基于多模型预测控制策略的输电网电压协调控制

Jia-lin Bai, I. Erlich
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引用次数: 0

摘要

针对输电网在不同预期条件下的电压协调控制问题,提出了一种基于多模型的预测控制策略。由于卡尔曼滤波和优化过程都是基于数学模型的,因此需要一个代表关键工况的模型数据库。对于非表示条件,通过设置卡尔曼滤波的噪声模型和调整MMPC的优化窗口,使MMPC具有鲁棒性。在每个控制周期中,MMPC寻找自动电压调节器和静态无功补偿器的最优协调。案例研究考虑了两种类型的运行变化:负载在24小时内的变化和发电机进入/退出服务。在不同的仿真试验中,与基于单模型的控制策略相比,证明了MMPC在负荷增加扰动下的优越性和鲁棒性。
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Coordinated Voltage Control for Transmission Grid Based on Multi-model Predictive Control Strategy
This paper proposes a multi-model based predictive control (MMPC) strategy for the coordinated voltage control of the transmission grid that may operate under diverse anticipated conditions. Since both Kalman filtering and optimization process are based on mathematical model, a model database representing the critical operating conditions is required. For unrepresented conditions, MMPC is designed to be robust by setting the noise model of Kalman filter and by tuning the optimization window of MMPC. In each control cycle, MMPC searches for the optimal coordination of Automatic Voltage Regulators and Static Var Compensators. The case studies take into account two types of operation changes: load change over 24 hour and generator in/out of service. In different simulation tests, in comparison with single -model based control strategy, the superiority and robustness of MMPC following a load increase disturbance are demonstrated.
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