Multi-stage optimization and meta-model analysis with sequential parameter range adjustment for the low-energy house in Korea

Abstract

The demand for low-energy building in the market is growing in Korea. However, transition of the market is slow mainly due to shortage of relevant information regarding the selection of energy saving design and technical elements with their subsequent impact on energy performance. Recent development of optimization tools has tried to integrate energy performance simulation with conventional architectural design process. However, these new optimization techniques such as stochastic optimization, sensitivity analysis, and meta-model analysis failed to provide sufficient knowledge base for all stakeholders during the design process despite their potentials. The objective of this study was to test an integrated process of optimization analysis and information production. An integrated automatic simulation framework was established with Passive House Planning Package (PHPP) and modeFrontier. Sequential adjustment of ranges of influential parameters was then performed until the median value of heating demand in randomly constructed design of experiment (DOE) cases reached two target performance levels. 2D plot charts for influential parameters in each target performance level were obtained based on meta-model analysis satisfying low-energy target objects.Main findings of this study are as follows: 1) Technical parameters are more influential than design parameters. Thus, it is necessary to establish technical levels for selected primary parameters such as SHGC and linear thermal transmittance; 2) The influential priority of parameters changes through eight simulation phases. Thus, the reliability of the sensitivity analysis is largely dependent on the defining realistic and feasible ranges for every planning parameter; 3) In the case of newly-introduced parameters and technologies, the proposed methodology of multi-stage optimization analysis for advising technical level has potential to provide enough information regarding the selection of appropriate technical levels and the interrelationship among other parameters.Comparative analysis of simulation results and experts’ cognition was conducted. Results of analysis show that education for thermal bridge free design is required and solar heat gain coefficient (SHGC) of glazing should be addressed more seriously. The final design decision advisory 2D charts of influential parameters in two performance target levels showed potential of knowledge platform for all stakeholders during the design process. Although this study simulated and tested the potential of multi-stage optimization based on heating demand of the prototype rural house, the methodology could be expanded to the multi-objective optimization, including cooling and lighting consumptions.