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为了对直流输电系统的PI控制器进行优化设计,提出了一种自适应粒子群优化(APSO)算法以克服传统粒子群优化(PSO)算法易于陷入局部极值、使算法早熟的缺陷。在APSO算法中粒子群寻优计算时,每个粒子的惯性权重系数根据该粒子当前的适应值而自适应地变化,使得适应值好的粒子趋向于做当前最优解附近的精细搜索,适应值差的粒子则以较大步长对可行域进行全局粗略探测以便有机会发现新的更好的解,从而使得整个群体保持了多样性和良好的收敛特性。基于APSO算法,给出了一套系统化的直流输电PI控制器优化设计方法。通过对CIGRE HVDC Benchmark Model的仿真计算,以及与“稳定边界法”设计结果的比较、分析,证明了所提出的设计方法的可行性和有效性。
In order to optimize the PI controller of DC transmission system, an Adaptive Particle Swarm Optimization (APSO) algorithm is proposed to overcome the defect that the traditional Particle Swarm Optimization (PSO) algorithm is apt to fall into local extremum and make the algorithm premature. In the APSO algorithm, the inertia weight coefficient of each particle changes adaptively according to the current fitness value of the particle, so that particles with good fitness value tend to do fine search around the current optimal solution and adapt to The poorly-sized particles then globally rough measure the feasible region with larger steps in order to have the opportunity to find new and better solutions, thus keeping the whole population diverse and with good convergence. Based on the APSO algorithm, a systematic optimization design method of PI controller for DC transmission is given. Through the simulation calculation of CIGRE HVDC Benchmark Model and the comparison with the design results of “stable boundary method ”, the feasibility and effectiveness of the proposed design method are proved.