By Topic

Optimization of a typical biomass fueled power plant using Genetic algorithm and binary particle swarm optimization

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)

Over thousands tons of animal manures are produced in Iran. The major animal manures producers are located in central regions. Animal manures collection is an autochthonous and important renewable energy sources that in most cases are released in nature by ranchers. In this paper, a typical animal manure producer region is considered and optimal location and size of a typical biomass fueled power plant is determined. Genetic algorithm (GA) is used as the major approach of determination and effectively this approach will make possible to determine the optimal location, biomass supply area and power plant size that offer the best profitability for investor. Binary particle swarm optimization algorithm is also used as the second approach of optimization and eventually results obtained from both algorithm are compared. In this work we use profitability index (PI) as the fitness function of Genetic algorithm and the point with the maximum PI is selected.

Published in:

Electrical Power Distribution Networks (EPDC), 2012 Proceedings of 17th Conference on

Date of Conference:

2-3 May 2012