Research on non‑invasive industrial equipment monitoring methods
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(State Grid Tianjin Electric Power Company, Tianjin 300100, China)

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TM615

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    Abstract:

    Non-invasive load monitoring (NILM) technology can obtain the electricity consumption information of various electrical devices of users without intruding into their premises, solely through the analysis of data from their electricity meters. NILM has been extensively researched and applied in residential load disaggregation, but its application in industrial loads is limited. On one hand, industrial loads differ significantly from residential loads in terms of load characteristics and data distribution, leading to a noticeable performance decline when methods designed for residential scenarios are applied to industrial settings. On the other hand, industrial users, concerned about privacy protection, are reluctant to disclose their electricity consumption data, making it highly challenging to effectively learn about industrial load equipment using limited data. To address these issues, an industrial load disaggregation method based on the factorial hidden Markov model (FHMM) is proposed. This method utilizes multiple independent hidden state chains of the FHMM to simulate the operational state transition process of industrial load equipment. By determining the state of the equipment at each moment, the electricity consumption of the equipment can be predicted in conjunction with state-specific energy consumption information. Finally, the proposed method is tested using on-site energy consumption monitoring data from a factory, and the results demonstrate its effective load disaggregation performance.

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赵学明,杨国朝,杨朝雯,郝 爽,焦 龙.非介入式工业设备监测方法研究[J].电力科学与技术学报英文版,2024,39(5):112-117. ZHAO Xueming, YANG Guozhao, YANG Zhaowen, HAO Shuang, JIAO Long. Research on non‑invasive industrial equipment monitoring methods[J]. Journal of Electric Power Science and Technology,2024,39(5):112-117.

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  • Online: December 02,2024
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