Modeling and optimization of energy generation and storage systems for thermal conditioning of buildings targeting conceptual building design

Building thermal conditioning systems are responsible for almost half of the energy consumption in commercial buildings. Since, in many European countries and in the USA, buildings account for around 40% of the primary energy consumption, it is worth exploring further ways to reduce the HVAC (Heating, Ventilation and Air Conditioning) system energy consumption. This thesis investigates the relationship between the energy generation and storage systems for thermal conditioning of buildings (shorter: primary HVAC systems) and the conceptual building design. Certain building design decisions irreversibly influence the building energy performance and, in reverse, many generation and storage components impose restrictions on building design and therefore cannot be introduced at a later design stage. The objective is, firstly, to develop a method to quantify this influence, in terms of primary HVAC system dimensions, its cost, emissions and energy consumption and, secondly, to enable the usage of the developed method to architects during conceptual design. In order to account for the non-stationary effects of the intermittent renewable energy sources (RES), thermal storage and for the component part load efficiencies, a time domain system simulation is required. An abstract system simulation method is proposed based on seven pre-configured primary HVAC system models, including components such as boilers, chillers and cooling towers, thermal storage, solar thermal collectors, and photovoltaic modules. A control strategy is developed for each of the models and their annual quasi-stationary simulation is performed. The obtained performance profiles are used to calculate the energy consumption, carbon emissions and costs. The annuity method has been employed to calculate the cost. Optimization is used to automatically size the HVAC systems, based on their simulation performance. Its purpose is to identify the system component dimensions that provide minimal costs, emissions or consumption while maintaining the quality of the supply and, where specified, achieving the targeted annual solar ratio. Two optimization algorithms, the global bounded Nelder Mead and the Exhaustive search are implemented. Simulation and optimization performance has been evaluated using building and weather data for four cities situated in four different climates. Finally, a tool entitled PROBA has been proposed by adding a user interface to the models. The major characteristic of the interface is its suitability for non-expert users. This is achieved by, firstly, reducing amount of input data by implementing preset values and, secondly, providing information support. Providing this tool to the architects represents an effective way to consider the primary HVAC during the preliminary design, without causing additional cost. Although such a tool can never replace an HVAC engineer, its use can heighten the awareness of architects regarding the significance of the building energy consumption and inspire further education in this field.