The wind power producers in India are obliged to give a forecast of their power in advance as per Indian Electricity Grid Code 2010 (IEGC). This work explores Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to forecast the average hourly wind speed. To obtain ANFIS that best suited the wind speed forecasting system, several ANFIS models were trained, tested, and compared. The results for the short term wind speed forecast using the available data have been studied. A typical Supervisory Control and Data Acquisition (SCADA) system is modeled to transfer data to a forecasting system in the host computer loaded with ANFIS and also to communicate the output to the State Load Dispatch Centers (SLDC). With the constraints of data and computation capability, the proposed wind speed forecast work is expected to deliver better wind power forecast results, when the required inputs are given. The presented work deals with the methodology which can be used by the Wind power producers with appropriate facilities and tools on a larger scale.
S. R. Nandha Kishore and .Vanitha, V., “Wind speed forecasting for grid code compliance”, Journal of Renewable and Sustainable energy, 2013.