GG Brown 2029
Title: "Modeling the Occupant Behavior, Building Systems Performance, and Energy Consumption Nexus Using Multi-Method Distributed Simulation"
Buildings consume 40% of the total energy produced in the United States (US), making this sector an opportune choice for devising strategies aimed at reducing energy consumption. Even though various tools and simulation frameworks have been developed in prior work for evaluating, monitoring, and regulating the energy use in buildings, their deployment has primarily been in the form of standalone applications that consider limited aspects of the entire system. For example, energy simulation programs provided by the US Department of Energy such as EnergyPlus and eQuest calculate the annual operating energy in a building by assuming static parameters for occupancy schedules and performance of building systems. However, this approach does not consider the effects of occupants’ dynamic energy use behavior or the effects of material and systems degradation over the life cycle of a building, among other influencing factors. Therefore, the primary objective of this dissertation is to create a simulation framework that is capable of modeling and analyzing a building’s energy consumption with improved accuracy by considering dynamic influencing factors through an interdependent analysis.
A primary contribution of this research effort is the Lightweight and Adaptive Building Simulation (LABS) framework, an innovative distributed computing environment that can conduct a life cycle based building energy simulation by incorporating several dynamic energy-influencing factors in unison. LABS integrates all the energy requirements occurring in a building’s life cycle such as embodied, operational and end of life energy demands, thereby visualizing the inter-dependency among these energy requirements and all dynamic influencers affecting a building’s life cycle energy profile.
The effectiveness of the LABS framework was evaluated and demonstrated through several case-study analyses. A system dynamics based energy simulation analysis performed on a case study building located in Chicago has shown that energy savings of up to 20.5% are possible by adopting effective operational and maintenance schemes in a building’s entire life cycle. Similarly, it has also been demonstrated that influencing occupant behavioral choices through energy based interventions, can achieve energy savings of up to 13% per month. These two observations highlight the importance of analyzing the effects of dynamic factors in a building’s life cycle and the capabilities of the LABS framework in analyzing and quantifying the interdependent effects of such factors during a building’s life cycle. By allowing coupled effects of multiple energy-influencing processes to be concurrently explored, this research opens future possibilities for the performance-based assessment of building energy systems.
Chair: Carol Menassa