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Garrad Hassan break the 3GW mark with GH Forecaster |
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Written by jonathan pitzer
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Tuesday, 11 March 2008 |
Garrad Hassan (GH) announces reaching its target for 2007, providing reliable forecasts for 3GW of wind energy worldwide. GH Forecaster is a state of the art short term forecasting service used and trusted by grid operators, wind farm owners and energy traders. GH provides online forecast services for clients in 9 countries across 4 continents.
GH Forecaster is a state of the art short term forecasting service used and trusted by grid operators, wind farm owners and energy traders. GH provides online forecast services for clients in 9 countries across 4 continents. Comment from Andrew Tindal, GH Director:“As the world wind energy industry booms, with 20GW of new installations in 2007 (Global Wind Energy Council, January 2008) the issue of integrating power from wind farms into the electrical grid and trading wind on energy exchanges are becoming some of the most important issues facing the wind industry. State of the art forecasting such as the service we offer is a key part of the solution to these issues. GH has a global reputation for expertise in predicting the energy production of wind farms over the long term, and I am pleased that we are developing an equally strong reputation in the rapidly growing international market for short term forecasting, as evidenced by GH now forecasting for 3GW of wind in 9 countries.” GH Forecaster adopts a combined physical/statistical approach. The method utilises weather model inputs from a number of approved suppliers and enhances this data to the site-specific conditions. The refinement of the weather model input and conversion to wind farm power is achieved through the application of high resolution models accounting for the topography and turbine wake effects, and through statistical routines that “learn” using feedback from the site. The combination of data from weather model suppliers provides additional service reliability due to redundancy of input data, and improves forecast accuracy by enabling the application of ensemble forecasting techniques. |
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Last Updated ( Thursday, 20 March 2008 )
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