Abstract
Measurement Model is the main approach for short-term power generation prediction of a wind turbine generator system (WTGS), which utilizes the relationship between power generation and wind speed. This paper introduces genetic neural networks (NN) technique for wind speed and power generation prediction of a wind turbine generator system. Firstly, the following 3 hours wind speed was predicted by means of Neural Network with measured wind speed data of latest 24 hours, and then the wind power generation was forecasted based on the standard power curve of the WTGS. In order to test the predict precision different neural networks (NN), this paper also compares three NN models: standard BP, Momentum BP and Genetic Algorithm. The results show that Genetic Neural Network is a more effective and accurate method to predict wind speed and wind turbine power generation.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.