Publications
Institutional heat wave analysis by building energy modeling fleet and meter data
• Shows detailed methodology for applying building energy model fleets to institutional heat wave analysis. • Demonstrates uncertainty in heat wave analysis based on meter data. • Shows how detailed building energy models used for energy retrofit analysis can be used for heat wave analyses. • The proposed methodology is much more extensible than data-driven or low-order energy models to detailed cross analyses between energy efficiency and resilience for future institutional studies. • Cross benefits between resilience analysis and energy retrofit analyses are demonstrated. Heat waves increase electric demand from buildings which can cause power outages. Modeling can help planners quantify the risk of such events. This study shows how Building Energy Modeling (BEM), meter data, and climate projections can estimate heat wave effect on energy consumption and electric peak load. The methodology assumes that a partial representation of BEM for an entire site of buildings is sufficient to represent the entire site. Two linear regression models of the BEM results are produced: 1) Energy use as a function of heat wave heat content and 2) Peak load as a function of maximum daily temperature. The uncertainty conveyed in meter data is applied to these regressions providing slope and intercept 95% confidence intervals. The methodology was applied using 97 detailed BEM, site weather data, 242 building meters, and NEX-DCP30 down-scaled climate data for an entire institution in Albuquerque, New Mexico. A series of heat waves that vary from 2019 weather to a peak increase of 5.9 °C was derived. The results of the study provided institutional planners with information needed for a site that is presently growing very rapidly. The resulting regression models are also useful for resilience analyses involving probabilistic risk assessments.