There is a crucial need to reduce energy consumption in all fields. International initiatives, such as the COP21, and European ones, such as 20/20/20, have a fundamental objective to achieve countries to reduce their energy consumption. In Europe, buildings contribute to more than 40% of the total energy consumption. In addition, small and large business owners seek to reduce costs.
Both events have aroused interest in technologies that enable intelligent monitoring, with computer support, to control the buildings' equipment. These types of buildings, known as Smart Buildings, represent the future, and their mission will be to combine the energy saving with their occupants' comfort.
Energy consumption is determined by many and different sources, such as the equipment's efficiency, the building materials and the meteorological conditions. However, energy consumption of buildings is proved to be largely influenced by the presence and behaviors of occupants. In relating to this, there is a significant uncertainty caused by occupant behaviors that produces significant discrepancy between the predicted and actual energy usage. In the real world, most systems of control and operation of buildings in energy matter consider general models based on occupants' schedules and general behaviors that leads to large predictive and optimization errors. In addition, these systems never consider how the information from the individual preferences could improve the occupant's comfort. Therefore, the technology will be employed to improve not only the energy consumption but also the occupancy comfort and it is clear that this objective requires the use of simulators that allows to generate premonitory studies that justify the investments.
Currently, several different software capable to realize architecture and energy studies in buildings are available. These generally allow to make studies by accurately modifying the materials of windows, roof and walls, or the characteristics of the equipment and the machinery. Nevertheless, occupancy behavior can only be configured with fixed schedules.
The design and implementation of occupancy simulation and methodologies for the improvement of energy efficiency in buildings is performed as objective of this project, that could be divide in three parts. First, an agent-based occupancy simulator will be designed and programmed. This software could be used for other social simulations, such as emergency evacuations. Secondly, useful features and elements for energy models will be added. Electrical equipment, lights and air conditioning systems will be modeled as passive agents. In addition, energy and comfort measures will be evaluated. Finally, the simulated environment's operations will be modified by distinct policy or control strategies involving different levels of intelligent operation. The obtained comfort and energy results will be evaluated and analyzed.
Python will be the programming language used for the implementation of the simulator. The results will be represented with IPython and Notebooks technology.