By Topic

A multiple objective evolutionary approach for the design and selection of load control strategies

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

3 Author(s)
A. Gomes ; Dept. of Electr. Eng. & Comput., Univ. of Coimbra, Portugal ; C. H. Antunes ; A. G. Martins

Load management activities, even in scenarios characterized by an unbundled electricity market, maintain their potential attractiveness, not just due to operational issues but also because of potential economic benefits. However, multiple incommensurate and conflicting objectives are at stake in the design and selection of load management actions. Evolutionary algorithms, working with a population of potential solutions, are well suited for such multiobjective optimization problems of combinatorial nature. Moreover, when applied to load management programs, they allow both for the design and the selection of control strategies. The combined use of this type of algorithms and adequate load models allows some of the concerns these actions may arise, such as the payback phenomenon, to be taken into account. In the proposed approach, the effects of load control strategies are computed at different demand aggregation levels. This capability and the explicit consideration of multiple objective functions in the mathematical model enable the proposed approach to be used in different possible scenarios related with power systems structure and by different entities.

Published in:

IEEE Transactions on Power Systems  (Volume:19 ,  Issue: 2 )