Modeling and simulation of individual user behavior for building performance predictions

User behavior is a key to the correct prediction of building performance. Performance is meant here not only in relation to energy consumption, but more importantly to user satisfaction and, in commercial buildings, job performance. The contributions of this paper are static and dynamic models of individual users and user activities in an office environment in relation to building control systems. The models are based on a well structured general model of five different domains of building entities, including user activities. Models for specific simulation projects are refinements of this general model. It is shown how multi-agent based simulations can be automatically derived from such models. A case study of an university office with irregular occupancy is introduced as an example. 1. INTRODUCTION Contemporary buildings are becoming more complex in structure, control, and operation. At the same time, demands for energy savings, user comfort, and security for example are increasing. Therefore, simulations during the design, construction , commissioning, and operation phases are becoming more and more important. So far, building simulations are primarily performance simulations. Most simulators assume simple algorithms for the control of internal air temperature and humidity, illumi-nance and other human comfort parameters and also assume fixed schedules for occupancy. With today's flexible work hours and more sophisticated occupation based and interactive controls these assumptions may lead to erroneous simulation results, which do not reflect the situation of the buildings during its operation. Therefore, the behaviors of individuals and user groups have to be modeled and integrated into building performance simulators to get more realistic results. This is the goal of our research work. Applications that we envision are for example in the design and test of control systems for heating, cooling, air quality, and natural lighting that react to individual user