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Improving fuel efficiency in offshore support vessels under dynamic positioning Mode
Main TrackOffshore WindCyan Renewables
Up to S$5,000 in POC / pilot expensesUK-Singapore Collaborative R&D Call
Cyan Renewables,
founded in 2022 and headquartered in Singapore, is Asia’s first offshore wind-focused vessel operator. Managing 32 vessels across seven countries, it provides full-cycle wind farm support. Through innovation, sustainability, and digitalisation, Cyan partners with global developers, advancing offshore wind infrastructure, clean energy, and workforce development across Asia-Pacific and Europe.
Cyan aims to enhance the sustainability of offshore wind farm operations by improving the fuel efficiency of Offshore Support Vessels (OSVs) that perform Operations and Maintenance (O&M) activities. These vessels operate in Dynamic Positioning (DP) mode for roughly 50% of their time at sea, consuming large amounts of fuel as all engines are typically kept running to ensure redundancy and station-keeping reliability.
While newer OSVs are being purpose-built for offshore wind (described by Cyan as the “BYDs and Teslas of the sea”), the majority of the global fleet still consists of older, legacy vessels that cannot easily be converted or retired. These legacy vessels are the focus of this challenge: identifying retrofit-ready, data-driven solutions that can achieve measurable decarbonisation without the need for major capital reinvestment.
In DP mode, an OSV uses a network of sensors and propulsion controls to maintain its position and heading relative to a fixed target, such as a turbine. The DP control system integrates position, heading, and environmental data to ensure precise station keeping.
However, under current practice, all onboard generators run simultaneously to meet redundancy requirements, even in mild conditions where it may not be necessary to do so. This results in excessive fuel consumption, higher emissions, and greater equipment wear and tear. To be classified as DP2, a vessel must maintain redundancy in its positioning systems and power supply; however, during benign conditions, it may be possible to achieve redundancy without having to operate all generators simultaneously.
The industry already has sensor and cloud-based monitoring systems capable of tracking fuel use. The real challenge is not measurement, but how to use that data effectively to optimise day-to-day vessel operations, particularly by helping crews make data-informed, real-time decisions during DP mode.
Currently, Deck Officers (DPOs) rely heavily on experience and judgment to balance positioning accuracy, redundancy, and power use. This results in inconsistent operational efficiency across vessels and conditions.
This creates an opportunity to develop a decision support tool powered by real-time analytics and AI-driven recommendations to help DPOs dynamically optimise fuel economy, redundancy, and safety.
In this case, incremental improvements matter. Even if full decarbonisation is not immediately possible, achieving 10 to 20% reductions in fuel consumption would represent meaningful progress, both toward sustainability goals and in lowering OPEX and maintenance costs.
How might we enable fuel-efficient Offshore Support Vessel operations in Dynamic Positioning mode, maintaining redundancy and safety?
Requirements
Technical Requirements:
- Develop a predictive model or AI-driven Decision Support Tool capable of determining the environmental and operational parameters that allow safe, reduced-engine operation during DP mode.
- The model must include redundancy logic to ensure that safety requirements remain satisfied when optimising engine configurations.
- Must include a mechanism to determine how long a reduced-engine mode can be safely maintained before revalidation is required.
- Should be adaptable to multiple engine and propulsion configurations, including:
- Shaft generators
- Diesel-electric systems
- Controllable pitch propellers
- Azimuth thrusters
- Through-hull thrusters
- The tool should be retrofittable or add-on, designed for existing OSVs rather than requiring replacement of onboard systems or major hardware modifications.
- The solution should leverage existing sensor and cloud infrastructure already used for fuel monitoring and vessel telemetry, to minimise installation complexity.
- The tool should ingest live and historical DP data (position, heading, wind, thrust, current, load, and engine performance) to calculate redundancy confidence levels and predict optimal operating configurations.
- Output should be delivered via an intuitive visual dashboard or alert interface, suitable for bridge use.
Performance Requirements:
- Must demonstrate safe DP redundancy retention while achieving measurable fuel savings.
- Must be validated under different environmental conditions, for example, varying wind, current, and sea states.
- Must provide clear visual recommendations for when reduced-engine operation is safe, and for how long it can be sustained.
- The tool should also quantify improvements in operational efficiency (fuel saved, CO₂ reduced, and engine runtime lowered).
Financial Considerations:
- Solution cost should be proportional to demonstrated fuel savings and scalability across multiple vessels.
- Solutions should prioritise low-cost, software-driven implementations rather than heavy CAPEX installations.
Who Should Apply:
- Expected Technology Readiness Level (TRL) of 5
Potential Sustainability Impact:
- Optimised DP operations that can reduce carbon emissions by minimising unnecessary engine use
- Estimated emissions savings could reach up to 1,500-2,000 tonnes of CO₂ per vessel annually, depending on operating profiles and duty cycles. This estimate assumes typical DP utilisation patterns and highlights that even partial fuel-efficiency gains through improved generator management represent a meaningful, incremental step toward decarbonising older fleets.
- Lower fuel use, translating directly to reduced costs and longer engine lifespans
POC / Pilot & Incentives
Expected POC / Pilot & Timeline:
- Development and POC / pilot duration: Approximately 12 months, comprising:
- 6 months for model development and data integration
- 6 months for prototype validation and pilot deployment
- POC / pilot scope may include one vessel in active DP operations and validation against baseline fuel consumption logs.
- Success criteria will likely focus on verified fuel and emissions savings as well as crew adoption and usability.
POC / Pilot Support:
- Cyan will cover selected expenses up to S$5,000.
- Potential for technology demonstration project utilising UK-Singapore Collaborative R&D Call (jointly administered by Innovate UK and Enterprise Singapore)
- Access to vessel data
- Access to a testbed vessel for prototype validation
- Technical guidance from Cyan's operations and ESG teams
Further Opportunities:
- There is an immediate opportunity for deployment across Cyan Renewables’ OSV fleet and charter partners.
- The solution could also be applicable to legacy offshore vessels across oil & gas and subsea sectors.
Info Session
Check out the recording from our Info Session, where Lidl & Kaufland Asia shared more about their challenge statement.
RESOURCES
Info Session Recording
Revisit the detailed presentation on this challenge statement from our virtual Info Session.
Next Steps
Still have questions?
- Write to us at info@padang.co with any questions.
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