Building energy modeling is essential to estimate energy consumption of buildings. Predicting building energy consumption benefits the owners, designers, and facility managers by enabling them to have an overview of building energy consumption and can help them to determine building energy performance during the design phase. This paper focuses on two different shapes of commercial building, H and rectangle to estimate energy consumption in buildings in three different climate zones, cold, hot-humid, and mixed-humid. To address this, DOE-2 building simulation software was used to build and simulate individual commercial building configurations that were generated using Monte Carlo simulation techniques. Ten thousand simulations for each building shape and climate zone were conducted to develop a comprehensive dataset covering the full range of design parameters.
Machine learning approaches for estimating building energy consumption
