By Topic

Parallel Load Schedule Optimization With Renewable Distributed Generators in Smart Grids

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
$33 $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)
Peng Yang ; Preston M. Green Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA ; Phani Chavali ; Elad Gilboa ; Arye Nehorai

We propose a framework for demand response in smart grids that integrates renewable distributed generators (DGs). In this model, some users have DGs and can generate part of their electricity. They can also sell extra generation to the utility company. The goal is to optimize the load schedule of users to minimize the utility company's cost and user payments, while considering user satisfaction. We employ a parallel autonomous optimization scheme, where each user requires only the knowledge of the aggregated load of other users, instead of the load profiles of individual users. All the users can execute distributed optimization simultaneously. The distributed optimization is coordinated through a soft constraint on changes of load schedules between iterations. Numerical examples show that our method can significantly reduce the peak-hour load and costs to the utility and users. Since the autonomous user optimization is executed in parallel, our method also significantly decreases the computation time and communication costs.

Published in:

IEEE Transactions on Smart Grid  (Volume:4 ,  Issue: 3 )