The Available Transfer Capability Based on a Chaos Cloud Particle Swarm Algorithm

An optimal power flow model was established for Available Transfer Capability (ATC) under the static security constraints. The maximum active power of all load nodes in receiving area was taken as objective function. To aim at the low accuracy and premature convergent in ATC optimization algorithms, the chaos cloud particle swarm algorithm based on golden section evaluation criteria (CCGPSO) was proposed. This method divided the particle swarm into standard particle, chaos cloud particle and cloud particle, which used the golden section judge principle according to fitness level. Every sub-swarm particle had respective different algorithm operations. The ATC calculated by the proposed algorithm was simulated in the IEEE-30 node test system. Results are compared with the cloud PSO and chaos PSO algorithm. The simulation results verify that the CCGPSO is greatly superior to the cloud PSO and chaos PSO in terms of accuracy and speed. It is more suitable for solving such large-scale non-linear multi-constraint optimization problems.