Paper Conference

Proceedings of BSA Conference 2017: Third Conference of IBPSA-Italy

     

Stochastic Multi-Criteria Decision Making of Energy Recovery Ventilation Systems using Cumulative Prospect Theory

Young Jin Kim

Abstract: Recently, an Energy Recovery Ventilator (ERV) in a residential building was seen as an attractive ventilation option in terms of energy saving and indoor air quality. In order to identify a feasible set among many ventilation strategies in this situation, various decision-making approaches (deterministic or stochastic) using Building Performance Simulation (BPS) tools have been suggested. As a simulation-based decision-making approach, a Stochastic Multi-Criteria Decision Making (SMCDM) method based on Cumulative Prospect Theory (CPT) is presented in this paper to find the best ventilation strategy under model uncertainties. For this study, two ventilation strategies, considering air inlet positions and CO2 sensor positions, were chosen and modelled using two simulation tools: CONTAMW 3.1 for the airflow model and EnergyPlus for the thermal model. In addition, Latin Hypercube Sampling (LHS) was used to reflect the model uncertainties. In this study, it is shown that CPT can provide a more realistic and trustworthy framework than the Bayesian decision theory.
Pages: 513 - 520
Paper:
bsa2017_9788860461360_63