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