Engineers to utilise Big Data to Create Smart Wind Farms

Published: 18 Oct 2017 By Matt Cook

Engineers are continuing to improve and redevelop wind turbine designs and improve the efficiency and reduce costs associated with wind power generation. Whilst new technology has benefits of increasing turbine outputs, the research and development process can incur massive costs and consequently reduce the benefits of introducing this new technology.

Engineers utilise big data for Wind Farms

Engineers are now broadening their development strategy to look at a wind farm as an entirety, rather than focusing specifically on individual turbine designs.

The Department of Energy believes in a future with wind farms being developed based on a SMART energy strategy. Engineers are exploring methods to create wind turbines that communicate and cooperate, working together, rather than individually.

Wind farms of today are generally developed with turbines spaced apart and facing directly into the wind to utilize as much wind power as possible. Research has suggested that when turbines in the front row of a wind farm gather as much wind as possible, the overall operation of the farm produces less electricity. In contrast, when the leading edge turbines allow more wind to pass to other turbines, the whole wind farm will achieve higher levels of efficiency and production.

Adopting a SMART energy approach and using a wind farm controller which provides real-time weather conditions. This technology will allow certain turbines to rotate slightly away from the wind or adjust blade pitch in order to steer winds away from downstream turbines, allowing those turbines to perform more efficiently.

High-Fidelity Modelling (HFM) is another advanced technique using a set of transducers to measure certain parameters such as wind velocity, direction, and turbulence. Utilising the data from these sensors, along with the wind farm controllers maximises energy production by utilizing the optimum conditions for wind power generation. The data from this system will provide essential information on turbine loads and allow engineers to optimise maintenance and predict any component failures, reducing the costs associated with wind farm operations.

High fidelity modeling will assist engineers and scientists in accurately measuring and predicting overall wind patterns. The big data available to engineers will be essential in designing the most efficient and cost-effective wind farms of the future.

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