Application of Quantum Bayesian Network in the Reliability Analysis of Offshore Wind Turbine Generator

As energy demand grows worldwide and the impact of climate change, renewable energy sources have become increasingly prominent in the global energy transition, especially offshore wind farms, which benefit from stronger wind conditions. However, due to the effects of wind and waves on wind turbines, assessing their reliability is essential. In this study, quantum computing was employed as an alternative approach to estimate the probabilities in a Bayesian Network model of a floating offshore wind turbine generator. The quantum version of the model was implemented on a quantum circuit with 22 qubits, simulating service times of up to 10 years, with 10 executions performed for each service time using a quantum simulator. The results, when compared to the exact solution, showed error values close to zero, indicating that quantum computing can be effective for applications of this nature.