Improved non‐intrusive identification technique of electrical appliances for a smart residential system. Issue 5 (28th February 2019)

• Record Type: Journal Article
• Authors: Ghosh, Soumyajit; Chatterjee, Arunava; Chatterjee, Debashis
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 5(2019)
• Page Start: 695
• Page End: 702
• Publication Date: 2019-02-28
• Subjects: building management systems -- domestic appliances -- passive filters -- power system measurement -- energy conservation -- power engineering computing -- load management -- power consumption -- smart power grids; nonintrusive identification technique -- electrical appliances -- smart residential system -- electrical load monitoring techniques -- consumer site -- electricity costs -- smart grid technology -- advanced load monitoring applications -- efficient consumption -- electrical energy -- nonintrusive load monitoring -- moderately new practice -- power consumption -- individual appliances -- aggregated household -- improved NILM technique -- shunt passive filter -- residential complex -- single household -- different loads -- consumer end; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.5475
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Electrical load monitoring techniques are valuable to consumer site for energy saving, permitting reduction in electricity costs. Nowadays, smart grid technology incorporates advanced load monitoring applications, enabling efficient consumption of electrical energy. Non‐intrusive load monitoring (NILM) is a moderately new practice to identify the power consumption of individual appliances of a consumer from the aggregated household at a single point of measurement. In this study, an improved NILM technique is proposed by using a shunt passive filter installed at the source side of any residential complex. The proposed method can be realised in two steps. The first step is to determine the harmonic impedance at the load side for different groups of loads for a single household. The second step is to implement a fuzzy rule‐based approach for identification of different loads at the consumer end. Suitable simulations backed by experiments are demonstrated in this study to validate the viability of the proposed methodology.