On Neighborhood-Based Control of Wave Energy Arrays: Possible Realization Strategies and Impact of Local Wave Force Estimation and Forecasting

Read full text
Authors: Zechuan Lin, Pedro Fornaro, Yifei Han, Xi Xiao, John V. Ringwood
Cited by: 3
References: 22

Abstract

In the control of wave energy converter (WEC) arrays, due to radiation coupling effects, ideal (optimal) centralized control has complexity that grows rapidly with the array size, making it impossible to handle arbitrarily large arrays. Given that radiated energy decays with distance, leveraging proximity relationships within the array is a natural approach to limiting control complexity. However, such neighborhood-based (NB) control, with many possible realization strategies, has remained unexplored. This study makes a first step in this direction, with two fundamental contributions. First, it is shown how neighborhoods should be selected, and how the control action of each device should be determined, to achieve the highest performance among various NB control options. Second, it is revealed that local wave excitation force (WEF) estimation and forecasting can sometimes create a positive model-error-coupling effect, improving overall control performance. The developed NB control strategy shows improvement in energy production across a wide range of wave conditions while effectively limiting computational complexity (e.g., with a maximal neighborhood size of three in a 1-D array, it achieves over 90% mechanical energy capture of centralized control (17% above independent control) with ideal WEF information or about 95% (8% above) with independent WEF estimation), offering an efficient solution for the control of large WEC arrays, and providing important guidelines for further control design.

Fields of Study & Subjects

Wave and Wind Energy Systems Ocean Waves and Remote Sensing Coastal and Marine Dynamics

Publication details

Journal / source
IEEE Transactions on Control Systems Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
34
Issue
5
Pages
2392–2404
Publication date
2 June 2026