基于粒子群优化的PI预测函数励磁控制器
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摘要
将PI控制器与预测函数算法相结合,利用粒子群算法优化整定其参数,提出了一种新型的基于粒子群优化的PI预测函数励磁控制器的设计方法。该算法具有广义上的PI控制器的两个参数,同时具有预测函数算法对模型要求低和上升速度快等优点,同时利用粒子群算法优化PI参数,使其克服了传统PI控制器参数难以整定的缺点。仿真结果表明该算法不仅能有效的解决机端电压偏移问题,还能有效的抑制电网低频振荡,且具有较好的鲁棒性,同时PI参数整定方便,为电力系统稳定性控制提供了一种新型有效的方法。
It proposes a new design of excitation controller of PI prediction function,combining the algorithm of PI and the algorithm of Prediction Function,and tuning parameters based on PSO. The improved algorithm does not only have the two parameters of the PI controller in a broad sense,but also have the advantages of lower degree of precision to parametric models and rising fast,etc.,at the same time using PSO to tune two parameters of PI. This improved algorithm also overcome the shortage of difficult to tuning PI controller parameters. The simulation results indicate that this algorithm can solve the problem of terminal voltage offset effectively and control the low frequency oscillation of power grid effectively,have better robustness,and to tune parameters,providing a new effective method of the control of the stability of power system.
It proposes a new design of excitation controller of PI prediction function,combining the algorithm of PI and the algorithm of Prediction Function,and tuning parameters based on PSO. The improved algorithm does not only have the two parameters of the PI controller in a broad sense,but also have the advantages of lower degree of precision to parametric models and rising fast,etc.,at the same time using PSO to tune two parameters of PI. This improved algorithm also overcome the shortage of difficult to tuning PI controller parameters. The simulation results indicate that this algorithm can solve the problem of terminal voltage offset effectively and control the low frequency oscillation of power grid effectively,have better robustness,and to tune parameters,providing a new effective method of the control of the stability of power system.
引文
[1]陆继明,刘伯康,毛承雄,等.基于机电配置的线性最优励磁控制设计方法[J].大电机技术,2009,(1):58-63.
[2]刘辉,李啸骢,韦化,等.基于目标状态方程的非线性预测励磁控制器的设计[J].中国电机工程学报,2005,25(17):28-31.
[3]Giuseppe F,Mario R.Nonlinear control design for excitation controller and power system stabilizer[J].Control Engineering Practice,2011,19(3):243-251.
[4]姚舜才,潘宏侠.粒子群优化同步电机分数阶鲁棒励磁控制器[J].中国电机工程学报,2010,30(21):91-97.
[5]张秀华,张庆灵,靖新.具有鲁棒性分代数模型的励磁控制器模型[J].电机与控制学报,2005,9(3):229-234.
[6]郭伟,倪家健,李涛,等.基于时域的分数阶PID预测函数励磁控制器[J].仪器仪表学报,2012,32(11):2461-2467.
[7]Richalet J.Predictive Functonal control-application to fast and accurate robots[C]//Proc of the 10th IFAC World Congress.Oxford:Pergamon Press,1987:251-258.
[8]郭敬,赵克定,郭治富.液压仿真转台的PFC-PID串级控制[J].航空学报,2008,29(5):1395-1400.
[9]夏泽中.张光明.预测函数控制及其在伺服系统中的仿真研究[J].中国电机工程学报,2005,25(14):130-134.
[10]金丰,项福禄,天罡,等.主汽温串级控制系统PSO优化方法的工程实践[J].现代电力,2010,27(4):78-82.
[11]IEEE Power Engineering Society.IEEE standard definition for excitation systems for synchronous machines IEEE std 421.1[S].New York,NY,USA:Energy Development and Power Generation Committee,2007.
[2]刘辉,李啸骢,韦化,等.基于目标状态方程的非线性预测励磁控制器的设计[J].中国电机工程学报,2005,25(17):28-31.
[3]Giuseppe F,Mario R.Nonlinear control design for excitation controller and power system stabilizer[J].Control Engineering Practice,2011,19(3):243-251.
[4]姚舜才,潘宏侠.粒子群优化同步电机分数阶鲁棒励磁控制器[J].中国电机工程学报,2010,30(21):91-97.
[5]张秀华,张庆灵,靖新.具有鲁棒性分代数模型的励磁控制器模型[J].电机与控制学报,2005,9(3):229-234.
[6]郭伟,倪家健,李涛,等.基于时域的分数阶PID预测函数励磁控制器[J].仪器仪表学报,2012,32(11):2461-2467.
[7]Richalet J.Predictive Functonal control-application to fast and accurate robots[C]//Proc of the 10th IFAC World Congress.Oxford:Pergamon Press,1987:251-258.
[8]郭敬,赵克定,郭治富.液压仿真转台的PFC-PID串级控制[J].航空学报,2008,29(5):1395-1400.
[9]夏泽中.张光明.预测函数控制及其在伺服系统中的仿真研究[J].中国电机工程学报,2005,25(14):130-134.
[10]金丰,项福禄,天罡,等.主汽温串级控制系统PSO优化方法的工程实践[J].现代电力,2010,27(4):78-82.
[11]IEEE Power Engineering Society.IEEE standard definition for excitation systems for synchronous machines IEEE std 421.1[S].New York,NY,USA:Energy Development and Power Generation Committee,2007.