A Chaos Cloud Particle Swarm Algorithm Based Available Transfer Capability

Su Hongsheng, qi ying


A mathematical model for ATC based on optimal power flow was built under the static security constraints, where the maximum of all load nodes in receiving area was considered as aim function. In view of the defects of slow convergence and low accuracy in ATC optimization algorithms, a chaos cloud particle swarm optimization algorithm based on golden section criteria (CCGPSO) was proposed. This method classified the particle swarm into three populations based on golden section judge principles according to fitness level. They are called chaos cloud particles, cloud particles and standard particles respectively. Each population was operated by different processing operations and updating modes. Comparing with other methods, the numerical simulation results of CCGPSO in IEEE-30 bus system demonstrate the higher efficiency and validity in ATC calculation. It is more suitable for solving the large-scale non-linear multi-constraint engineering practical problems.

DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.3368



available transfer capability;particle swarm optimization

Full Text:



  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License