OPTIMUS
Demonstration of methods and tools for the optimisation of operational reliability of large-scale industrial wind turbines
| Coordinatore | OFFSHORE RENEWABLE ENERGY CATAPULT
Organization address
address: OFFSHORE HOUSE ALBERT STREET contact info |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 5˙653˙500 € |
| EC contributo | 3˙333˙275 € |
| Programma | FP7-ENERGY
Specific Programme "Cooperation": Energy |
| Code Call | FP7-ENERGY-2012-2 |
| Funding Scheme | CP |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-08-01 - 2016-07-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
OFFSHORE RENEWABLE ENERGY CATAPULT
Organization address
address: OFFSHORE HOUSE ALBERT STREET contact info |
UK (BLYTH NORTHUMBERLAND) | coordinator | 0.00 |
| 2 |
"Dynamics, Structures and Systems International"
Organization address
address: Jules Vandenbemptlaan 71 contact info |
BE (Heverlee) | participant | 0.00 |
| 3 |
Feldman Enterprises Limited
Organization address
address: ANGIOU PAVLOU 15 contact info |
CY (NICOSIA) | participant | 0.00 |
| 4 |
INDRA SISTEMAS S.A.
Organization address
address: Avenida de Bruselas 35 contact info |
ES (ALCOBENDAS-MADRID) | participant | 0.00 |
| 5 |
INGETEAM SERVICE SA
Organization address
address: PG PG. INDUST. CAMPOLLANO 1 contact info |
ES (ALBACETE) | participant | 0.00 |
| 6 |
INSTITUTO DE SOLDADURA E QUALIDADE
Organization address
address: AVENIDA DO PROFESSOR DOUTOR CAVACO SILVA 33 PARQUE DAS TECNOLOGIAS contact info |
PT (OEIRAS) | participant | 0.00 |
| 7 |
ROMAX TECHNOLOGY LIMITED
Organization address
address: RUTHERFORD HOUSE NOTTINGHAM SCIENCE AND TECHNOLOGY PARK contact info |
UK (NOTTINGHAM) | participant | 0.00 |
| 8 |
SINCLAIR KNIGHT MERZ (EUROPE) LIMITED
Organization address
address: ST MARYS PARSONAGE ALBERTON HOUSE 30 contact info |
UK (MANCHESTER) | participant | 0.00 |
| 9 |
TERNA ENERGIAKI ANONIMI VIOMIHANIKI EMPORIKI TEHNIKI ETERIA AE (Terna Energy Industrial Commercial and Technical Company S.A)
Organization address
address: MESSOGION AVE contact info |
EL (ATHENS) | participant | 0.00 |
| 10 |
THE UNIVERSITY OF BIRMINGHAM
Organization address
address: Edgbaston contact info |
UK (BIRMINGHAM) | participant | 0.00 |
| 11 |
THE UNIVERSITY OF SHEFFIELD
Organization address
address: FIRTH COURT WESTERN BANK contact info |
UK (SHEFFIELD) | participant | 0.00 |
| 12 |
UNIVERSIDAD DE CASTILLA - LA MANCHA
Organization address
address: CALLE ALTAGRACIA 50 contact info |
ES (CIUDAD REAL) | participant | 0.00 |
Mappa
Word cloud
Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.
Obiettivo del progetto (Objective)
The power output from wind turbines has increased dramatically over the past thirty years from 50 kW to 6 MW, while 8-12 MW turbines are in the stage of design. State-of-the-art condition monitoring systems, such as vibration-based systems and temperature sensors, are able to monitor and evaluate the current condition of components of interest. Nonetheless, varying wind loads can result in the generation of false alarms or even misinterpretation of the data collected. In addition, commercially available condition monitoring systems offer no or very limited prognostics capability with regards to the remaining lifetime of a component before a serious fault occurs. Therefore evolution to predictive maintenance strategies is currently impossible. Experience has shown that by combining disparate data sources wind farm operators will be able to move from common reactive maintenance approach to a more cost effective risk-based operation and maintenance strategy with a high level of predictive maintenance scheduling. OPTIMUS will develop and demonstrate in the field novel methods and tools for prognosis of the remaining lifetime of key components based on data acquired by a cost-effective wind turbine condition monitoring system implemented by custom-designed dependable computing systems. This technology will reduce the total cost of energy and advance the deployment of large scale offshore and onshore wind energy by increasing availability and reducing downtime due to unplanned maintenance. Predictive maintenance will also reduce costs incurred from secondary damage to components and enable maintenance activities (and the associated costs) to be optimized with respect to forecast revenue from power generation. The results of this project will lead to a significant step-change over the current capability of commercial condition monitoring systems.