Novel High Performance Wave Energy Converters with advanced control, reliability and survivability systems through machine-learning forecasting
Lead Research Organisation:
Lancaster University
Department Name: Engineering
Abstract
The NHP-WEC project aims to advance data-driven monitoring and control in connection to both device technology and sea state predictions for WEC arrays. The research proposed is simultaneously generic while also significantly contributing to the development of an existing concept device that has shown potential, namely the multi-axis TALOS that has been developed and tank tested at Lancaster University (LU). TALOS is a novel multi-axis point absorber-style built as a 1/100th scale representation, with a solid outer hull containing all the moving parts (like a submarine or a PS Frog style WEC device). The internal PTO system is made up of an inertial mass with hydraulic cylinders that attach it to the hull. The mass makes up a significant proportion of the device, hence it moves around as the hull is pushed by various wave motions. The motion of the ball moves hydraulic cylinders causing them to pump hydraulic fluid through a circuit. The flow of this hydraulic fluid is used to turn a hydraulic motor, which is coupled to an electrical generator, to generate electricity i.e. an inertial mass PTO approach. Key strengths include: The arrangement of the rams allows for the mass ball to move in multiple directions, allowing energy to be captured from multiple degrees of freedom. The flow of hydraulic fluid will change as the ball's motion changes, so an internal hydraulic smoothing circuit is utilised to regulate the output. The latest design has proven to be successful in wave tank testing and the PTO system yields a smooth output in response to time-varying inputs from waves. An analytical model has also been developed to combine data from the hull model and hydraulic rig, yielding a predicted power output of up to 3.2 kW. However, TALOS is at a very early stage of development and requires further research to advance its Technology Readiness Level (TRL). The design, development, deployment and operation of WECs, such as TALOS and their potential commercial use requires a holistic understanding of the marine environment, including on-line monitoring to enhance control combined with prediction. Potential WEC deployment sites and energy resource from single devices and arrays must be determined. Operational conditions, including wave characteristics must be quantified to estimate dynamic loads on WEC, constraining manufacturing and their real-time operation. In this context, SmartWave, developed by the UoH, with the ORE Catapult and Orsted, is a tool capable of deriving high resolution sea state conditions from satellite images using machine learning. Key strengths: SmartWave is based on a novel forecasting methodology, capable of resolving sea state within offshore windfarms for sector O&M logistics. It integrates recent advances in all-weather satellite monitoring to map and study the temporal and spatial distribution of sea surface wave characteristics. However, existing limitations must be addressed to advance the TRL of WEC capabilities and hence fully exploit this new technology. For example, it has been developed to characterize significant wave height, whilst further research is essential in order to extract other sea state parameters, including wave height, direction and frequency. Nonetheless, since it is capable of global reach remotely, without the use of in situ sensors, SmartWave is uniquely placed to identify the selection of appropriate deployment sites depending on the device size and specification, for optimal production of electricity.
The NHP-WEC project brings together key aspects of WEC technology and the global deployment potential of SmartWave, allowing integration of novel methodologies across optimisation, control, condition monitoring and resource forecasting. These advances will together drive evidenced reductions in costs and hence provide confidence on the benefits of wave energy technology to developers and investors.
The NHP-WEC project brings together key aspects of WEC technology and the global deployment potential of SmartWave, allowing integration of novel methodologies across optimisation, control, condition monitoring and resource forecasting. These advances will together drive evidenced reductions in costs and hence provide confidence on the benefits of wave energy technology to developers and investors.
Organisations
- Lancaster University (Lead Research Organisation)
- Aura Innovation (Project Partner)
- Det Norske Veritas DNV GL UK Limited (Project Partner)
- European Marine Energy Centre (Project Partner)
- Offshore Renewable Energy Catapult (Project Partner)
- ADVANCED MANUFACTURING RESEARCH CENTRE (Project Partner)
- The Deep (Project Partner)
Publications
Zhang H
(2022)
A Preliminary Study on Identifying Biomimetic Entities for Generating Novel Wave Energy Converters
in Energies
Ayub M
(2023)
A Review of Power Co-Generation Technologies from Hybrid Offshore Wind and Wave Energy
in Energies
Guo C
(2023)
A Review of the Levelized Cost of Wave Energy Based on a Techno-Economic Model
in Energies
Darwish A
(2022)
A Review on Power Electronic Topologies and Control for Wave Energy Converters
in Energies
Sheng W
(2023)
Development and validation of the in-house hydrodynamics code and the DNV software for TALOS wave energy converter
in Proceedings of the European Wave and Tidal Energy Conference
Sheng W
(2022)
Hydrodynamic studies of floating structures: Comparison of wave-structure interaction modelling
in Ocean Engineering
Zha ZM
(2022)
Python-assisted biological knowledge acquisition method to trigger design inspiration.
in Scientific reports
Michailides C
(2024)
Response and Power Absorption Assessment of the TALOS Wave Energy Converter in Time Domain
in International Journal of Offshore and Polar Engineering
Hall C
(2024)
The impact of model predictive control structures and constraints on a wave energy converter with hydraulic power take off system
in Renewable Energy
Sheng W
(2022)
Time-Domain Implementation and Analyses of Multi-Motion Modes of Floating Structures
in Journal of Marine Science and Engineering