Noncausal explicit model predictive control of wave energy converters
Noncausal explicit model predictive control of wave energy converters
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).
Optimal Control, Wave Energy Converters, Wave Prediction, model predictive control, robustness, Model predictive control, Wave prediction, Optimal control, Robustness, Wave energy converters
Gao, Teng
b239fe09-cfd0-4a58-945f-c4a24eb2b644
Zhang, Yao
40b201b9-953e-45d5-a219-0c68442c3363
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
28 June 2025
Gao, Teng
b239fe09-cfd0-4a58-945f-c4a24eb2b644
Zhang, Yao
40b201b9-953e-45d5-a219-0c68442c3363
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Gao, Teng, Zhang, Yao and Tezdogan, Tahsin
(2025)
Noncausal explicit model predictive control of wave energy converters.
Ocean Engineering, 338, [121999].
(doi:10.1016/j.oceaneng.2025.121999).
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).
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Accepted/In Press date: 22 June 2025
e-pub ahead of print date: 28 June 2025
Published date: 28 June 2025
Keywords:
Optimal Control, Wave Energy Converters, Wave Prediction, model predictive control, robustness, Model predictive control, Wave prediction, Optimal control, Robustness, Wave energy converters
Identifiers
Local EPrints ID: 503569
URI: http://eprints.soton.ac.uk/id/eprint/503569
ISSN: 0029-8018
PURE UUID: e69f4bf7-166e-4a54-9387-00f043c32a81
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Date deposited: 05 Aug 2025 16:47
Last modified: 01 Oct 2025 02:12
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Contributors
Author:
Teng Gao
Author:
Yao Zhang
Author:
Tahsin Tezdogan
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