Why is the reliability of building simulation limited as a tool for evaluating energy conservation measures?

Abstract

Buildings account for approximately 32% of the total energy consumption globally and up to 40% in the developed countries, which makes buildings a prime target for energy conservation. Various energy conservation measures (ECMs) have been proposed to improve the energy efficiency in buildings, and these ECMs are usually designed and assessed using calibrated building energy models. However, there is empirical evidence that reveals noticeable discrepancies between simulated performances of ECMs reported in building energy models and their actual performances measured in buildings. This paper examines two possible causes of such discrepancies. Specifically, this paper tests the following two hypotheses: (1) using assumed occupancy data as opposed to actual occupancy data in building energy simulation reduces the reliability of estimated performance of demand-driven ECMs; and (2) using an energy model built for one ECM to cross estimate energy consumption of another ECM is statistically inaccurate. An educational building was used as a test bed. The results proved both hypotheses true, showing that estimations were more accurate and consistent for models calibrated using actual occupancy compared with those using assumed occupancy, and that cross-ECM estimation resulted in statistical inaccuracy. The findings indicated that current

Occupancy prediction through Markov based feedback recurrent neural network (M-FRNN) algorithm with WiFi probe technology

“…However, many studies suggested that actual energy performances of buildings severely deviates from their original design conditions due to incorrect assumption or estimation of occupancy behavior [3][4][5][6]. Significant discrepancies have been observed [7,8] due to complicated interrelationship of energy consumption in building facilities and occupancy behavior [9][10][11].…”

Evaluating energy performance in non-domestic buildings: A review

“…A range of studies have shown individual case studies or evaluations of the results of many building energy simulations. While some carefully endorse simulation as being able to predict performance when models are accurately built [83], others show that uncalibrated simulations are often very far from representing reality and may not be useful tools for predicting performance [84], [85].…”

Energy utilizability concept as a retrofitting solution selection criterion for buildings

“…Many studies have identified simulation as a good tool for building studies Ann 2002), such as its capability to evaluate the system performances when field experiments are infeasible and the investigation of various retrofitting solutions before being implemented. However, the reliability issue of using building energy models for assessing these solutions, especially the cross estimation between different solutions, has been well noticed in previous study (Li et al 2015). While all the retrofitting solution are simulated based on the calibrated base case, there is lack of possible and available data to calibrate the model after applied each solutions.…”