Data-driven based estimation of HVAC energy consumption using an improved Fourier series decomposition in buildings

作者：Niu Fuxin; O'Neill Zheng^*; O'Neill Charles

来源：Building Simulation, 2018, 11(4): 633-645.

DOI：10.1007/s12273-018-0431-2

• data-driven
• decomposition
• Fourier series
• HVAC energy estimation

Many data-driven algorithms are being explored in the field of building energy performance estimation. Choosing an appropriate method for a specific case is critical to guarantee a successful energy operation management such as measurement and verification. Currently, little research work on assessment of different data-driven algorithms using real time measurement data sets is available. In this paper, five commonly used data-driven algorithms, ARX, SS, N4S, discretized variable BN and continuous variable BN, are used to estimate HVAC related electricity energy consumption in a university dormitory. In practice, total energy consumption data is easily accessible, while separated HVAC energy consumption data is not commonly available due to expensive sub-metering and/or the complexity of mechanical and electrical layouts. A virtual sub-meter based on a decomposition method is proposed to separate HVAC energy consumption from the total building energy consumption, which is derived from an improved Fourier series based decomposition method.

• 出版日期2018-8