Introduction
Floating offshore wind is transitioning from demonstration-scale projects to commercial deployment, with multiple GW-scale projects in planning worldwide. This transition necessitates a fundamental rethinking of monitoring strategies. While demonstration projects could afford comprehensive instrumentation, commercial floating wind farms require optimized approaches that balance cost, reliability, and actionable insights. Effective monitoring is critical not only for operational performance and safety but also for reducing lifecycle costs through informed maintenance decisions and integrity management. The commercial viability of floating wind depends on monitoring systems that scale efficiently while providing critical decision support. Ozea, developed through collaboration between AMOG and sowento, directly addresses this industry need with a holistic monitoring, risk management and decision support platform specifically designed for commercial-scale floating wind farms.
The Evolution of Floating Wind Monitoring
Demonstration and pilot floating wind projects typically employed extensive instrumentation suites, with sensors measuring virtually every component from turbine to mooring system. These projects, comprising 1-5 turbines, justified comprehensive monitoring to validate designs and build operational understanding. However, as projects scale to dozens or hundreds of units, this approach becomes economically and operationally unsustainable. Early monitoring focused on data collection rather than actionable intelligence, with limited integration between component monitoring systems. Commercial scale demands a shift from data accumulation to decision-focused monitoring that supports integrity management throughout the asset lifecycle. Ozea’s approach represents this evolution, combining AMOG’s 30+ years of offshore monitoring expertise with sowento’s wind turbine modeling capabilities to deliver actionable integrity insights rather than mere data collection.
Commercial Scale Monitoring Challenges
The scale and complexity of commercial floating wind farms introduce numerous monitoring challenges. Farm size dramatically impacts instrumentation strategy—a 200-turbine farm cannot sustain the same monitoring intensity as a 5-turbine demonstration. Larger turbines (15-20 MW) create different loading profiles requiring tailored monitoring approaches. Mooring configurations, whether non-redundant (3×1) or redundant (3×2), influence failure risk and monitoring requirements. Cable arrangements (radial vs. ring) affect system vulnerabilities. Site heterogeneity means design variations across a single farm, complicating standardized monitoring. Additional factors include staged deployment, operational changes over time, maritime traffic, design life considerations, and insurance requirements. These challenges are compounded by instrumentation maintenance requirements, data management constraints, and cybersecurity concerns. Ozea’s monitoring platform is specifically designed to address these commercial-scale challenges, with a fully modular, sensor-agnostic approach that can adapt to various farm configurations and scales.
Why Demonstration Scale Approaches Don’t Work
The demonstration approach of instrumenting entire floating wind turbines (FOWT) with comprehensive sensor arrays is economically prohibitive at commercial scale. A fully instrumented demonstration turbine might deploy dozens of subsea sensors, hundreds of structural gauges, and multiple environmental monitoring systems—costing millions per unit. This approach generates excessive data without proportional actionable insights, creating “data swamps” rather than useful intelligence. Subsea sensors present particular scaling challenges, with high failure rates in harsh environments and prohibitive maintenance costs. Component-level monitoring lacks the holistic system understanding necessary for commercial operations. Most critically, instrumentation suppliers often lack system engineering expertise, focusing on sensor deployment rather than integrity management integration, resulting in disconnected monitoring systems that fail to support operational decision-making effectively. Ozea distinguishes itself by combining instrumentation strategy with comprehensive engineering expertise in floating systems, offering a holistic approach rather than simply deploying sensors.
Optimal Monitoring Arrangement for Commercial Scale
Commercial floating wind farms require strategic instrumentation clustering rather than uniform deployment. Optimal arrangements typically include “master” units with comprehensive instrumentation (approximately 10-15% of the fleet) that provide detailed understanding, while the remainder employs minimal targeted instrumentation. This approach enables system calibration while managing costs. Effective commercial monitoring systems employ digital twin integration with virtual sensing capabilities, reconstructing unmeasured parameters through physics-based models. Systems should be sensor-agnostic and modular, allowing technology evolution and retrofitting. Cloud-based architectures with appropriate redundancy provide cost-effective scalability, while maintaining operational technology security. Critical components require integration with control systems for automatic response to detected failures, such as mooring line breakage. Commercial systems must demonstrate robustness to sensor failure, maintaining functional monitoring even with partial data streams. Ozea’s platform embodies these principles, leveraging sowento’s SLOW model and AMOG’s SMIC technology to provide virtual sensor capabilities and maintain monitoring integrity even with minimal physical instrumentation.
Holistic Monitoring Framework Components
A holistic monitoring framework addresses five key FOWT subsystems. Turbine monitoring focuses on acceleration limits, power curve assessment, and performance optimization. Tower structural monitoring tracks base bending moments and fatigue accumulation rates against design limits. Floater structural monitoring evaluates stress distributions, fatigue accumulation, and identifies potential integrity concerns. Cable monitoring assesses dynamic and static cable integrity through tension and bending fatigue utilization indicators. Mooring system monitoring provides real-time line integrity status, fatigue accumulation, and wear indicators at critical interfaces. These component-level monitoring systems integrate through a unified framework that correlates environmental conditions with system responses, providing system-level understanding rather than isolated parameters. This holistic approach enables differentiation between normal operational variations and actual integrity concerns. Ozea’s platform is distinguished by its comprehensive coverage of all these subsystems through a single integrated solution, rather than requiring separate monitoring systems for each component.
Data Management and Decision Support
Commercial scale monitoring generates terabytes of operational data requiring sophisticated management. Effective systems differentiate between real-time processing needs (for operational safety and control) and historical analysis (for integrity management and optimization). Alert systems must employ multi-tiered thresholds with appropriate escalation protocols to prevent alarm fatigue while ensuring critical conditions receive immediate attention. Reporting structures should provide daily operational summaries, monthly performance assessments, and quarterly integrity evaluations. Data visualization interfaces require role-specific dashboards that translate complex monitoring data into actionable insights for operators, maintenance teams, and asset managers. API integration with computerized maintenance management systems enables condition-based maintenance planning, optimizing resource allocation based on actual system health rather than calendar-based schedules. Ozea delivers this functionality through its secure web interface, real-time alerting systems, and comprehensive performance reporting capabilities that transform complex monitoring data into clear decision support tools.
Virtual Sensing Capabilities
Ozea’s most significant innovation is its advanced virtual sensing capability, which significantly reduces the cost of the monitoring approach for commercial-scale floating wind. The system uses a sophisticated state observer model that combines limited physical measurements with sowento’s SLOW real-time simulator to reconstruct “virtual sensors” throughout the floating wind turbine. This approach enables monitoring of critical parameters—such as mooring line tensions, cable bending moments, and structural stresses—even where direct physical sensors are not installed. The virtual sensing framework is verified against a highly instrumented “master” unit. It continuously calibrates against measurements ensuring accuracy while dramatically reducing instrumentation costs. In tests, Ozea’s virtual sensors have demonstrated high accuracy compared to direct measurements, with particular strength in capturing dynamic response characteristics during extreme events. This capability allows operators to maintain comprehensive monitoring coverage while implementing only the most critical physical sensors, addressing the fundamental economic challenge of commercial-scale monitoring. The virtual sensing system is robust to sensor failure, automatically reconfiguring to maintain monitoring integrity even when individual sensors are compromised, a critical advantage in the harsh offshore environment where sensor maintenance presents significant operational challenges.
Case Study: Commercial Scale Implementation
A 50-turbine floating wind farm would implement a stratified monitoring approach with five fully instrumented “master” units and 45 units with minimal instrumentation. Master units feature comprehensive packages including GPS, IMU, strain gauges, load cells, fiber optics, and environmental monitors. Standard units employe only GPS, IMU, and critical connection point monitoring. Approximately, this approach would reduce monitoring CAPEX by 50-60% compared to comprehensive instrumentation while maintaining 90%+ of the integrity management value. The digital twin integration reconstructs unmeasured parameters with 92-96% accuracy compared to direct measurement. We assume to identify around 5-8 potential developing issues before they became critical failures, resulting in an estimated 2M-4M maintenance savings over the years. The main implementation challenges we anticipate are calibrating digital twin models against actual operational data and developing robust data cleansing algorithms to manage sensor noise and drift. Ozea’s approach, combining AMOG’s SMIC and sowento’s SLOW technologies, enables similar optimization of instrumentation strategies while maintaining comprehensive integrity insights through its state observer model and real-time simulator capabilities.
Future Outlook
Commercial floating wind monitoring is rapidly incorporating machine learning capabilities that improve anomaly detection and failure prediction accuracy. Supervised learning models trained on demonstration projects are being deployed to identify developing issues before traditional threshold-based systems can detect them. Autonomous inspection technologies including underwater and aerial drones are being integrated with fixed monitoring systems to provide periodic verification of continuous monitoring data. Classification societies are developing updated standards for floating wind monitoring that recognize the cost-benefit balance of stratified instrumentation approaches. Farm-level control strategies are beginning to incorporate monitoring data to optimize not just individual turbine performance but overall array efficiency and component loading. These advancements point toward increasingly intelligent monitoring systems that will further reduce operational costs and improve reliability. Ozea is well-positioned to integrate these emerging technologies through its modular, retrofittable architecture and the combined expertise of AMOG and sowento in offshore engineering and wind turbine technology.
Conclusion
Successful commercial-scale floating wind monitoring requires a fundamental shift from the demonstration mindset of comprehensive instrumentation to strategic, risk-based approaches that balance information needs with economic constraints. Critical success factors include digital twin integration, strategic sensor deployment, robust data management, and seamless integrity management integration. By adopting these principles, developers can create monitoring systems that scale efficiently while providing the insights needed for safe, reliable operation. As the industry matures, standardized monitoring approaches will emerge that optimize the cost-benefit equation, contributing significantly to reducing the overall Levelized Cost of Energy (LCOE) for floating wind. Ozea Technologies represents this next-generation approach, providing a comprehensive monitoring solution that integrates AMOG’s offshore integrity management expertise with sowento’s wind turbine modeling capabilities. This collaboration delivers a unique value proposition: a monitoring system designed specifically for commercial-scale floating wind that balances instrumentation optimization with comprehensive integrity management support throughout the asset lifecycle.
