An automated process is developed to perform dynamic energy simulations for several hundreds or thousands of the conditions required to examine the influence of dozens of building envelope design factor changes on the heating and cooling load of a building. The developed process was applied for 10-factor 128-treatment fractional factorial design, it was experimentally confirmed that the simulated preparation period, which took about 1 day to complete via manual operation, took about 10 min using the automated process; this represents a 400-fold increase in speed. It is shown that the processing time savings obtained with the automation process increase exponentially as the number of design factors considered increases. The regression equations between heating and cooling loads and design factors are analyzed with a multi-objective optimization algorithm to obtain the Pareto-front, which is a combination of optimal design factors that can be used to minimize the building heating and cooling loads and to provide building designers with viable alternatives by considering the building energy performance.