Next Article in Journal
The Effect of Value Co-Creation on Social Enterprise Growth: Moderating Mechanism of Environment Dynamics
Next Article in Special Issue
Evaluation of Building Energy and Daylight Performance of Electrochromic Glazing for Optimal Control in Three Different Climate Zones
Previous Article in Journal
Affordability Assessment of Energy-Efficient Building Construction in Italy
Previous Article in Special Issue
A Sustainable Power Plant Control Strategy Based on Fuzzy Extended State Observer and Predictive Control
Open AccessArticle

An Optimal Load Disaggregation Method Based on Power Consumption Pattern for Low Sampling Data

by Huijuan Wang 1,2,3, Wenrong Yang 1,2,*, Tingyu Chen 3 and Qingxin Yang 1,2
1
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China
2
Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, China
3
School of Computer and Remote Sensing Information Technology, North China Institute of Aerospace Engineering, Langfang 065000, China
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(1), 251; https://doi.org/10.3390/su11010251
Received: 16 December 2018 / Accepted: 31 December 2018 / Published: 7 January 2019
(This article belongs to the Collection Power System and Sustainability)
In recent years, Smart Grids have been developing globally. Since smart meters only acquire low-frequency data, non-intrusive load monitoring technology using the signature extracted from high-frequency data needs an additional measurement device to be installed, so it is not suitable for promotion to the smart grid environment. However, methods using low-frequency features are poorly-suited when several appliances are switched on at the same time, or devices with similar power values are used. In response to these problems, this paper proposes a load disaggregation method based on the power consumption patterns of appliances, combining an improved mathematical optimization model and optimized bird swarm algorithm (OBSA) for load disaggregation. Experiments show that the method can effectively identify the operating states of appliances, and deal with situations in which multiple instruments have similar power characteristics or are simultaneously switching. The performance comparison proves that the improved model is more efficient than the traditional active and reactive power (PQ) optimization model in load disaggregation performance and computation time, and also verifies the robustness of the proposed method and the convergence of OBSA. As an inexpensive method without extra measurement hardware installed, the process is suitable for large-scale applications in smart grids. View Full-Text
Keywords: non-intrusive load monitoring; load disaggregation; power consumption pattern; improved bird swarm algorithm; low-frequency data non-intrusive load monitoring; load disaggregation; power consumption pattern; improved bird swarm algorithm; low-frequency data
Show Figures

Figure 1

MDPI and ACS Style

Wang, H.; Yang, W.; Chen, T.; Yang, Q. An Optimal Load Disaggregation Method Based on Power Consumption Pattern for Low Sampling Data. Sustainability 2019, 11, 251.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop