摘要
提出了一种新的进化计算方法——差分进化粒子群优化算法(DEPSO)进行多机电力系统稳定器(PSS)的参数优化。该方法以系统正常运行方式下的最小机电振荡模式阻尼比为目标函数,将PSS的参数优化问题等效为非线性、非解析、非突性的连续实域空间的函数优化问题。基于传统的差分进化策略,引入种群中的最优个体信息和方向信息,提出了一种全新的差分进化策略。仿真结果表明,该算法搜索空间广,收敛速度快,优化效果好。
A new evolution computation method-Differential Evolution Based Particle Swarm Optimization（DEBPSO） used to optimize the parameters of multi-machine Power System Stabilizers （PSSs）, is presented in this paper. By this approach, with an objective function for the minimal damp ratio of all electromechanical modes under conventional system operating condition, the parameter optimization of PSS is referred as a matter of nonlinear, non differential and non convex function optimization over a continuous real-world space. A new differential evolution strategy considering the optimal individual and directional information, based on the conventional differential evolution strategy, is proposed in order to accelerate the convergence of this algorithm. The simulation in 4-machine system indicates that the proposed algorithm has extensive search space, faster convergence speed and better optimization effect in comparison with the conventional optimization algorithm.
出处
《水电能源科学》
2008年第2期156-159,204,共5页
Water Resources and Power
基金
国家自然科学基金重大资助项目(90612018)
上海电力公司重大基金资助项目(F020303)
