Quantifying the effect of multiple demand response actions on electricity demand and building services via surrogate modeling

The expansion of commercial building demand response (DR) as a demand-side management resource for the electric grid necessitates new decision support resources for customers to rapidly assess the benefitrisk tradeoffs of candidate load flexibility strategies. This work develops surrogate models of load flexibility impacts on office building electricity demand and indoor temperature. The surrogate models are fit to a large synthetic database generated via whole building simulations of multiple flexibility strategies under a variety of conditions; the models are translated to a Bayesian framework to allow straightforward communication of uncertainty and parameter updating given new evidence. The strong predictive performance of the models underscores their potential utility in guiding DR decision-making in office settings.