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Reliable OM decision tools and strategies for high LCoE reduction on Offshore wind

Periodic Reporting for period 4 - ROMEO (Reliable OM decision tools and strategies for high LCoE reduction on Offshore wind)

Reporting period: 2021-06-01 to 2022-05-31

The EU is actively promoting Europe’s transition to a low-carbon society and is dedicating huge efforts in reaching a real clean energy transition. Although in the last years there is a substantial increase of the Wind Energy power capacity across the EU, there is still a long way to achieve the current 2030 target of at least 32% for the renewable energy share consumed in the EU, and the even more ambitious 40-45% target by 2030 recently proposed by the European Institutions. Offshore Wind Energy demands advanced Operation & Maintenance (O&M) solutions to significantly improve the return of investment (Rol) and Levelized Cost of Energy (LCoE) indicator, and for performing the reliability and extended life-time of wind turbines (WTs) and wind farms (WF) over the years. Under this scenario, ROMEO project was launched as a strategic initiative to continue leading the offshore wind energy in the EU. Its main aim is to develop models and tools for early fault detection and diagnosis and prognosis, allowing the transition from calendar based maintenance to condition-based maintenance strategies significantly reducing O&M costs. To that end, a flexible and interoperable cloud IoT platform provides an advanced analytics ecosystem to better understand the real time behaviour of the main components of the WTs under operation conditions; maximizing their life-time and reducing unexpected major correctives, thus minimizing the OPEX which drastically impact on LCoE of offshore Wind Energy.

The project is structured in 3 phases:
- 1. “Specifications” has defined the specifications and requirements to develop a monitoring strategy for the most relevant and critical components to be further considered
- 2. “Models/tools/database” has developed health monitoring systems, diagnosis and prognosis tools for failure detection both at WT components and support structures level, feeding the development of a data acquisition and advanced analytics ecosystem
- 3. “O&M/rollout” has developed and deployed an O&M platform validated in 3 pilot scenarios; the data has served as input for impact assessment with a special focus on LCoE and replicability.

ROMEO’s successful implementation has led to achieve the following overall objectives:
-Reduction of unexpected major correctives through early fault identification, in WTG and substructure;
-Improved performance for new and operating offshore wind power plants and improved cost of energy;
-Contribution to strengthening the European industrial technology base, thereby creating growth and jobs in Europe;
-Contribute to health and safety in the Wind industry;
-Generating synergies in the field of O&M strategies with Onshore wind sector;
-Laying the foundation to place on the market a set of new products and services.
ROMEO project has reached the end producing significant results linked to dissemination, exploitation and impact potential. The activities have progressed well and according to the planning established with minor deviations. The project has achieved all expected milestones and the partners submitted all committed deliverables. The following results achieved are highlighted:

- Requirements have been defined as a solid roadmap and the potential failure modes that apply for predictive maintenance have been identified according to their criticality. 337 failure modes have been identified out of which the 120 most critical have been investigated towards applicability of monitoring systems;
- All expected algorithms of diagnosis and prognosis related to drive train, blade bearing and electrical equipment have been successfully implemented and validated. Portability has been developed were applicable;
- Physical models for the diagnosis and prognosis of critical failure modes for platforms AD5-135 to Wikinger (13 models) and for SWT 2.3 93 to Teesside (5 models) have been developed and tested. Machine Learning (ML) models have been developed and tested for all these physical models;
- The partners completed 2 temporary measuring campaigns on Wikinger substation and one jacket foundations, finished the Finite Element (FE) models for Wind Turbines (WT) and jacket substructure, completed t load interactions and set off for low-cost monitoring methods for the WT jackets as main results achieved; Low cost monitoring methods for damage detection and fatigue have been developed.
- The 3 ICT architectures of the WFs have been finalized. A full connection with the IBM Cloud ecosystem was reached, establishing IBM Cloud components, gateways and secure connections; Models have been hosted on the cloud and ran providing result to the O&M tool.
- New concepts have been developed for monitoring and analytics functionalities, as well as advisory generation on the O&M information and management tool. This novel approach required to create digital twins of WTs, establish an asset management framework and provide a knowledge base and a reasoning process. A visualization platform based on VR has been developed to show results from the foundations models.
- Node#1 Gateway, including Alert algorithm, has been deployed on East Anglia One Onshore substation. Connections for visualization to internal information systems have been developed.
- An impact assessment tool has been developed, including modules for cost and power production assessment but also for environmental impact assessment. Its modular form structured in 5 modules of the numerical tool enables focused research to take place in order to evaluate the effect of modelling uncertainties to the assessment of the KPIs; The analysis of project results has shown very good O&M costs reduction and LCOE reduction figures.
- 21 Business models have been elaborated for results with exploitation potential. 3 training pills blocks have been created and put at disposal of industry and Academy. 2 dissemination videos and 2 factsheets have been prepared showing main project results.
A significant progress beyond the SoA has been achieved thanks to ROMEO project:
- 3rd generation of WTG components Condition Monitoring technologies;
- Data driven models for early fault detection, diagnosis and prognosis;
- Advanced low-cost monitoring techniques at WTG substructure level for damage detection and fatigue;
- Extreme Transaction and Processing Architectures for data acquisition and analytics ecosystem;
- Deployment of on-edge computing system
- Ensuring proper integration of multiple data streams in O&M Information Management;
- Smart and advanced wind farm O&M strategies;
- Innovative cost models to improve LCoE and provide replicability strategies.

21 project results count on relevant potential to become future ground-breaking products and services. Impacts and results achieved as a result of the project’s progress beyond the SoA:
- Component failure reduction and increased reliability;
- The development of innovative solutions and tools will allow to create more reliable wind turbines and plants;
- Significant contribution to an improved performance for new and operating offshore wind power plants and therefore to the cost of energy;
- Project’s tools and solutions will have exploitation potential in the onshore wind sector;
- Contribution to strengthen the European industrial technology base, creating growth and jobs;
- Contribution to health and safety in the Wind industry;
- Impact to substructure and soil monitoring by fatigue and damage detection models.
Infographics with the goals of ROMEO project