An enhanced linear regression-based building energy model (LRBEM plus ) for early design

作者：Al Gharably Maged; DeCarolis Joseph F^*; Ranjithan S Ranji

来源：Journal of Building Performance Simulation, 2016, 9(2): 115-133.

DOI：10.1080/19401493.2015.1004108

• EnergyPlus
• Monte Carlo simulation
• multivariate regression
• building geometry

The design community lacks simple, data-driven energy assessment tools to explore energy-efficient alternatives during the early stages of building design. A promising option is to utilize a whole building energy simulation engine (e.g. EnergyPlus) within a Monte Carlo simulation framework to develop a linear regression-based building energy model (LRBEM) that can predict idealized heating and cooling loads based on parameters relevant to early design. Previous work was limited to medium-sized US commercial office buildings with rectangular geometries. A key limitation is addressed in this paper by considering complex geometries. A reformulated model, LRBEM+, is developed and tested with a suite of building geometries that represent limiting cases. The resultant relative error between LRBEM+ and EnergyPlus is generally less than 10%. Furthermore, LRBEM+ correctly predicts the direction and magnitude of changes in heating and cooling loads in response to changes in the most influential early design parameters.

• 出版日期2016-3