Transient event detection in spectral envelope estimates for nonintrusive load monitoring

  title={Transient event detection in spectral envelope estimates for nonintrusive load monitoring},
  author={Steven B. Leeb and Steven R. Shaw and James L. Kirtley},
  journal={IEEE Transactions on Power Delivery},
This paper describes the theoretical foundation and prototype implementation of a power system transient event detector for use in a nonintrusive load monitor (NILM). The NILM determines the operating schedule of the major electrical loads in a building from measurements made at the electric utility service entry. The transient event detector extends the applicability of the NILM to challenging commercial and industrial sites. A spectral preprocessor for use in the transient event detector is… 
Transient event detection for nonintrusive load monitoring and demand side management using voltage distortion
This paper describes a simple system that can be used for autonomous demand-side management in a load site such as a home or commercial facility. The system identifies the operation of individual
Nonintrusive Load Monitoring and Diagnostics in Power Systems
A transient event classification scheme, system identification techniques, and implementation for use in nonintrusive load monitoring form a system that can determine the operating schedule and find parameters of physical models of loads that are connected to an AC or DC power distribution system.
Instrumentation for High Performance Nonintrusive Electrical Load Monitoring
This paper reviews the design and implementation of hardware and software tools for nonintrusive electrical load monitoring. Estimates of spectral content in measured waveforms can be used to
Spectral envelope estimation for transient event detection
A Nonintursive Load Monitor (NILM) is a device that determines the operating schedule of electric loads by properly locating and identifying transient events in the spectral envelopes of the current
A New Measurement Method for Power Signatures of Nonintrusive Demand Monitoring and Load Identification
Artificial neural networks, in combination with turn-on transient energy analysis, are used to improve recognition accuracy and computational speed of NILM results.
A time-frequency approach for event detection in non-intrusive load monitoring
This paper develops a joint time-frequency approach for appliance event detection based on the time varying power signals obtained from the measured aggregated current and voltage waveforms and demonstrates the superior performance of the proposed algorithm compared to the conventional generalized likelihood ratio detector.
System identification techniques and modeling for nonintrusive load diagnostics
This thesis addresses the requirements of a system that can detect on/off transients and identify physical parameters of loads connected to a power distribution network. The thesis emphasizes three
Power signature analysis
Nonintrusive load monitoring (NILM) can determine operating schedule of electrical loads in a target system from measurements made at a centralized location, such as the electric utility service
A review of nonintrusive load monitoring and its application in commercial building
  • Yan Liu, Mei Chen
  • Engineering
    The 4th Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent
  • 2014
Nonintrusive load monitoring (NILM) has been developed for decades in load monitoring and disaggregation. Methods of digital signal processing and statistical modeling have been applied in detecting
Improvements to the nonintrusive load monitor
This thesis is a number of improvements to the Nonintrusive Load Monitor. First a preprocessor, the NILM stage that emphasizes the features of power data useful for load classification, was


A conjoint pattern recognition approach to nonintrusive load monitoring
A new syntactic grammar is created that extends minimum information techniques into many possible applications that can be viewed in a multiscale framework and is implemented on an advanced digital signal processor that serves as a prototype for a commercial NILM.
Using appliance signatures for monitoring residential loads at meter panel level
The author presents an initial approach to identifying electrical household appliances strictly by analyzing variations in current-voltage signals at the meter panel level. The study shows that local
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A nonintrusive appliance load monitor that determines the energy consumption of individual appliances turning on and off in an electric load, based on detailed analysis of the current and voltage of
Generalized averaging method for power conversion circuits
The method of state-space averaging has been successfully applied to pulse-width modulated power converters, but has its limitations with switched circuits that do not satisfy a small-ripple
Detection of abrupt changes in signals and dynamical systems : Some statistical aspects
The aim of this paper is to present some points of this detection problem, with a particular emphasis on the statistical aspects, leaving out the system theoretic aspects, which are of great importance in the control context, or, more generally, in the case of multichannel signal processing.
Circuits, Signals, and Systems
These twenty lectures have been developed and refined by Professor Siebert during the more than two decades he has been teaching introductory Signals and Systems courses at MIT and are designed to familiarize students with the properties of a fundamental set of analytical tools.
Multirate digital filters, filter banks, polyphase networks, and applications: a tutorial
Several applications of the polyphase concept are described, including subband coding of waveforms, voice privacy systems, integral and fractional sampling rate conversion, digital crossover networks, and multirate coding of narrowband filter coefficients.
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
  • S. Mallat
  • Computer Science
    IEEE Trans. Pattern Anal. Mach. Intell.
  • 1989
It is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2/Sup j/ can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.