Paper Conference

Proceedings of Building Simulation 2011: 12th Conference of IBPSA


MEESG – A Total Energy Demand Prediction and Optimization Program for Architectural Scheme Design Stage

Xiaoru Zhou, Borong Lin, Yingxin Zhu

Abstract: In this research, a new energy-­saving design method and a design-­aided program MEESG (Most-­Energy-­ Efficient-­Scheme-­Generator) are developed. The program aims to aid energy-­saving design by means of optimization algorithms at a very early design stage, when the building shape is not even determined by the architects. In this program, a simplified prediction model BEFPM (Building Energy Demand Fast Prediction Model) is established to simulate the building total energy demand very quickly. Meanwhile, by introducing Genetic Algorithm into BEFPM, from shape and envelope parameters to HVAC system forms, the systems, and can be utilized in a very early design stage when the building shape is not even determined. The structure of this method is: (1) A fast prediction model (BEFPM) for building total energy demand, in which the sub-­models are validated by some well-­accepted simulation softwares such as DeST (Jiang 1997), Radiance (Ward et al. 1996) and Daysim (Reinhart 2001), or established by mass practical testing data. (2) A Genetic Algorithm (GA) model with BEFPM as its fitness evaluation function to pick the most energy efficient schemes by computer automatically. The structure of this research is shown in Figure 1. computer can automatically generate the design parameters of the most energy efficient scheme(s).
Pages: 546 - 553