基于多目标混合进化算法的多台TCSC控制器协调设计

将多台可控串联补偿器(TCSC)之间的协调运行问题转化为多目标优化问题,详细介绍了一种基于进化规划和粒子群优的多目标混合进化算法(MOEPPSO),提出了基于MOEPPSO的协调控制器设计方法.采用多目标混合进化算法优化控制器参数,得到一组Pareto参数解集,为运行人员提供更丰富、准确的信息.在装有两台TCSC的IEEE典型四机两区域系统研究实例中,非线性时域仿真验证了所提方法的有效性.与单独设计控制器的方法相比较,所提方法能够更好地提高互联系统的稳定性.

Application of Multi-Objective Hybrid Evolutionary Algorithm to Coordinate Multiple TCSC Controllers in Power System

A novel multi-objective hybrid evolutionary algorithm based on Evolutionary Programming(EP) and Particle Swarm Optimization(PSO),named MOEPPSO,is presented to coordinate multiple Thyristor Controlled Series Compensator(TCSC) devices in power system.The coordinate design problem of TCSCs is formulated as a multi-objective optimization problem,in which the system response is optimized by minimizing several system behavior measure criterions.Then,MOEPPSO is employed to search optimal controller parameters.Design of the multi-objective optimization aims to find out the Pareto optimal solution which is a set of possible optimal solutions for controller parameters.The proposed approach has been applied to a typical IEEE 4-machine 11-bus system with two TCSCs.The simulation results validate the proposed approach.Besides,compared with separate design of the controllers,the better performance of the system is achieved.