A Holistic Framework for Net-Zero Building Performance Modeling

Thesis Abstract

This study addresses the growing demand for credible, integrative methods to quantify and optimize net-zero performance in contemporary buildings by bridging energy, environmental, and retrofit considerations within a unified modeling framework. The aim is to develop a holistic framework for net-zero building performance modeling that synthesizes operational energy use, embodied energy, occupant behavior, and dynamic climatic conditions into a single, scalable tool suitable for design-stage optimization and post-occupancy evaluation. The specific objectives are to (i) articulate a theory-driven integration of energy performance, carbon impact, and lifecycle assessment within a single modeling architecture; (ii) formulate a modular analytical framework that couples building physics, occupant interaction, and supply-side energy systems; (iii) validate the framework against empirical data from a diverse sample of 60 operational buildings across temperate and hot-humid climates; (iv) assess the sensitivity of net-zero outcomes to design choices, material selections, and operational practices; and (v) derive design guidelines and policy-relevant indicators to support decision-making in early-stage projects and retrofit programs. A mixed-methods research design is employed, combining quantitative simulation-based modeling with qualitative validation and expert elicitation. The population comprises commercial, institutional, and high-performance residential buildings constructed or retrofitted within the last decade. A stratified random sample of 60 buildings is selected, ensuring representation across climate zones, building typologies, and retrofit levels. Data collection instruments include detailed building geometry and enclosure performance databases, monitored energy consumption data, sub-metered end-use data, material lifecycle inventories, and occupant behavior surveys coded for time-use patterns. Instrument validity is established through calibration against measured energy performance benchmarks and cross-validation with utility data. The methodological core integrates energy balance equations, control-volume analysis, and life cycle assessment within a modular simulation platform. Statistical techniques include regression analysis to quantify relationships between net-zero indicators and design variables, structural equation modeling to examine latent constructs linking behavior and performance, and Monte Carlo simulations to assess uncertainty in climate outputs and material emissions. The study also employs scenario analysis and sensitivity analysis to explore parameter influence and risk. The theoretical underpinning draws on the Theory of Planned Behavior to interpret occupant actions, and the Life Cycle Assessment framework to contextualize embodied versus operational emissions, with a systems-thinking lens derived from the Holistic Sustainability Model. Key expected findings include (1) a validated integrative model capable of predicting net-zero performance metrics (net energy consumption, total CO2e, and lifecycle emissions) within acceptable bounds across climate zones; (2) quantified contributions of operational efficiency, embodied carbon, and adaptive controls to net-zero performance; (3) identified leverage points in design and operation where marginal changes yield disproportionate reductions in emissions; (4) evidence on the interaction effects between occupant behavior and building automation within net-zero targets; and (5) robust uncertainty bounds for decision-makers under climate and market volatility. The study contributes to knowledge by delivering a transferable, theory-informed framework that unites building physics, lifecycle considerations, and behavioral dynamics into a single analytic tool, advancing neither purely prescriptive nor purely empirical approaches but a coherent, implementable methodology for net-zero performance assessment. The main conclusion anticipates that integrated, modular modeling can significantly improve predictive accuracy for net-zero outcomes and support proactive design optimization and retrofit prioritization. Recommendations include adopting the framework in early-stage design briefs to evaluate material choices and envelope strategies, incorporating occupant behavior modulation into control strategies, and developing standardized data reporting protocols to enable cross-project comparability and policy alignment. The study also suggests refining the framework to accommodate emerging energy technologies, such as on-site low-carbon generation and seasonal energy storage, to maintain relevance for future net-zero pathways.