Simultaneous Design and Control of Energy Systems

The comprehensive design of building energy systems incorporates the tasks of selection, dimensioning and control of devices. A simultaneous acquirement of these tasks is a necessity to achieve an overall optimal design. However, such mutual optimizations become a complex problem, implying a high computational effort. On the other hand, the concept of Smart Buildings is being introduced as a result of the altered boundary conditions such as directives, sustainability considerations, energy tariffs, user demands, and the emerging novel energy supply which is called the Smart Grid. Furthermore, due to the stringent requirements for integration of renewable energy sources and storage systems in future smart building systems, their complexity of design and control will increase inevitably. The goal of this thesis is to develop a design framework for the optimal selection, dimensioning, and control of smart building systems, in order to investigate the potentials and tackle the problems of such comprehensive design. In this framework, namely the smart building designer, 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. The implementation as a mixed integer linear programming problem allows the evaluation of the optimal system operation for an entire year in less than a minute on an average desktop computer. As a result, analyses on the sensitivity of designs to various boundary conditions such as governmental legislation and ambient conditions are carried out within reasonable amount of time. Using the design framework, several case studies are conducted. The first case study deals with the consequences of variable energy tariffs,