The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage. Energy disaggregation is intended to separate the total power consumption into specific appliance loads, which can be achieved by applying Non-Intrusive Load Monitoring (NILM) techniques with a minimum invasion of privacy. NILM techniques are becoming more and more widespread in recent years, as a consequence of the interest companies and consumers have in efficient energy consumption and management. This work presents a detailed review of NILM methods, focusing particularly on recent proposals and their applications, particularly in the areas of Home Energy Management Systems (HEMS) and Ambient Assisted Living (AAL), where the ability to determine the on/off status of certain devices can provide key information for making further decisions. As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics.

NILM Techniques for Intelligent Home Energy Management and Ambient Assisted Living: A Review

Energy management using non-intrusive load monitoring techniques - State-of-the-art and future research directions

Robust event-based non-intrusive appliance recognition using multi-scale wavelet packet tree and ensemble bagging tree

Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction

Optimal placement of phasor measurement unit in distribution networks considering the changes in topology

Implementation of a robust real-time non-intrusive load monitoring solution

In this paper, design, implementation and analysis of a new underwater multiple input multiple output visible light communication (VLC) system is presented. The VLC system consists of a transmitter, water channel, and a receiver. The transmitter is made out of light emitting diodes (LEDs'), while a camera based architecture is adopted at the receiver. We present a possible system design and characterize the channel for symbol detection. At the training phase, the underwater channel is characterized using a channel matrix, which presents the relationship between the multiple input LED states and the pixel values of the frame in the video stream obtained from the camera receiver. Thereafter the inverse model of the system is obtained. Then symbol detection is carried out by analysing consecutive frames of the real-time video stream. Also we analyse the performance of this system in terms of the bit error rate (BER), bit rate, behaviour of the system at different transmission distances, and present results using the experimental setup. From our study, it was realised that, reasonable BER performance can be achieved using the proposed system designs at low and medium transmission distances compared to most of the existing underwater communication systems.

Design and analysis of an under water visible light MIMO communication system with a camera receiver

Availability of large quantities of residential electrical consumption data is bringing considerable attention towards load monitoring, load forecasting, load disaggregation and demand response. Load modelling is the first and most essential step in achieving all the above said tasks. Even though many appliance modelling schemes are presented in the literature, no considerably influential work has been done on modelling appliances under voltage fluctuating environment. Motivated by this fact, we present the design and analysis of a Volterra based appliance modelling scheme which can be used in a voltage fluctuating environment. Principles of Volterra filter, least mean square algorithm for Volterra filter coefficient approximation and applicability of Volterra filter for appliance modelling are discussed. Further, a case study is presented to validate and identify the performance of the model using a data set obtained from a real household. Obtained results show that, Volterra filter can be utilized as an efficient tool for appliance modelling in a supply voltage fluctuating environment. Finally, how Volterra filter modelling can be extended to achieve the non intrusive load monitoring task is discussed.

Muhammed Akram

Papers

Implementation of a robust real-time non-intrusive load monitoring solution

Design and analysis of an under water visible light MIMO communication system with a camera receiver

Second Order Volterra Filter for Appliance Modelling