WindSENSE Project Explores Turbine Speed Impact

US researchers have launched a programme that aims to produce wind turbine software able to help turbines better adapt to rapid wind speed changes. The programme's known as WindSENSE and the Office of Energy Efficiency and Renewable Energy - part of the US Department of Energy - is funding it.

Based at Lawrence Livermore National Laboratory (LLNL), the researchers are basically developing technology capable of carrying out 24-hour wind energy predictions. "One of our goals is to help the people in the control room at the utilities determine when ramp events [swift wind speed shifts] may occur and how that will affect the power generation from a particular wind farm", head researcher Chandrika Kamath explained in a recent laboratory press release.

Wind Turbines: Speed Impact

So far, she and her colleagues have assessed wind conditions in two areas - Southern California's Tehachapi Pass and the Columbia Basin, which straddles Washington and Oregon. Employing techniques used in data-mining, they've tried to establish if local weather conditions can inform the likelihood of future ramp events, i.e. moments when wind speeds suddenly shoot up or down and the impact these have on turbines.

Wind turbine arrays located in the Tehachapi Pass presently produce a baseline capacity of 700 megawatts, with over 2GW set to be added in years to come. Meanwhile, the Columbia Basin's farms currently generate more than 3GW. LLNL's research team now thinks it's possible that the effect of ramp events can alter both these outputs by more than a gigawatt over the course of less than an hour.

WindSENSE Project

"Our work identified important weather variables associated with ramp events", Kamath explains in the WindSENSE project update release. "This information could be used by the schedulers to reduce the number of data streams they need to monitor when they schedule wind energy on the power grid.

"We're trying to reduce the barriers to integrating wind energy on the grid by analyzing historical data and identifying the new data we should collect so we can improve the decision making by the control room operators", Kamath concludes. "Our work is leading to a better understanding of the characteristics and the predictability of the variability associated with wind generation resources."

Enviro News will look again at the WindSENSE project in future News Coverage

Image copyright Ikluft - Courtesy Wikimedia Commons

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