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access icon free Improved non-intrusive identification technique of electrical appliances for a smart residential system

© The Institution of Engineering and Technology
Received 07/05/2018, Accepted 04/12/2018, Revised 12/11/2018, Published 19/12/2018

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.

Inspec keywords: domestic appliances; power consumption; power system measurement; load management; energy conservation; building management systems; passive filters; smart power grids; power engineering computing

Other keywords: aggregated household; electrical energy; smart grid technology; electricity costs; consumer end; individual appliances; electrical appliances; electrical load monitoring techniques; consumer site; single household; efficient consumption; smart residential system; advanced load monitoring applications; nonintrusive identification technique; nonintrusive load monitoring; improved NILM technique; shunt passive filter; moderately new practice; different loads; residential complex; power consumption

Subjects: Power system management, operation and economics; Power system measurement and metering; Power engineering computing; Domestic appliances; Optimisation techniques

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