Model predictive control of VSC-HVDC system for wind power integration

被引:0
|
作者
Liu Y. [1 ]
Zhang L. [1 ]
Liang H. [1 ]
Zhao W. [2 ]
Song W. [2 ]
Liu X. [2 ]
机构
[1] School of Electrical and Electronic Engineering, North China Electric Power University, Baoding
[2] Cangzhou Electric Power Supply Company, State Grid Hebei Electric Power Supply Co., Ltd., Cangzhou
基金
中国国家自然科学基金;
关键词
Model predictive control; Pulse width modulation; Two-step prediction method with time-delay compensation; VSC-HVDC; Wind power integration;
D O I
10.16081/j.issn.1006-6047.2019.06.015
中图分类号
学科分类号
摘要
The traditional double-closed-loop control strategy of VSC-HVDC(Voltage Source Converter based High Voltage Direct Current) system with wind power integration has many problems, such as complex control structure, many PI parameters which are difficult to be set, slow response speed, and so on. In order to solve the above pro-blems, a model predictive control strategy of VSC-HVDC system for wind power integration is proposed. To improve the control precision of AC voltage of wind farm bus, WFVSC(Wind Farm VSC) adopts the constant AC voltage control based on the optimized model predictive control and a two-step prediction method with time-delay compensation is proposed. The model predictive control is combined with PWM(Pulse Width Modulation) technology to obtain the optimal solution of modulating wave in two control cycles, and then the switching signal is generated by the modulating unit to act on the WFVSC. GSVSC(Grid Side VSC) adopts the finite control set model predictive power control. Based on the discrete mathematical model of GSVSC, the switching state combination which minimizes the cost function is found to act on GSVSC by cost function ergodic optimization. The VSC-HVDC system based on the proposed model predictive control has good steady-state performance, dynamic performance and fault recovery performance, and can provide stable AC voltage for wind farm. Simulative results verify the feasibility and effectiveness of the proposed control strategy. © 2019, Electric Power Automation Equipment Press. All right reserved.
引用
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页码:102 / 108and114
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