By Topic

Modeling and weather-normalization of whole-house metered data for residential end-use load shape estimation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)

A method is presented for modeling load shapes in the residential sector by using hourly whole-house metered data and temperature. Individual household-level load data are analyzed to achieve data smoothing (noise rejection) and compression (in the ratio of approximately 150:1), and to disaggregate the weather-dependent and weather-independent components of the load. The weather-independent (lifestyle) component is modeled as a weighted sum of orthogonal functions (primarily sinusoids and boxcars), while the weather-dependent component is modeled as a nonlinear dynamic system based on thermodynamic principles. Numerical examples show efficient representation of data and good model fit

Published in:

Power Systems, IEEE Transactions on  (Volume:3 ,  Issue: 1 )