In this work, the societal risk (SR) technique is applied considering the capacity of power generation by a wind power system, according to the following equation: (2) SR = A · N
... data clearly shows that blade failure is the most common accident with wind turbines, closely followed by fire. Figure 4 shows a chronological summary of the previous mentioned accident table. The trend is as expected -as more turbines are built, more accidents occur. [...]
Without full access to all wind turbine accidents and their details, it is impossible to prove that the data used in the present study or related studies truly represent all wind turbine accidents.
The tabular and visual analyses relate accidents to location (offshore vs. onshore), wind turbine life cycle phases (transportation, construction, operation, and maintenance), and the incidence of death and injury. As one of the insights, more incidents were found to occur during operation and transportation.
The first factor is the stage of the life cycle of the wind turbine at which the accident occurred, and the second factor was the cause of the wind turbine accident, namely, nature, system and equipment, or humans. The two outcomes were the occurrence of death, the occurrence of injury, or a combination of the two.
Such a full dataset cannot practically be constructed by an independent research team, because it would not be possible to convince all wind turbine manufacturers to share all their data on accidents, let alone convince even one manufacturer.
We used data mining methods to predict death and injury incidences from text data in wind turbine accident news reports, and our study thus falls into this category, both with respect to the type of data collected and the application of data mining methods.
