By Topic

Chaotic Particle Swarm Optimization Algorithm with Niche and its Application in Cascade Hydropower Reservoirs Operation

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

3 Author(s)
Huang Xiaofeng ; Sch. of Renewable Energy, North China Electr. Power Univ., Beijing, China ; Ji Changming ; Pei Zheyi

Niche evolutionary strategy and chaotic searching were introduced into PSO, called as chaotic particle swarm optimization algorithm with niche (CNPSO) in this thesis. Restricted competition selection method was used to establish niche, in which each species excluded each other and dynamically formed their own searching spaces, effectively maintain the diversity of the species, so as to avoid local convergence. The chaotic searching further improved the global optimization searching precision. CNPSO was programmed to do the optimization regulation of 14 cascade hydropower stations with giant reservoirs by 48-year run-off series. With the result showing that CNPSO is highly efficient in optimization searching, capable of solving the complicated multi dimensional, strong-constraint, multi-states, multi-stages and non-linear problems such as optimization regulation of cascade hydropower stations with giant reservoirs.

Published in:

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on  (Volume:1 )

Date of Conference:

7-8 Nov. 2009