摘要
提出了模糊神经网络电力系统稳定器与高压直流调制器的自适应在线协调控制策略,改善了系统在大扰动后的动态品质。该协调控制策略采用辨识器预测各个发电机在下一个采样点的角速度变化,并以其为变量构造目标函数对模糊控制器进行在线训练,使功角摇摆过程中各发电机间角速度差值的平方和最小。算法用于三区域双馈入直流系统的在线协调控制。仿真结果表明,自适应在线协调策略使系统在不同的运行状态和不同的故障下均具有良好的暂态稳定性,抑制了故障后系统的振荡。
Based on adaptive-network-based fuzzy inference system （ANFIS） an adaptive on-line coordinated control strategy for power system stabilizer （PSS） and HVDC modulation controllers is proposed to improve post-large disturbance dynamic performance of power system. By use of identifier the proposed control strategy forecasts the variation of angular velocity of each generation set at next sampling point, and taking the variations of angular velocity as variables the objective function is constructed to perform on-line coordination of fuzzy controller to make the sum of squares of angular velocity differences among generation sets minimal. The proposed algorithm is applied in on-line coordinated control for doubly-fed HVDC system covering three regions. Simulation results show that using the proposed adaptive on-line coordinated control strategy, power system possesses good transient stability under different accidents and the oscillation of post-fault power system can be suppressed effectively.
出处
《电网技术》
EI
CSCD
北大核心
2009年第6期29-32,49,共5页
Power System Technology
基金
国家自然科学基金重点资助项目(50337010)~~
关键词
在线协调
模糊神经网络
系统振荡
暂态稳定
on-line coordination
fuzzy neural network power system oscillation
transient stability
