Self-contained power optimization for wave energy conversion: A step change in generation
Year: 2025
Type: article
Abstract: Wave energy holds immense potential, yet to date progress has been hampered by substantial design challenges and perceived high levelized cost of electricity (LCoE). Control strategies could be vital for improving the economic viability of wave energy converters (WECs), yet practical implementations demonstrating performance remain limited. Here, we present, and implement experimentally for the first time, a self-sufficient control system requiring no external measurements. It is physically demonstrated for the complex hinged, Moored, MultiMode, Multifloat WEC, called M4. The controller operates within a linear noncausal framework to optimize generator torque, where excitation forces are estimated and predicted autoregressively. A real-time state-space hydrodynamic model, based on the Cummins-type linear diffraction-radiation formulation, enables operation based solely on motor-generator torque-speed data. In a first-of-its-kind wave basin experiment, the control strategy is shown to over double energy capture (up to a 125% increase) whilst also demonstrating performance in both unidirectional and directionally spread irregular wave conditions, mimicking real ocean complexity. Site-specific assessment across four European wave sites demonstrates substantial implications for system design and performance: The optimal device size is approximately 40 % less than that defined by the average peak period of a site, as often used, and with control implemented, the average power per unit mass (approximately proportional to the inverse of LCoE) increased by about 100 % across the four sites. This represents a step change toward the commercial viability of wave energy.
Source: Physical Review Research
DOI: 10.1103/f24b-9hkc
Authors: Zhijing Liao, Samuel Draycott, Peter Stansby, Jinqian Du, Guang Li
Institution: University of Manchester
Language: English
Topic: Wave and Wind Energy Systems
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,625
OpenAlex ID: W4417268058