[1]林 江,马子钰,杜 伟,等.基于ESO和MPC的光伏模型预测MPPT控制系统设计[J].工业仪表与自动化装置,2025,(04):49-55.[doi:10.19950/j.cnki.CN61-1121/TH.2025.04.009]
　LIN Jiang,MA Ziyu,DU Wei,et al.Strategy for photovoltaic model predictive control MPPT based on ESO and MPC[J].Industrial Instrumentation & Automation,2025,(04):49-55.[doi:10.19950/j.cnki.CN61-1121/TH.2025.04.009]
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基于ESO和MPC的光伏模型预测MPPT控制系统设计()

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2025年04期
页码:
49-55
栏目:
出版日期:
2025-08-15

文章信息/Info

Title:
Strategy for photovoltaic model predictive control MPPT based on ESO and MPC
文章编号:
1000-0682（2025）04-0049-07
作者:
林 江1; 马子钰2; 杜 伟3; 孙睿择4; 李 义3
1.上海交通大学 电气工程系电力传输与功率变换控制教育部重点实验室，上海 200240； 2.贵州电网有限责任公司贵阳供电局，贵州 贵阳 550000； 3.贵州电网有限责任公司毕节供电局，贵州 毕节 551700； 4.贵州电网有限责任公司贵安供电局，贵州 安顺 561100
Author(s):
LIN Jiang1;  MA Ziyu2;  DU Wei3;  SUN Ruizhe4;  LI Yi3
(1. Ministry of Education Key Laboratory of Power Transmission and Power Conversion Control, Department of Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China; 2. Guizhou Power Grid Co., Ltd., Guiyang Power Supply, Guizhou Guiyan
关键词:
扩张状态观测器; 模型预测控制; 扰动观测法; MPPT
Keywords:
extended state observer(ESO);  model predictive control(MPC);  perturbation observation method(P&; O);  MPPT
分类号:
TM615
DOI:
10.19950/j.cnki.CN61-1121/TH.2025.04.009
文献标志码:
A
摘要:
针对多传感器使用降低系统可靠性及传统PI光伏MPPT控制策略动态性能差的问题，提出了一种基于扩张状态观测器的光伏模型预测MPPT控制策略。构造了电压、电流扩张状态观测器，实现电压、电流实时在线估计，减少了传感的使用；结合扰动观察法及模型预测控制策略以光伏输出电压为控制对象，设计成本函数实现光伏MPPT控制；搭建了基于MATLAB/Simulink的光伏系统模型进行对比验证。结果表明，扩张状态观测器能够精确的实现电压、电流实时在线估计，代替电压电流传感器，提升系统的可靠性；光伏模型预测MPPT控制策略比传统PI控制策略具有更强的鲁棒性和更好的动态性能。
Abstract:
Aiming at the problems of multi-sensor use to reduce system dependability and slowly dynamic performance of traditional PI PV MPPT control, a PV model predictive control(MPC) MPPT strategy based on extended state observer(ESO) is proposed. The ESO of voltage and current is constructed to realize the online estimation of voltage and current, to reduce the use of sensor. The cost function is designed to realize the PV MPPT control，in which the PV output voltage as the control object and combining the perturbation observation(P&O) method and model predictive control strategy. The PV system model based on MATLAB/Simulink is built for simulation verification. The result shows that the ESO can accurately realize the real-time online estimation of voltage and current instead of the voltage and current sensors to improve the dependability of the system and the PV MPC MPPT control strategy has stronger robustness and faster dynamic performance than the traditional PI control strategy.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：2024-11-20第一作者：林江(1980－)，男，硕士，高级工程师，研究方向为新型电力系统、电力设备状态监测与诊断等。E-mail：1050727063@qq.com
更新日期/Last Update: 1900-01-01