Abstract
The increased level of embedded wind energy generation systems in smart grids posed increased daily challenges because of the intermittent nature of these systems. Forecasting of the generated power from the wind energy systems helps to deal with these challenges. In this paper, a proposed forecasting system for short term wind power prediction is presented. The proposed system is used to increase the accuracy of the forecasted value by creating multiple small datasets with the same features of the main dataset. A neuro-fuzzy model is created for each dataset. The output of each neuro-fuzzy model represents a forecasting of the wind turbine power (WTP). Thereafter, the output of all models is combined using a combination model to calculate the final forecasted WTP.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
