associated to time windows or heating storage abilities. A constraints formulation of the energy allocation problem is given. A derived mixed linear program is used to solve this problem. The energy consumption in houses is very dependent to uncertain data such as weather forecasts and inhabitants’ activities. Parametric uncertainties are introduced in the home energy management problem in order to provide robust energy allocation. Robust linear programming is implemented. Event related uncertainties are also addressed through stochastic programming in order to take into account the inhabitant’s activities. A scenario based approach is implemented to face this robust optimization problem.
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References
AFNOR (2006) Ergonomie des ambiances thermiques. Norme Européenne et Française
Alvarez-Valdés Olaguíbel R, Tamarit Goerlich J (1993) The project scheduling polyhedron, facets and lifting theorems: dimension, facets and lifting theorems. Eur J Oper Res 67(2): 20–204
Artigues C, Lopez P, Hait A (2009) Scheduling under energy constraints. In: International conference on industrial engineering and systems management (IESM 2009), Monrea, Canada
Bertsimas D, Sim M (2004) The price of robustness. Oper Res 52-1: 35–53
Billaut JC, Moukrim A, Sanlaville E (2008) Flexibility and robustness in scheduling. ISTE, Wiley, London
Castro P, Grossmann I (2006) An efficient mipl model for the short-term scheduling of single stage batch plants. Comput Chem Eng 30: 1003–1018
Freire R, Oliveira G, Mendes N (2008) Predictive controllers for thermal comfort optimization and energy savings. Energy Build 40: 1353–1365
Ha D (2007) Un système avancé de gestion d’énergie dans le bâtiment pour coordonner production et consommation. Ph.D. thesis, Grenoble Institute of Technology, Grenoble, France
Ha DL, Ploix S, Zamai E, Jacomino M (2006) A home automation system to improve the household energy control. In: INCOM2006 12th IFAC symposium on information control problems in manufacturing
Hawarah L, Jacomino M, Ploix S (2010) Smart home: user’s behavior prediction of home energy consumption. In: 7th International conference on informatics in control, automation and robotics
House J, Smith T (1995) Optimal control of building and hvac systems. In: Proceedings of the American control conference, Seattle, Washington
IEA (2006) Energy technology perspectives: scenarios and trategies to 2050. IEA Publications
Koné O, Artigues C, Lopez P, Mongeau M (2011) Event-based milp models for resource-constrained project scheduling problems. Comput Oper Res 38(1):3–13
Le MH, Jcomino M, Ploix S DLH (2009) An approach for home load energy management problem in uncertain context. In: Dubrovnik conference on sustainable development of energy, water and environment systems (SWEDES 2009)
Liu N, Ritzert G, Belloc A (2005) Rapport final: ModTlisation des flux TnergTtiques dans une maison autonome. Technical report, Ecole Centrale de Lyon
Lopez P, Roubellat F (2008) Production scheduling. ISTE, Wiley, London
Lozano MA, Ramos J, Carvalho M, Serra L (2009) Structure optimization of energy supply systems in tertiary sector buildings. Energy Build 41: 1063–1075
Mago P, Chamra L (2009) Analysis and optimization of cchp systems based on energy, economical, and environmental considerations. Energy Build 41: 1099–1106
Mingozzi A, Maniezzo V, Ricciardelli S, Bianco L (1998) An exact algorithm for the multiple resource- constrained project scheduling problem based on a new mathematical formulation. Manag Sci 44(5): 29–714
Mulvey J, Ruszczynski A (1995) A new scenario decomposition method for large-scale stochastic optimization. Oper Res 43(3): 477–490
Pinto JM, Grossmann I (1995) A continuous time mixed integer linear programming model for short term scheduling of multistage batch plants. Ind Eng Chem Res 35: 338–342
Pinto JM, Grossmann IE (1998) Assignment and sequencing models for the scheduling of process systems. Ann Oper Res 81: 433–466
Roy B (2010) Robustness in operational research and decision aiding: a multi-faceted issue. Eur J Oper Res 200(3): 629–638
Wood G, Newborough M (2007) Influencing user behaviour with energy information display systems for intelligent homes. Int J Energy Res 31: 56–78
Yu CS, Li HL (2000) A robust optimization model for stochastic logistic problems. Int J Prod Econ 64: 385–397
Zhou G, Krarti M (2005) Parametric analysis of active and passive building thermal storage utilization. J Solar Energy Eng 127: 37–46
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Jacomino, M., Le, M.H. Robust energy planning in buildings with energy and comfort costs. 4OR-Q J Oper Res 10, 81–103 (2012). https://doi.org/10.1007/s10288-011-0192-6
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DOI: https://doi.org/10.1007/s10288-011-0192-6