Many technological systems that are composed of technical parts embedded in human, organizational, and environmental contexts can be categorized as complex systems. They have various interactions and a nonlinear relationship between their components. They are also open to their environment and make exchanges with it. Almost all traditional risk assessment techniques, such as Failure Modes and Effect Analysis (FMEA), Hazard and Operability Analysis (HAZOP), Fault Tree Analysis (FTA), and Probabilistic Risk Analysis (PRA) rely on a chain of linear cause and effect analysis. These techniques also have some limitations in terms of incorporating efficient links between risk models and human and organizational factors for studying modern complex technological systems. This paper generally reviews existing approaches of risk assessment for complex technological and specifically studies risk assessment of wind turbines. Then it proposes an integrated risk assessment framework for complex technological systems through a Bayesian network considering various system levels and their interaction using a cause and effect approach. Since wind turbines are instances of complex power generating systems consisting of several structural, electrical, and mechanical components interacting with human resource and organizational factors within natural, political, economic, and social environments, the proposed model is applied to assess risk and reliability in a wind turbine. Different scenarios of reliability analyses were investigated, which illustrated that Bayesian networks are effective for the reliability assessment of the chosen system and very useful for understanding the system behavior.
