Disaggregating power consumption of commercial buildings based on the finite mixture model

Yang Zhou, Zhixiong Shi, Zhengyu Shi, Qing Gao and Libo Wu ()

Applied Energy, 2019, vol. 243, issue C, 35-46

Abstract: Power disaggregation that breaks down the overall power consumption to appliance level acts as a feasible technical solution to meet the extensive data demand but reduce the costs of installing advanced metering system in Demand Side Management (DSM). Considering the intensive query of high-frequency training data of existing methods, this paper presents a new behavior based model applicable to low-frequency data by introducing external determining factors of power consumption into a finite mixture model (FMM) that disaggregates overall power consumption into those of various electrical appliances. Empirical verification by employing a dataset including detailed hourly appliance-level power consumption of commercial buildings in Shanghai proves that this newly developed model can provide more accurate result than other previous models but requires relatively lower-frequency data. The benefits of energy-saving potential from information feedback and appliance replacement facilitated by disaggregation data is further simulated to show the practical application.

Keywords: Energy disaggregation; Hourly consumption data; Finite mixture model (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.apenergy.2019.03.014

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