Distributed Model Predictive Control for Two-area Interconnected Power System

2018 International Conference of Green Buildings and Environmental Management

土木建筑工程;生态环境科学

An, Aimin^1,2 ; Lin, Jian^1 ; Cheng, Chi^2 ; Zhu, Wenpei^2

College of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou

730050, China^1

Key Laboratory of Gansu Advanced Control for Industrial Processes, Lanzhou University of Technology, Lanzhou

730050, China^2

关键词: Area control error;    Closed-loop performance;    Control target;    Distributed Model predictive Control;    Dynamic equations;    External disturbances;    Load frequency control (LFC);    Prediction model;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/186/4/012008/pdf
DOI  :  10.1088/1755-1315/186/4/012008

来源: IOP

【 摘 要 】

For the problem of uncertain external disturbances which are always present in modern power systems, this study proposes a distributed model predictive control (DMPC) scheme for the load frequency control (LFC) problem of the multi-area interconnected power system. In this paper, the dynamic model of multi-area interconnected power system is introduced, and the DMPC is proposed to replace the traditional PI control. For the constraint of generator power rate of change, the control system uses the dynamic equation of state of the interconnected power system as the DMPC prediction model. The disturbance is the change of the load and the input change of the governor. The predicted output is the area control error (ACE). The power system consists of subsystems that contain their own controllers, and the controllers in each region integrate the information of the other controllers into the control targets to facilitate coordination. The DMPC algorithm proposed in this paper ensures the applicability and stability of the DMPC algorithm in the LFC system and reduces the communication requirements at the same time. Simulation results show that closed loop performance and robustness are greatly improved compared with the traditional methods.