AWESOME network aims to educate eleven young researchers in the wind power operation and maintenance (O&M) field by constructing a sustainable training network gathering the whole innovation value chain. The main EU actors in the field of wind O&M have worked together, under the umbrella of the European Wind Energy Academy (EAWE), in order to design a training program coping with the principal R&D challenges related to wind O&M while tackling the shortage of highly-skilled professionals on this area that has been foreseen by the European Commission, the wind energy industrial sector and the academia. The overall AWESOME research programme tackles the main research challenges in the wind O&M field identified by the European wind academic and industrial community: (1) to develop better O&M planning methodologies of wind farms for maximizing its revenue, (2) to optimise the maintenance of wind turbines by prognosis of component failures and (3) to develop new and better cost-effective strategies for Wind Energy O&M. These main goals have been divided into eleven specific objectives, which will be assigned to the fellows, for them to focus their R&D project, PhD Thesis and professional career. The established training plan answers the challenges identified by the SET Plan Education Roadmap. Personal Development Career Plans will be tuned up for every fellow, being their accomplishment controlled by a Personal Supervisory Team. The training plan includes intra-network activities, as well as network-wide initiatives. The secondments at partner organizations and between beneficiaries are a key attribute of the training programme. Each fellow will be exposed to three different research environments from both, academic and industrial spheres. All the network activities will be developed in accordance with the established in the Ethical Codes and Standards for research careers development, looking therefore for talent, excellence and opportunity equality.

Floating offshore wind is still a nascent technology and its LCOE is substantially higher than onshore and bottom-fixed offshore wind, and thus requires to be drastically reduced. The COREWIND project aims to achieve significant cost reductions and enhance performance of floating wind technology through the research and optimization of mooring and anchoring systems and dynamic cables. These enhancements arisen within the project will be validated by means of simulations and experimental testing both in the wave basin tanks and the wind tunnel by taking as reference two concrete-based floater concepts (semi-submersible and spar) supporting large wind turbines (15 MW), installed at water depths greater than 40 m and 90 m for the semi-submersible and spar concept, respectively. Special focus is given to develop and validate innovative solutions to improve installation techniques and operation and maintenance (O&M) activities. They will prove the benefits of concrete structures to substantially reduce the LCOE by at least15% compared to the baseline case of bottom-fixed offshore wind, both in terms of CAPEX and OPEX. Additionally, the project will provide guidelines and best design practices, as well as open data models to accelerate the further development of concrete-based semi-submersible and spar FOWTs, based on findings from innovative cost-effective and reliable solutions for the aforementioned key aspects. It is aimed that the resulting recommendations will facilitate the cost-competitiveness of floating offshore wind energy, reducing risks and uncertainties and contributing to lower LCOE estimates. COREWIND aims to strength the European Leadership on wind power technology (and specially floating). To do so, the project consortium has been designed to ensure proper collaboration between all stakeholders (users, developers, suppliers, academia, etc.) which is essential to accelerate commercialization of the innovations carried out in the project.

The focus of the project will be on floating wind turbines installed at water depths from 50m to about 200m. The consortium partners have chosen to focus on large wind turbines (in the region of 10MW), which are seen as the most effective way of reducing the Levelized Cost of Energy (LCOE). The objective of the proposed project is two-fold: 1. Optimize and qualify, to a TRL5 level, two (2) substructure concepts for 10MW turbines. The chosen concepts will be taken from an existing list of four (4) TRL>4 candidates currently supporting turbines in the region of 5MW. The selection of the two concepts will be made based on technical, economical, and industrial criteria. An existing reference 10MW wind turbine design will be used throughout the project. 2. More generally, develop a streamlined and KPI-based methodology for the design and qualification process, focusing on technical, economical, and industrial aspects. This methodology will be supported by existing numerical tools, and targeted development and experimental work. It is expected that resulting guidelines/recommended practices will facilitate innovation and competition in the industry, reduce risks, and indirectly this time, contribute to a lower LCOE. End users for the project deliverables will be developers, designers and manufacturers, but also decision makers who need to evaluate a concept based on given constraints. The proposed project is expected to have a broad impact since it is not led by single group of existing business partners, focusing on one concept only. On the contrary, it will involve a strong consortium reflecting the value chain for offshore wind turbines: researchers, designers, classification societies, manufacturers, utilities. This will ensure that the project's outcomes suit the concrete requirements imposed by end-users.

Emerging technologies as Offshore Wind Energy, demand new advanced solutions for reducing Operation & Maintenance (O&M) costs, as well as for performing the reliability and extended life-time of wind turbines (WT) and farms (WF). In this sense, ROMEO is a 5 years project whose main objective is to develop and demonstrate an O&M information management and analytics platform capable of improving the decision making processes of offshore WF operators allowing the transition from calendar base maintenance to condition-based maintenance strategies reducing significantly O&M costs. Thus, a flexible and interoperable IoT platform will provide 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 the need for maintenance, thus minimizing the OPEX which drastically impact on LCoE of offshore Wind Energy. The project has been structured in three phases: 1st phase “specifications” will pave th

Current practice in wind turbines operation is that every turbine has its own controller that optimizes its own performance in terms of energy capture and loading. This way of operating wind farms means that each wind turbine operates based only on the available information on its own measurements. This gets the wind farm to operate in a non-optimum way, since wind turbines are not operating as players of a major system. The major reasons for this non-optimum approach of wind farms operation are based on the lack of knowledge and tools which can model the dynamics of the flow inside the wind farm, how wind turbines modifies this flow, and how the wind turbines are affected by the perturbed flow. In addition, this lack of tools deals to also a lack of advanced control solutions, because there are not any available tool which can help on developing and testing virtually advanced control concepts for wind farms. CL-WINDCON will bring up with new innovative solutions based on wind farm open and closed loop advanced control algorithms which will enable to treat the entire wind farm as a unique integrated optimization problem. This will be possible thanks to the development of appropriate dynamic tools for wind farm simulation, at a reasonable computing effort. These tools for wind farm dynamic modelling of wind farm models will be fully open source at the end of the project, while control algorithms will be extensively validated simulations, in wind tunnel tests. Some open loop validations will be performed at wind farm level tests. Proposed control algorithms, useful for future but also for already existing wind farms. Then these will improve the LCOE, as well as the O&M costs will decrease, and improves in terms of reliability the wind turbine and wind farm. These performance improvements will be evaluated for both, wind turbine operation and wind farm operation.