Cart (Loading....) | Create Account
Close category search window
 

Reference prediction in optimal control of smart-grid with asynchronous RDG's

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

2 Author(s)
Jayaweera, S.K. ; Dept. of Electr. & Comput. Eng., Univ. of New Mexico, Albuquerque, NM, USA ; Ding Li

This paper proposes an efficient interaction infrastructure between the Utility and distributed customers in a future smart grid. Detailed steps of a complete interaction cycle are presented, including demand response (DR), distributed customer mode-switching decision making and stochastic tracking control for the Utility-maintained conventional generation facilities. We further extend our previous work by considering the realistic scenario of asynchronous load demand signals from different customer loads. To compensate for different delays seen by different customer/load signals, we design a Kalman filter (KF) based prediction scheme to construct the correct reference signal. The prediction problem is essentially transformed into a problem which can be solved by the standard Kalman filtering technique. Due to the system linearity and the fact that different customer/loads are decoupled with each other, we show that the centralized reference prediction can equivalently be implemented distributively, where a distributed Kalman filter is implemented for each of the delayed load signal. In addition, we establish that the separation of the reference prediction and tracking design is still optimal for the original objective function. Simulation results are presented to show the performances of the proposed prediction and tracking schemes.

Published in:

Intelligent and Advanced Systems (ICIAS), 2012 4th International Conference on  (Volume:2 )

Date of Conference:

12-14 June 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.