The decisions made during conceptual building design irreversibly influence the selection and dimensions of thermal energy generation and storage components and systems. A method to quantify this influence is developed. It consists of the quasi-stationary simulation and the design optimization of the system. Demonstrated on seven preconfigured systems, the method is used to propose a tool that, using data available at the conceptual design stage, provides dimensions, costs, energy consumption and emissions of the optimized system to architects.
The thermal conditioning systems are responsible for almost half of the energy consumption by commercial buildings. In many European countries and in the USA, buildings account for around 40% of primary energy consumption and it is therefore vital to explore 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 a building’s energy performance and, conversely, many generation and storage components impose restrictions on building design and, by their nature, 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 use of the developed method by architects during the 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 performance profiles obtained are then 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 mod-els. 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. Making this tool available to the architects represents an effective way to consider the primary HVAC during the preliminary design, with-out 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 building energy consumption and inspire further education in this field.