DOCTORAL POSITION (R1): Condition-Based Maintenance Planning for Wave Energy Technology through Prognostics & Health Management Strategies

Offshore renewable energy technologies such as offshore wind, tidal or wave energy have the potential to support traditional renewable energy sources (e.g., solar, onshore wind) and contribute to the energy mix in the short-medium term. Wave energy is an emerging area where the motion of ocean waves can be converted into electricity. Several different technologies have been suggested by developers & researchers [1], but all include different components to convert mechanical energy into electricity [2,3], which have a significant impact on the final performance of the wave energy devices and require relatively frequent maintenance. However, the nature of the operating environment generates operation and maintenance challenges that hamper the wide implementation and adoption of the wave energy technology.

There are different electrical and mechanical assets that take part in the wave energy conversion and distribution processes such as turbines, converters, generators, batteries, transformers, cables, or circuit breakers. The operation and degradation processes of these components are well studied in the context of traditional power grids [4-6]. In the context of wave energy, open sea and weather conditions determine when it is possible to travel to the offshore power plant and perform maintenance actions. These travel time instants are known as weather windows. Accordingly, failures of system components can result in prolonged periods of downtime and this situation limits the benefits of wave energy applications. In this context, effective risk management and maintenance planning are crucial activities for the effective implementation and adoption offshore technologies.

Thanks to the modern technologies and increasing monitoring systems there is room to optimize operations and improve risk management and maintenance planning through risk monitoring, prognostics, and health management (PHM) applications, e.g. [7, 8]. Namely, it is possible to monitor the health state of the assets that take part in the wave-to-electricity energy conversion process and determine optimal maintenance strategies. This process will require modelling the health state of various components along with sea and weather operation conditions and inferring a maintenance planning strategy. This strategy will have to evaluate the risk of failure of components, cost of maintenance actions and weather windows, and accordingly elicit optimal maintenance windows. This process will involve the development and application of PHM techniques via engineering knowledge combined with artificial intelligence and reliability methods.

There are two pioneering offshore facilities in the Basque Country, both owned by the “Ente Vasco de la Energía” (EVE). The Mutriku Wave Power Plant in Mutriku  and the testing site located in Armintza. The plant located in Mutriku was launched in 2011 and there are different power assets monitored and tested in the power plant for years (transformers, air turbines, generators). In addition, IDOM/Oceantec developed the wave energy generator MARMOK-A-5, which was deployed in Armintza for the last two years (funded by the Opera H2020 project). In this project, there have been tested and collected datasets for different assets.