Whole building energy simulation (BES) models play a significant role in the design and optimisation of buildings. Simulation models may be used to compare the cost-effectiveness of energy-conservation measures (ECMs) in the design stage as well as assessing various performance optimisation measures during the operational stage. However, due to the complexity of the built environment and prevalence of large numbers of independent interacting variables, it is difficult to achieve an accurate representation of real-world building operation. Therefore, by reconciling model outputs with measured data, we can achieve more accurate and reliable results. This reconciliation of model outputs with measured data is known as calibration.
This paper presents a detailed review of current approaches to model development and calibration, highlighting the importance of uncertainty in the calibration process. This is accompanied by a detailed assessment of the various analytical and mathematical/statistical tools employed by practitioners to date, as well as a discussion on both the problems and the merits of the presented approaches. (C) 2014 Elsevier Ltd. All rights reserved.