Real-time Nonlinear Economic Model Predictive Control of Wind Energy Conversion System

被引：0

作者：

Wang, Wenwen ^{[1
]}

Liu, Xiangjie ^{[1
]}

Kong, Xiaobing ^{[1
]}

机构：

[1] School of Control and Computer Engineering, North China Electric Power University, Beijing

来源：

Xitong Fangzhen Xuebao / Journal of System Simulation | 2025年 / 37卷 / 03期

关键词：

fatigue load; moving horizon estimation; nonlinear economic model predictive control; real-time iteration; wind energy conversion system;

D O I：

10.16182/j.issn1004731x.joss.23-1396

中图分类号：

学科分类号：

摘要：

To address the new challenges of economic control and real-time requirements in wind energy conversion systems (WECS), this study proposes a nonlinear economic model predictive control (NEMPC) strategy. This strategy aims to maximize power generation and while reducing fatigue loads on critical structures, such as towers and gearboxes. Additionally, a moving horizon estimator (MHE) has been designed to provide an effective initialization for optimization. By exploiting the similarity of nonlinear programs between adjacent sampling moments, the algorithm achieves real-time iterative (RTI) solutions. Using a 5 MW wind turbine as the research object, the proposed strategy is implemented in the ACADOS framework for real-time optimization. Simulation results demonstrate that the strategy effectively improves the economic performance of the system while ensuring real-time control. © 2025 Acta Simulata Systematica Sinica. All rights reserved.

引用

页码：679 / 690

页数：11

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