In this research, a new approach to monitor and maintain wind power plants using the digital twin technology is proposed. As one can build a dynamic virtual model of the wind farm in general, one can expect to achieve the operational efficiency, reliability and lifespan of the wind energy systems offered by this approach. A set of sensors distributed around the facility provide real time data and updating the image on the computer allows an “image” to be maintained of the physical objects and their healthy behaviour. This real time integration of the system facilitates the continuous performance analysis, proactive maintenance, swift fault identification, energy saving and minimizing environmental impact. The digital twin helps to identify poorly-performing turbines in real-time and anticipate potential failures to take the required interventions. For the operational and maintenance planning, historical or real-time data can be used to minimise downtime and operational costs, while maximising safety and reliability of the system. In addition, adding the most recent analytics and machine learning can help increase the amount of faults, leading to the wind farm's better overall performance and stability. The trend suggests that digital twins technology will become a new management solution for wind energy in the future.