Optimal design and operation of building services using mixed-integer linear programming techniques

As mandated by several directives issued by the European Union, starting from 2020, new buildings must be designed and constructed as low-energy buildings. This situation is to be achieved mostly by an installation of renewable energy technologies, storage systems, and improved insulations. As a result, the capital cost of these building systems and thus the potential for optimization will grow significantly. In addition, on the electric supply side, a smart grid with time-varying electricity tariffs may be established. These two directions of impact offer the opportunity to optimize the interactions between the so-called smart building and the distribution grid. Due to the stringent requirements for such future building systems, their complexity of design and control will increase inevitably. Therefore, in this paper a design framework for the optimal selection and sizing of a smart building system is presented. Various building services such as thermal and electrical storages, heating and cooling systems, and renewable energy sources are modeled and implemented using mixed-integer linear programming techniques. In order to enable a reasonable comparison of various configurations, optimal operating strategies are computed in parallel. Finally, the impact of regulatory policies and variable pricing systems on the design of the building components are examined.