By Topic

AI based Economic Load Dispatch incorporating wind power penetration

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)
Kumar, A.N. ; Dept. of Electr. & Electron. Eng., SRM Univ., Kancheepuram, India ; Suchitra, D.

Economic Load Dispatch (ELD) is one of the most important problems to be solved in the operation and planning of a power system. Its objective is to schedule the power generation properly in order to minimize the total operational cost. Renewable energy resources such as wind power have significant attention in recent years in power system field. It reduces fuel consumption and also benefits in curbing emission. But wind power penetration into conventional systems due to its intermittent nature has some implications like security concerns. Thus a reasonable trade off is required between system risk and operational cost. In this paper a bi-objective economic dispatch problem considering wind power penetration is formulated. A fuzzy membership function is used to represent the dispatch of wind power into the conventional system. A particle swarm optimization algorithm, Genetic algorithm and a bacteria-foraging technique are adopted to develop a dispatch scheme compromising both the economic and security requirements. The results of all these 3 proposed techniques are compared. Numerical analyses are reported based on a typical IEEE-30-bus with six-generator test power system to show the validity and applicability of the proposed approaches.

Published in:

Electrical Engineering and Informatics (ICEEI), 2011 International Conference on

Date of Conference:

17-19 July 2011