HYPERWINDGlobal and systemic monitoringof offshore renewable power systems

What is the project?

How to reach this goal? Which are the deliveries of HYPERWIND?Ÿ Provide a hyper vision system for renewable power farms Offshore and Onshore.Ÿ Provide a comprehensive and systemic monitoring system of all plants components

associated with a global model to take into account, very early, the discrete signals.Ÿ Provide a reliable remote monitoring system and easy to interpret by end users.Ÿ Development of a methodology of construc�on of models and indicators on various

machines including other domains of the Marine Renewable Energies.Ÿ Present a demonstrator on a wind turbine equipped and func�onal (onshore wind)

HyperWind is a project to develop a comprehensive monitoring system for Offshore and On Shore wind turbines. This system is composed of various sub-systems (blade system monitoring, SHM on gearboxes, SHM sha�ing line, ...) interconnected with a global and systemic vision of wind turbine and its rela�ve posi�oning to known points of dysfunc�on.

This project intends to propose the construc�on of a methodology for modeling system behavior and so high levels indicators and its implementa�on using a prototype of a pilot plant.

The goal is to provide operators of a wind plant a systemic and dynamic view of their facili�es and the plant as a whole. The assump�on here is such that the overall integra�on of complete system will refine the understanding of dysfunc�ons or altera�ons and this as soon as possible. Moreover, this global integra�on and its interpreta�on via a set of models will guide the control strategy of the system. And, more generally, this system will adapt the control strategy of the plant func�on of external system constraints (energy demand, evolu�on of the primary resource .... ) but also the velocity of signal evolu�on as possible malfunc�ons expressing.

HYPERWIND benefit from the support of:

Dominique FOLLUT, PhDR&D DirectorKEOPS Performance Groupd.follut@keops-group.com

Meteodyn, interna�onal expert in wind engineering and climatology, brings together a team of specialist in fluid mechanics, I.T., Meteorology and Sta�s�cs.Computa�ons and simula�ons of the climate take into account effects of all kinds of terrains and environments at every spa�al scales, in real �me or days ahead.

The DUKe (Data User Knowledge) research group, part of the LINA laboratory (UMR CNRS 6241), University of Nantes, aims at proposing querying, mining and learning techniques that take into account (1) data types (rela�onal, spa�al, graphical, temporal, stream, etc.), uncertainty, privacy or (2) expert knowledge or user interac�ons through adapted visual supports

Developer of performance, KEOPS Automa�on specialises in the automa�on and monitoring of industrial processes. By the supply of turnkey systems and expert services, KEOPS Automa�on improves the produc�vity of industrial installa�ons.

École des Mines de Nantes – a public body of higher educa�on and research – is associated with four CNRS and one EA joint research units. Both fundamental and applica�on-oriented research is designed for use in business and in society, through research contracts, and technology transfer, and public awareness.

We develop and engineer cu�ng-edge and peerlessly reliable products in the fields of defence and space. Our constant ambi�on is to connect and protect lives.Nowhere are technology and engineering requirements more stringent and demanding than in the fields of defence, security and space exploita�on. Airbus Defence and Space unites a range of capabili�es and skills unrivalled anywhere in the world.

Net-Wind is an independent company posi�oned on the windmills maintenance market with a full-service or speciality-service offering.Our ambi�on is to listen to our customer requirements and to offer a high quality service within the deadlines.

Contact:

Relevant rawdatas

Filtered datas

Aggregation modelof of the weak signals

Data for Follow-up

High level indicators

Bayesian model of facts-causes association

LiBalanced listof the likely failures

Management model ofmaintenance constraints

Probabilistique calculationof temporal evolution

Board for sequencing the tasks

Seasonal statistics

Operationalforecast(5 days)

Local corrected meteo data

Model of micro-climaticcorrection

Local setting-up model

Meteo forecast flow

Piloting installationsand maintenance

Action

Preventive maintenance

Safety management

Powermanagement

(loss of production)

AMDEC