Work

Noncausal explicit model predictive control of wave energy converters

Year: 2025

Type: article

Abstract: Wave energy is a promising renewable energy source, but its commercial utilisation is low compared to wind and solar energy. This paper proposes an explicit model predictive control (EMPC) strategy to reduce the high computational burden associated with online computation. Realistic wave data collected from the coast of Cornwall, UK, together with realistic single-point absorber parameters, are utilised. The dynamic response of the floating system is controlled, and a disturbance observer and an autoregressive model are designed for wave prediction. This paper aims to identify the most effective strategy to achieve optimal trajectory tracking, rapid prediction, efficient optimisation, and maximum energy capture. The results of numerical simulations show impressive effects of trajectory tracking, wave prediction, and maximum energy capture, with rapid prediction and low computational demand. These results demonstrate the effectiveness of the proposed EMPC method in wave energy converters (WECs).

Source: Ocean Engineering

DOI: 10.1016/j.oceaneng.2025.121999

Authors: Teng Gao, Yao Zhang, Tahsin Tezdogan

Institutions: University of Southampton, University College London

Language: English

Topic: Wave and Wind Energy Systems

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: hybrid

Estimated APC paid: $4,150