Design optimization of insulation usage and space conditioning load using energy simulation and genetic algorithm

Architectural design is a process to find the best solution to satisfy various design criteria. To achieve sustainable and green design, performance simulations are often used to verify these criteria and modify the design. The conventional approach of manual trial-and-error is too time-consuming to be practical. Introducing optimization technique can greatly improve the design efficiency and help designers find the optimal design. In this paper, modeFRONTIER was used as the design optimization environment to find the best insulation strategy to minimize the space conditioning load of an office building located in Nanjing, China while keeping the insulation usage at minimum. EnergyPlus was integrated into the optimization tool by writing a DOS batch file to automate the work flow. The search engine was the genetic algorithm and it proved to be able to generate a well-defined Pareto frontier in a reasonable number of runs. Based on the Pareto frontier, the designer can specify his preferences and select the final design. The case study shows that an energy simulation program can be effectively integrated into a design optimization environment to find the optimal design. The technique presented has a broad application in architectural design, especially when the design considerations are multi-objective.