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Decentralized model predictive control strategy of a realistic multi power system automatic generation control

机译:逼真多电力系统自动化控制的分散模型预测控制策略

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This paper presents a decentralized Model Predictive Control (MPC) for Automatic Generation Control (AGC) of a realistic multi power system in Egypt with inherent nonlinearities. The Egyptian Power System (EPS) is decomposed into three dynamic subsystems which are non-reheat, reheat, and hydro power plants. Moreover, each subsystem has its private characteristics compared to the others. Therefore, each subsystem controller has been designed independently to guarantee the stability of the overall closed loop system. Hence, MPC is proposed for every subsystem separately to regulate the frequency and to track the load demands of EPS. The performance of the proposed decentralized MPC of each subsystem is compared with the centralized one at different operational scenarios. The results by nonlinear simulation MATLAB/SIMULINK for the generation control of EPS approves that the decentralized predictive model gives almost the same performance as the centralized one. However, the centralized model cannot address the large load disturbance and system parameters variation. In contrast, the decentralized MPC scheme is more robust and effective against all disturbances and operating conditions.
机译:本文介绍了具有固有非线性的埃及现实多电力系统的自动生成控制(AGC)的分散模型预测控制(MPC)。埃及电力系统(EPS)被分解成三个动态子系统,这些子系统是非再加热,再加热和水力发电厂。此外,与其他子系统相比,每个子系统都有其私有特性。因此,每个子系统控制器已经独立设计以保证整个闭环系统的稳定性。因此,为每个子系统分开提出MPC以调节频率并跟踪EPS的负载需求。将每个子系统的提出的分散MPC的性能与不同操作场景的集中式相比。非线性模拟MATLAB的结果/ SIMULINK对EPS的生成控制批准,分散的预测模型提供与集中式相同的性能。但是,集中式模型无法解决大负载干扰和系统参数变化。相比之下,分散的MPC方案对所有扰动和操作条件更加坚固,有效。

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