AWS Truepower LLC, a provider of renewable energy consulting and information services, and Lawrence Livermore National Laboratory (LLNL) have conducted a multi-phase wind forecasting research project known as WindSENSE.
The project, funded by the U.S. Department of Energy's Energy Efficiency and Renewable Energy program, was designed to develop an observation deployment system and improve wind power generation forecasts. AWS Truepower's primary role in the WindSENSE forecasting project was to identify the locations and sensor types required to improve short-term and extreme-event forecasts.
The team used an Ensemble Sensitivity Analysis (ESA) approach to identify specific locations and variables. The study resulted in important forecasting tools that alert control-room operators of wind conditions and energy forecasts during extreme conditions. The use of ESA, along with an analysis of a sample of ramp cases, can provide guidance on where and what to measure in order to improve the prediction of these events, AWS Truepower explains.
‘The observation targeting research conducted as part of the WindSENSE project resulted in the development and testing of algorithms that provide guidance on what weather variables to measure and where to measure them in order to improve wind forecast performance," says John Zack, director of forecasting at AWS Truepower. ‘These new software tools have the potential to help forecast providers and users make informed decisions and maximize their weather sensor deployment investment.’
