This paper describes an approach aiming to automatically transform a model depicting a high level physical behavior into two different optimized building energy management application models. Basically, each application requires specific formalism and information therefore it is necessary to rewrite an initial physical behavior model to obtain application models. Up to now, these two application models should be rewritten manually, which is representing an significant work and possibly a source of error. In order to automatize this process, the MDE approach seems to be an appropriate solution. This paper presents core specifications of transformation of hinge model into application models. To illustrate this approach, transformations into both an acausal anticipative model based on a mixed integer linear programming problem and a nonlinear causal model for fast simulated annealing optimization are shown. These models are used for energy management of a smart building platform named "Monitoring and Habitat Intelligent" PREDIS in Grenoble, France.

Abstract-This paper proposes a model transformation approach for model-based energy management in buildings. Indeed, energy management is a large area that covers a wide range of applications such as simulation, mixed integer linear programming optimization, simulated annealing optimization, model parameter estimation, diagnostic analysis,. . . Each application requires a model but in a specific formalism with specific additional information. Up to now, application models are rewritten for each application. In building energy management, because the optimization problems may be dynamically generated, model transformation should be done dynamically, depending on the problem to solve. For this purpose, a model driven engineering approach combined with the use of a computer algebra system is proposed. This paper presents the core specifications of the transformation of a so-called high level pivot model into application specific models. As an example, transformations of a pivot model into both an acausal linear model for mixed integer linear programming optimization and a causal non-linear model for simulated annealing optimization are presented. These models are used for energy management of a smart building platform named Monitoring and Habitat Intelligent located at PREDIS/ENSE3 in

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