A novel maximum energy extraction strategy using lithium-ion batteries for Archimedes wave swing wave energy conversion systems
Ahmed Mahdy,
Shady H.E. Abdel Aleem and
Hany M. Hasanien
Renewable Energy, 2026, vol. 256, issue PI
Abstract:
Energy maximization in wave energy conversion systems (WECSs) is often constrained by grid code restrictions, limiting power absorption for higher energy yield. This work proposes an innovative maximum energy extraction (MEE) strategy that uses a nonlinear reference quadrature-axis current derived from the Archimedes Wave Swing (AWS) WECS model components. The approach adopts a bidirectional DC-DC converter with lithium-ion batteries, providing an on-demand energy supply and eliminating grid dependency. Lithium-ion batteries are chosen due to their elevated energy density, extended operational lifespan, rapid charging capabilities, and reduced maintenance needs. The system architecture includes an AWS-WECS with a linear permanent magnet synchronous generator (LPMSG). In addition, a cascaded rectifier-inverter topology with an intermediate DC link is needed for a successful grid connection. Seven proportional-integral (PI) controllers are employed to minimize losses, optimize energy extraction, regulate the DC-DC converter, and stabilize both the point of common coupling voltage and the DC link voltage. MATLAB simulations demonstrate an improvement in energy yield of 90 %, 50 %, and 33 % compared to the base uncontrolled case, model-based control (without power absorption), and the feedback linearization method. This confirms the efficacy of the suggested nonlinear control strategy based on lithium-ion technology in enhancing energy extraction for AWS-WECSs. Finally, the system's performance has been experimentally assessed through the utilization of the OP4610 real-time simulator.
Keywords: Archimedes wave swing; Energy maximization; Lithium-ion batteries; Power system control; Wave energy; Wave energy conversion systems (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:256:y:2026:i:pi:s0960148125023286
DOI: 10.1016/j.renene.2025.124664
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