Wind Field Reconstruction Based On CFD Information And Data Reduction Method

Short-term wind forecasting is important in updating wind electricity trading strategies,facility protection and more effective operation control.Physical based models,particularly those using computational fluid dynamics(CFD),are able to provide ever more detailed wind speed data.However,such methods involve handling a huge amount of CFD data,which is prohibitively time consuming for a short-term wind forecast in real situations.To solve this problem,Principal Component Analysis(PCA)algorithm is applied in this study to reduce the dimensions of wind speed data substantially.The novelty of the proposed method in this study is that CFD simulations and sparse sensor measurements are combined together based on PCA and Least Squares method to reconstruct wind field distributions.The investigation in this paper is divided into simulation and experimental work.Comparison and error analysis of the data from each of them are carried out.In this study,wind fields have successfully been reconstructed with good accuracy for the inlet wind direction angles ranging from 10° to 90° and the inlet wind speed ranging from3.5m/s to 33.5m/s.The accuracy of the proposed reconstruction algorithm increases with the sampling rate of the measurement,which is only recognizable below a certain value of sampling rate.The locations of the sensors do not significantly affect the accuracy of the results.Gaussian noise introduced into the input signal does not significantly deteriorate the reconstruction quality.The effectiveness of the proposed model in this paper has been validated by a wind tunnel experiment.The numerical simulation results and experimental results show that the method can be used quickly and accurately for the reconstruction of the wind field.The research results in this paper greatly improve the speed of wind field reconstruction.At the same time,only a small amount of measured data is used to reconstruct the wind field in real case,providing a new way to improve the utilization of wind power.