Laura Klein

Towards Optimization of Building Energy and Occupant Comfort Using Multi-Agent Simulation

The primary consumers of building energy are heating, cooling, ventilation, and lighting systems, which maintain occupant comfort, and electronics and appliances that enable occupant functionality. The optimization of building energy is therefore a complex problem highly dependent on unique building and environmental conditions as well as on time dependent operational factors. To provide computational support for this optimization, this paper presents and implements a multi-agent comfort and energy simulation (MACES) to model alternative management and control of building systems and occupants. Human and device agents are used to explore current trends in energy consumption and management of a university test bed building. Reactive and predictive control strategies are then imposed on device agents in an attempt to reduce building energy consumption while maintaining occupant comfort. Finally, occupant agents are motivated by simulation feedback to accept more energy conscious scheduling through multi-agent negotiations. Initial results of the MACES demonstrate potential energy savings of 17% while maintaining a high level of occupant comfort. This work is intended to demonstrate a simulation tool, which is implementable in the actual test bed site and compatible with real-world input to instigate and motivate more energy conscious control and occupant behaviors.

Continuous Sensing of Occupant Perception of Indoor Ambient Factors

Ambient factors such as temperature, lighting, and air quality influence occupants’ productivity and behavior. Although these factors are regulated by industry standards and monitored by the facilities management groups, occupants’ perceptions vary from actual values due to various factors such as building schedules and occupancy, occupant activity and preferences, weather and climate, and the placement of sensors. While occupant comfort surveys are sometimes conducted, they are generally limited to one-time or periodic assessments that do not fully represent occupant experiences throughout building operations. This study proposes a new methodology for gathering real time data on a continuous basis through participatory sensing of occupant ambient comfort in indoor environments based on a smart phone application. The developed application is presented and validated by a pilot study in a university building. Occupant perceptions of temperature are compared to actual temperature records. No correlation is found between perceived and actual room temperatures demonstrating the potential of a participatory sensing tool for adaptively controlling building temperature ranges.

Comparison of Image-Based and Manual Field Survey Methods for Indoor As- Built Documentation Assessment

As-built models and drawings are essential documents used during the operations and maintenance of buildings for managing facility spaces, equipment, and energy systems. Inefficiencies in processing, communicating, and revising as-built documents therefore result in high costs imposed on building owners. Facility managers still rely heavily upon manual surveying procedures for developing and verifying as-built drawings and models. To streamline this often time consuming process, this paper addresses the advantages and limitations of photogrammetry for remote sensing and verification of interior as-built conditions. Two classrooms are captured using photogrammetric image processing software and image-based dimensions are compared to dimensions gathered through a traditional manual survey yielding an average percent error of approximately 2%. Both image-based and manual dimensions are then compared to dimensions extracted from an existing asbuilt BIM model of the interior spaces, and the proposed image-based verification method successfully identifies the same gross errors in the as-built BIM model.