By Topic

Modeling Aluminum Smelter Plants Using Sliced Inverse Regression With a View Towards Load Flexibility

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

6 Author(s)
Molina-Garciá, A. ; Dept. of Electr. Eng., Univ. Politec. de Cartagena, Cartagena, Spain ; Kessler, M. ; Bueso, M.C. ; Fuentes, J.A.
more authors

This paper describes the application of sliced inverse regression to model the electrochemical process of aluminum smelter plants. Real data measurements obtained during several years in a Spanish industrial environment are used to illustrate the main dependencies between parameters. Nonlinear relations between the output variables and relevant linear combinations of input variables are deduced. An exploratory statistical analysis is also presented, checking for correlations and possible linear dependencies. The developed model is used to analyze the range of electrical power demand variations as a consequence of modifications in chemical and electrical parameters. An example is described maintaining constant the aluminum production. The results can be considered for future load flexibility programs, which might include aluminum smelter plants as a flexible industrial customer.

Published in:

Power Systems, IEEE Transactions on  (Volume:26 ,  Issue: 1 )