摘要
为指导PSS参数整定现场实验,提高电网动态安全稳定水平,对某网B厂新投机组PSS参数进行预整定。基于粒子群算法,动态调整惯性权重和加速因子自适应变化,并引入随机变异环节,以提高粒子寻优性能,从而提出适用于PSS参数预整定的自适应加速粒子群算法(SAPSO)。建立单机无穷大和两机协调预整定仿真模型,利用SAPSO算法,对某网新投PSS参数进行单机和两机协调预整定。时域仿真和现场试验表明预整定参数阻尼效果更好,对新投机组PSS参数采用预整定方法有效可行。
In order to guide field experiment of PSS parame- ters tuning and improve the dynamic security and stability level of power system, the PSS parameters of new invested units in B power plant was pre-tuned. To improve the opti- mization performance of PSO, a novel Self-adaptive Accel- eration PSO （SAPSO） algorithm is proposed, which dynami- cally adjusts inertia weight and acceleration factor, and adds random mutation factor to searching process. Time domain simulations of single-machine infinity system and two-ma- chine coordinated pre-tune system are studied and investiga- ted. PSS parameter of new invested units is pre-tuned with the SAPSO algorithm under single and coordination mode. The results of simulation and field experiment indicate that the low-frequency oscillation of power system is effectively suppressed and the pre-tune method for PSS parameter of new invested units is effective and feasible.
出处
《现代电力》
北大核心
2014年第4期60-65,共6页
Modern Electric Power
