Sensitivity analysis and energy optimization in residential complex in warm and semi-humid climates of Iran (Dezful)

Building energy optimization based on sensitivity analysis, considering all parameters influencing energy consumption, has not been so far implemented in Iran. Among the few previous works in this line, only one or two factors have been investigated. Thus, the present study can be introduced as the most complete one of its kind. To this end, the researchers first simulated energy consumption in a building located in the city of Dezful, southwestern Iran, with a hot and semi-humid climate, through the Quick Energy Simulation Tool (eQUEST) to illustrate thermal load for an assortment of important parameters. Then, they extracted some relationships using the SPSS Statistics, to connect energy (namely, electricity and gas) used in the building with the factors concerned. Finally, validations were performed to check the results via converting the data into neural networks and employing a genetic algorithm (GA) at each level of the study. The error between the software results and the annual gas bills was 9.2% and the error between the regression function and the measured values was ˃1%. Moreover, optimization error was about 4.3%. The results demonstrated that equipment power density and heating system efficiency were respectively among factors that could significantly affect electricity and gas consumption rates in buildings located in the climate in question.