中国电机工程学报
中國電機工程學報
중국전궤공정학보
ZHONGGUO DIANJI GONGCHENG XUEBAO
2013年
22期
61-67
,共7页
电力系统%非线性预测控制%励磁控制%平衡降阶%经验Gramians
電力繫統%非線性預測控製%勵磁控製%平衡降階%經驗Gramians
전력계통%비선성예측공제%려자공제%평형강계%경험Gramians
power systems%nonlinear predictive control%excitation control%balanced reduction%empirical Gramians
将预测控制与模型降阶技术相结合提出一种基于平衡降阶模型的多机电力系统非线性励磁预测控制方法，以解决最优励磁控制和传统比例积分微分励磁控制无法考虑系统复杂状态和控制输入约束的问题，并且降低非线性励磁预测控制高阶动态模型数值计算的复杂性。首先，利用经验Gramians 平衡降阶原理，对电力系统非线性动态模型进行降阶，以降低动态模型的维数。然后，建立基于降阶模型的励磁预测控制模型。以系统输入输出最小二乘残差向量为优化目标，以降阶动态模型作为等约束条件，以输出量、控制量的变化范围作为不等约束条件。利用内点法求解优化问题。最后，利用一个四机电力系统验证该预测控制方法的有效性，仿真结果表明：基于平衡降阶模型的多机电力系统非线性励磁预测控制器能够大大缩短优化计算时间，维持机端电压在定值附近，提高系统的稳定性。
將預測控製與模型降階技術相結閤提齣一種基于平衡降階模型的多機電力繫統非線性勵磁預測控製方法，以解決最優勵磁控製和傳統比例積分微分勵磁控製無法攷慮繫統複雜狀態和控製輸入約束的問題，併且降低非線性勵磁預測控製高階動態模型數值計算的複雜性。首先，利用經驗Gramians 平衡降階原理，對電力繫統非線性動態模型進行降階，以降低動態模型的維數。然後，建立基于降階模型的勵磁預測控製模型。以繫統輸入輸齣最小二乘殘差嚮量為優化目標，以降階動態模型作為等約束條件，以輸齣量、控製量的變化範圍作為不等約束條件。利用內點法求解優化問題。最後，利用一箇四機電力繫統驗證該預測控製方法的有效性，倣真結果錶明：基于平衡降階模型的多機電力繫統非線性勵磁預測控製器能夠大大縮短優化計算時間，維持機耑電壓在定值附近，提高繫統的穩定性。
장예측공제여모형강계기술상결합제출일충기우평형강계모형적다궤전력계통비선성려자예측공제방법，이해결최우려자공제화전통비례적분미분려자공제무법고필계통복잡상태화공제수입약속적문제，병차강저비선성려자예측공제고계동태모형수치계산적복잡성。수선，이용경험Gramians 평형강계원리，대전력계통비선성동태모형진행강계，이강저동태모형적유수。연후，건립기우강계모형적려자예측공제모형。이계통수입수출최소이승잔차향량위우화목표，이강계동태모형작위등약속조건，이수출량、공제량적변화범위작위불등약속조건。이용내점법구해우화문제。최후，이용일개사궤전력계통험증해예측공제방법적유효성，방진결과표명：기우평형강계모형적다궤전력계통비선성려자예측공제기능구대대축단우화계산시간，유지궤단전압재정치부근，제고계통적은정성。
This paper presented a multi-machine power system nonlinear excitation predictive control method which combined model predictive control and model reduction technology in order to tackle the problem that the optimal excitation control and the traditional proportional-integral-derivative (PID) excitation control could not consider the constraint of states and input of the system, and to reduce the complexity of the numerical calculation of high order dynamic model in nonlinear excitation predictive control. First, The theory of empirical Gramians balanced reduction was used to reduce the orders of power system nonlinear dynamic model to save the computing time of open-loop optimization of model predictive control. Then, it used the least-square residual of system input and output as the objection function, using reduced dynamic model as equivalent constraint and the change limits of system output and control input as unequivalent constrain to establish the excitation predictive control model based on reduced model. Next, the interior-point method was used to solve the optimal problem meanwhile to realize multi-step prediction. Finally, we took advantage of a four-machine power system to verify the effectiveness of the predictive control method. The simulation results show that nonlinear excitation predictive control method based on balanced reduced model for the multi-machine power systems can greatly shorten the optimization time, meanwhile maintain the voltage of generator terminals within the set points and improve the stability of power system.
