Probabilistic Energy Efficiency Analysis in Buildings Using Statistical Methods

Energy efficiency analysis has been presented recently to minimize the energy consumption of buildings by designing the optimal structural parameters. Because of uncertain parameters incorporated in the energy analysis of a building, computationally effective methods are needed to model the uncertainties in the analysis. In this paper, a probabilistic multi-objective optimization method is proposed based on the statistical methods, i.e., the empirical rule method and two-point estimate method, for analyzing the energy efficiency in buildings. The energy consumption density and thermal discomfort function of residents are considered as the objective functions of the optimization problem. The model of a 12-story commercial building is used to examine the proposed method. Probabilistic methods are compared with the deterministic one to show the effect of considering uncertainties on the results. According to the results, there is a substantial difference between the optimal values of the building's parameters by applying probabilistic and deterministic methods.