Vestas Wind Systems A/s

Martin Qvist

Morten Tim Thorsen

Niels Erik Danielsen

Jan Krogh Jensen

Jesper Schmidt

Tomislav Maric

Anders Rhod Gregersen

Mehran Nourbakhsh

Line Storelvmo Holmberg

A method for forecasting power production of at least one wind turbine, the wind turbine forming part of a wind farm arranged at a site. Global weather forecast data is received at a central data centre. A site specific forecast is then generated at the central data centre, based on the global weather forecast data. The site specific forecast from the central data centre is sent to a local data centre, e.g. arranged at the site of the wind farm. Site specific data is received at the local data centre and comprises site specific weather data and/or site specific wind turbine data measured at the site. The site specific forecast is then updated at the local data centre, using the site specific data. Finally, a power production forecast of the at least one wind turbine is generated based on the updated site specific forecast.

Power production forecasting for a wind turbine

A control system for one or more wind turbines comprising an RF receiver used as a method for adaptively controlling the noise mode of operation of a wind turbine. Preferably, this involves multilateration to determine location of RF sources near wind turbindes of a wind turbine park. The RF receivers would detect nearby RF signals in multiple spectrums, in particular mobile telecommunication signals (GSM/UMTS), to identify and localize RF sources near to the wind turbine(s). This information is then be processed to identify which RF sources are likely to be linked to a real person near the wind turbine, and this can be used to adjust the noise mode of the wind turbine accordingly. Thereby maximizing energy production from the wind turbine in absence of nearby people, while keeping noise low when people are nearby.

Adaptive noise control for wind turbine

A method, controller, wind turbine, and computer program product are disclosed for processing and analyzing wind turbine operational data in a distributed data analysis system. An example method generally includes obtaining, at a first data analysis system, operational data from a plurality of wind turbines in a first wind power plant, determining adjustments to wind turbine operational parameters based on the operational data, pushing the adjustments to the first wind power plant, transmitting the operational data to a second data analysis system not located at the first wind power plant, and transmitting the operational data from the first wind power plant and at least a second wind power plant to a third data analysis system, wherein the third data analysis system comprises a global data analysis system.

Distributed data analysis system for wind power plants background

A method, controller, wind turbine, and computer program product are disclosed for collecting data from wind turbines in a wind farm. An example method generally includes receiving, from a client device, a subscription request identifying a plurality of data points to collect from a set of wind turbines. A wind farm server establishes a client interface with the client device. The wind farm server receives data points form the plurality of wind turbines and buffers the identified collected data points from the set of wind turbines in a data repository. Through the client interface, the wind farm server receives a request for data points collected from at least one wind turbine over a specified time period, and responsive to the request, transmits the requested data points to the client device. The wind farm server also may push collected data points from wind turbines to a data analysis system.

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Højbjerg, Denmark

Martin Qvist