Optimization of Building Energy Consumption Considering Uncertainties

Energy optimization and consumption analysis is the first step in realizing smart houses. This paper incorporates the uncertainty of the effective parameters and probabilistically optimizes the energy consumption in a building. To this end, probability density functions (PDFs) of building uncertain parameters are modeled by empirical rule method and the energy usage in buildings is optimized. Energy-Plus and MATLAB softwares are respectively used to compute energy consumption in a building and to optimize energy consumption. Energy consumption of the building and the thermal comfort are considered as objective functions of the proposed multi-objective optimization problem. A 12-storey commercial building is used as a case study. The proposed probabilistic method is compared with the deterministic method to assess the proposed method,. The results show a significant difference between the deterministic and probabilistic cases. The maximum difference between the mean optimal values of variable parameters in these cases is about 34%. Finally, sensitivity of the results to the climate changes is also investigated in this paper.