|Advisor:||Dr. Yong Fu|
Optimization techniques are widely applied in the power system planning and operation to achieve more efficient and reliable power supply. With the introduction of new technologies, the complexity of today’s power system is significantly increased. Intelligent optimization techniques, such as Particle Swarm Optimization (PSO), can efficiently deal with the new challenges compared to conventional optimization techniques.
This thesis presents applications of discrete PSO in two specific environments. The first one is for day-ahead optimal scheduling of the reconfigurable gird with smart resources. The second one is a two-step method for rapid reconfiguration of shipboard power system. Effective techniques, such as graph theory, optimal power flow and heuristic mutation, are employed to make the PSO algorithm more suitable to application environments and achieve better performance.