CAJ | 학술논문

介绍一种基于平衡降阶理论的电力系统多机励磁预测控制方法。为减少开环优化计算时间，利用平衡降阶理论对电力系统多机线性模型进行降阶，降低预测模型维数。以预测步长内系统输出和控制量的偏差最小为优化控制指标，以模型降阶微分方程、状态和输入为约束条件，利用改进内点法求解优化问题。从降低模型阶数和改进优化算法两方面降低计算复杂度，加快在线计算速度，适用于电力系统大规模励磁控制。对某50机系统进行仿真验证该方法的有效性，仿真结果表明：基于平衡降阶模型的励磁预测控制器可极大降低优化计算时间，提高系统的稳定性。
개소일충기우평형강계이론적전력계통다궤려자예측공제방법。위감소개배우화계산시간，이용평형강계이론대전력계통다궤선성모형진행강계，강저예측모형유수。이예측보장내계통수출화공제량적편차최소위우화공제지표，이모형강계미분방정、상태화수입위약속조건，이용개진내점법구해우화문제。종강저모형계수화개진우화산법량방면강저계산복잡도，가쾌재선계산속도，괄용우전력계통대규모려자공제。대모50궤계통진행방진험증해방법적유효성，방진결과표명：기우평형강계모형적려자예측공제기가겁대강저우화계산시간，제고계통적은정성。
An excitation predictive control method for multi-machine power system based on balanced reduction model is presented. In order to shorten the open-loop optimization calculating time of model predictive control (MPC), the theory of balanced reduction is used to reduce the orders of multi-machine power system linear dynamic model. It uses the least-square residual of system output and control variables as the objection function, using reduced dynamic model and the change limits of system states and inputs as constraints. Then, the improved interior-point method is used to solve the optimal problem. The optimization calculation of MPC can be sped up from two aspects of the reduction of the dynamic model orders and the improvement of the optimization algorithm, and it is suitable for excitation control of large-scale power system. Finally, a fifty-machine power system is used to verify the effectiveness of the presented method. The simulation results show that excitation predictive control method based on balanced reduction model can greatly shorten the optimization calculating time and improve the stability of power system.