Buildings are responsible for a significant portion of energy consumption worldwide. Intelligent buildings have been devised as a potential solution, where energy consumption and building use are harmonised. At the heart of the intelligent building is the building energy management system (BEMS), the central platform which manages and coordinates all the building monitoring and control subsystems, such as heating and lighting loads. There is often a disconnect between the BEMS and the building it is installed in, leading to inefficient operation, due to incongruous commissioning of sensors and control systems. In these cases, the BEMS has a lack of knowledge of the building form and function, requiring further complex optimisation, to facilitate efficient all year round operation. Flawed BEMS configurations can then lead to ‘sick buildings’. Recently, building energy performance simulation (BEPS) has been viewed as a conceptual solution to assist in efficient building control. Building energy simulation models offer a virtual environment to test many scenarios of BEMS operation strategies and the ability to quickly evaluate their effects on energy consumption and occupant comfort. Challenges include having an accurate building model, but recent advances in building information modelling (BIM) offer the chance to leverage existing building data, which can be translated into a form understood by the building simulator. This study will address these challenges, by developing and integrating a BEMS, with a BIM for BEPS assisted predictive control, and assessing the outcome and potential of the integration.

This thesis presents the design and implementation of control strategies for building energy management systems (BEMS). The controllers considered include the multi PI-loop controllers, state-space designs, constrained input and output MIMO adaptive controllers, fuzzy logic solutions and genetic algorithm techniques. The control performances of the designs developed using the various methods based on aspects such as regulation errors squared, energy consumptions and the settling periods are investigated for different designs. The aim of the control strategy is to regulate the room temperature and the humidity to required comfort levels. In this study the building system under study is a 3 input/ 2 output system subject to external disturbances/effects. The three inputs are heating, cooling and humidification, and the 2 outputs are room air temperature and relative humidity. The external disturbances consist of climatic effects and other stochastic influences. The study is carried out within a simulation environment using the mathematical model of the test room at Loughborough University and the designed control solutions are verified through experimental trials using the full-scale BMS facility at the University of Bradford.

This thesis presents the design and implementation of control strategies for building energy management systems (BEMS). The controllers considered include the multi PI-loop controllers, state-space designs, constrained input and output MIMO adaptive controllers, fuzzy logic solutions and genetic algorithm techniques. The control performances of the designs developed using the various methods based on aspects such as regulation errors squared, energy consumptions and the settling periods are investigated for different designs. The aim of the control strategy is to regulate the room temperature and the humidity to required comfort levels. In this study the building system under study is a 3 input/ 2 output system subject to external disturbances/effects. The three inputs are heating, cooling and humidification, and the 2 outputs are room air temperature and relative humidity. The external disturbances consist of climatic effects and other stochastic influences. The study is carried out within a simulation environment using the mathematical model of the test room at Loughborough University and the designed control solutions are verified through experimental trials using the full-scale BMS facility at the University of Bradford.