Emulation based uncertainty and sensitivity analysis for complex building performance simulation - Wate, Parag (2020)
Uncertainties in building performance simulation arise from the propagation of both epistemic (e.g. due to poorly or un- observed input parameters) and aleatory (e.g. due to occupants' stochastic interactions) uncertainties. A good framework for the quantification and decomposition of uncertainties in dynamic building performance simulation should: (i) simulate the principle deterministic processes influencing heat flows in buildings and the stochastic perturbations to them, (ii) quantify and decompose the total uncertainty into its respective sources, and the interactions between them, and (iii) achieve this in a computationally efficient manner. In this thesis, a new framework, named as Emulation based Uncertainty and Sensitivity Analysis (EmUSA) framework, is introduced which does just that. Two case studies, a monozone office building for the frameworks' proof of principle and the other multizone residential building for it's extension are being investigated to perform Uncertainty and Sensitivity Analysis for the Complex case of Building Performance Simulation (BPS) i.e. the Stochastic BPS (S-BPS). The detailed development of this new framework for emulating both the mean and the variance in the response of a stochastic building performance simulator (EnergyPlus co-simulated with a multi-agent stochastic simulator called No-MASS) is presented, for heating and cooling load predictions.