Centralized Model Predictive Control Method for Arrays of Direct-drive Wave Energy Converters

LIN Zechuan; HUANG Xuanrui; XIAO Xi

doi:10.7500/AEPS20230731010

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Centralized Model Predictive Control Method for Arrays of Direct-drive Wave Energy Converters

Application Research | 更新时间：2025-06-16

- Centralized Model Predictive Control Method for Arrays of Direct-drive Wave Energy Converters
- Automation of Electric Power Systems Vol. 48, Issue 22, Pages: 191-198(2024)
- 作者机构：
  
  清华大学电机工程与应用电子技术系，北京市 100084
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2020YFE0205400);National Natural Science Foundation of China(52337002)
- DOI：10.7500/AEPS20230731010
  CLC：
- Received：31 July 2023，
  
  Revised：2024-03-07，
  
  Published Online：04 June 2024，
  
  Published：25 November 2024
- 稿件说明：
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林泽川,黄宣睿,肖曦.阵列式直驱波浪发电系统集中式模型预测控制方法[J].电力系统自动化,2024,48(22):191-198.

LIN Zechuan,HUANG Xuanrui,XIAO Xi.Centralized Model Predictive Control Method for Arrays of Direct-drive Wave Energy Converters[J].Automation of Electric Power Systems,2024,48(22):191-198.
林泽川,黄宣睿,肖曦.阵列式直驱波浪发电系统集中式模型预测控制方法[J].电力系统自动化,2024,48(22):191-198. DOI： 10.7500/AEPS20230731010.

LIN Zechuan,HUANG Xuanrui,XIAO Xi.Centralized Model Predictive Control Method for Arrays of Direct-drive Wave Energy Converters[J].Automation of Electric Power Systems,2024,48(22):191-198. DOI： 10.7500/AEPS20230731010.

摘要

将多个波浪能发电装置组成阵列是大规模开发波浪能的发展趋势。对于阵列式直驱波浪发电系统

采取合适的能量优化控制方法能显著提升波浪能捕获效率。然而，由于阵列式系统存在浮子间的相互辐射作用，已有的集中式模型预测控制（MPC）面临在线计算量大、难以工程应用的困难，而将各浮子视作独立系统的分布式MPC则存在能量捕获效率的损失。对此，文中提出一种改进的集中式MPC方法，将优化区间与约束区间进行解耦，可在保障系统整体能量捕获效率的同时，大幅减少计算开销，提升系统的实时控制性能。通过仿真研究分析了约束区间解耦方法的性能，并在多种波浪工况条件下验证了所提出方法的有效性。

Abstract

To further exploit wave energy on a large scale

it is an important trend to form multiple wave energy converters (WECs) into arrays. For arrays of direct-drive WECs

adopting an appropriate energy optimization control strategy can significantly improve their wave energy capture efficiency. However

due to the radiation coupling effects between bodies in arrays

existing centralized model predictive control (MPC) faces difficulties in online computation burden and engineering applications

while distributed MPC that regards each body as an independent system inevitably suffers from energy capture efficiency losses. In this regard

an improved centralized MPC method is proposed

in which the optimization horizon and constraint horizon are decoupled to significantly reduce the computation burden and improve the real-time control performance of the system while ensuring the overall energy capture efficiency. The performance of the constraint horizon decoupling method is analyzed through numerical simulation

and the effectiveness of the proposed method is verified under multiple wave spectra and wave directions.

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references

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