| Title |
Application of Stochastic Multi-Criteria Decision Making Approach for Design Support of Energy Recovery Ventilator |
| DOI |
https://doi.org/10.5659/JAIK_SC.2017.33.4.79 |
| Keywords |
Stochastic Multi-Criteria Decision Making ; Uncertainty ; Monte Carlo ; Cumulative Prospect Theory ; Ventilation |
| Abstract |
Recently, a Energy Recovery Ventilator(ERV) in a residential building has been highlighted as an attractive ventilation option in terms of energy saving and Indoor Air Quality(IAQ). For identifying a feasible set among many ventilation strategies in this situation, various decision making approaches(deterministic or stochastic) using building simulation tools have been suggested. In the simulation based decision making approaches, this paper addresses a Stochastic Multi-Criteria Decision Making(SMCDM) method based on Cumulative Prospect Theory(CPT) for finding a preferred 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 an air-flow model and EnergyPlus for a thermal model). And Latin Hypercube Sampling(LHS) was used to reflect model uncertainties. In this study, it is shown that CPT can lead to better a realistic and trustworthy framework, rather than Bayesian decision theory mentioned in a building simulation domain. |