An online, risk driven condition monitoring, predictive maintenance management and design upscaling tool for wave energy devices
RISKMAN is a maintenance management tool which will be developed as an enabling technology for reducing wave energy convertor (WEC) devices levelised cost of electricity (LCOE) to compete with other energy systems. RISKMAN aims to provide a step reduction in Albertern WaveNet WECs capital and operational expenditure (CAPEX/OPEX) and increase in availability times through:
- Condition Monitoring of critical components of the WEC arrays by a suite of embedded complementary sensors;
- Transmitting sensor output (electrical) signals to onshore in real time through electro-optical conversion and fibre optic cables for cloud computing;
- Assembly of the historic data into a reliability database, essentially a library of structural health signatures and norms; and
- construction of a risk driven predictive maintenance system (PMS) which combines the database with mathematical models to determine for each component a probability distribution function to give the RISK of failure over any time period.
Condition monitoring of critical components of wave energy devices. Development of risk driven predictive maintenance system combining mathematical models and big data analysis.
Reduction in CAPEX/OPEX through condition monitoring of WECs providing improved security of supply and reduction in levelised cost of electricity to compete with other renewable energy systems.
ALBATERN , TWI, BRUNEL UNIVERISTY LONDON
This project was co-funded by the UK’s innovation agency, Innovate UK.