Title :
72hr forecast of wind power in Mani̇sa, Turkey by using the WRF model coupled to WindSim
Author :
Efe, B. ; Unal, E. ; Mentes, Sibel ; Ozdemir, T. ; Unal, Yavuz ; Barutcu, Burak ; Tan, Ee Leng ; Onol, Baris ; Topcu, Satilmis
Author_Institution :
Dept. of Meteorol. Eng., Istanbul Tech. Univ., Istanbul, Turkey
Abstract :
Wind power forecasting has recently become important to fulfill the increasing demand on energy usage. Two main approaches are applied to the wind power forecasting which can vary from 6 hours to 48 hours. One way is to model the atmosphere dynamically and the other method is to analyze wind speed and direction statistically. Although dynamical models forecast better than statistical models, since the former solves the problem physically, statistical models can be preferable when short term forecasting is needed due to their quick response time. Most of the currently available wind power forecasting systems analyzes the effect of wind field on wind power based on numerical weather prediction models. However, the resolution of these models is not sufficient enough when the scale of the turbines on the wind farms is considered. It is possible to overcome this problem by using computational fluid dynamics (CFD) models, which can provide both linear and nonlinear solutions on the turbine scale in terms of both wind speed and wind power forecasting. In this study, the WRF model is used for 72-hour wind speed and direction forecasting. The initial and boundary conditions of the model are provided by ECMWF operational forecasting data with the resolution of 0.25 degree. The WRF model is downscaled to 1 km resolution over Manisa Soma wind farm and 72-hour forecasts for each day of 2010 are accomplished. WindSim uses wind speed and direction values, which are solved on the nearest grid point of the WRF model to the location of a wind turbine, to simulate high-resolution wind speed values for 72hours. These WRF to WindSim coupled model results are compared to the wind power observations. As a result, we found that daily wind power generation errors per turbine vary between 90kW and 200kW for the seasons of spring, summer, and fall, whereas the error is about 150-350kW for winter. We also compared the errors of 24 hourly model outputs and we found that there is no significant- difference among the first, the second, and the third 24 hourly forecasts. We finally applied model output statistics to the WRF to WindSim coupled model results in order to minimize their errors.
Keywords :
computational fluid dynamics; load forecasting; prediction theory; statistical analysis; wind power plants; wind turbines; CFD models; ECMWF operational forecasting data; Manisa Soma wind farm; Turkey; WRF model; WindSim; computational fluid dynamics; daily wind power generation errors per turbine; direction values; dynamical model forecasting; energy usage demand; high-resolution wind speed; numerical weather prediction model-based wind power; power 150 kW to 350 kW; power 90 kW to 200 kW; response time; short term forecasting; statistical models; time 72 hour; wind power forecasting; wind speed analysis; wind turbine; Atmospheric modeling; Computational modeling; Numerical models; Predictive models; Wind forecasting; Wind power generation; Wind turbines; Manisa Turkey; WRF; Wind Energy Prediction; WindSim;
Conference_Titel :
Renewable Energy Research and Applications (ICRERA), 2012 International Conference on
Conference_Location :
Nagasaki
Print_ISBN :
978-1-4673-2328-4
Electronic_ISBN :
978-1-4673-2329-1
DOI :
10.1109/ICRERA.2012.6477345