A Risk-Based Approach to Automate Preventive Maintenance Tasks Generation by Exploiting Autonomous Robot Inspections in Wind Farms

In this paper, we dealt with some problems of operation and maintenance in wind farms. We focused on the main critical aspects of any maintenance strategy, which must include the identification of the plant elements to inspect as well as the planning of the possible actions aimed at minimizing production losses. At the same time, any maintenance strategy must take into account the possible costs. In fact, those decisions can be made based on risk-based methods. We designed a risk-based maintenance approach to plan inspection tasks to be assigned to service robots in wind power plants. A supervisory control and data acquisition (SCADA) system is employed to collect and manage suitable data (power, wind velocity, and related machine events), and the risk is evaluated on a daily basis over the data collected. The evaluation of the risk is strictly related to the healthiness of the power plant itself. Then, the tasks are created and scheduled based on a certain priority, which is strictly correlated with the evaluated risk. For the analysis of our approach, we used the real data collected on a wind power plant in Greece over 396 days. The power plant is capable to produce an overall power of 7.2 MW, and it is composed of eight wind turbines of 900 KW per each. We observed that, out of 396 days, 50 days presented machine events leading to a related risk evaluation for which our approach will produce 258 inspection tasks. From this analysis, we conclude that the application of the risk-based methodology paired with the exploitation of permanent robots on the field could result in a 225-MWh reduction of the plant's lost production, in other words, an increase of production of 45.6%.