Extremely short-term wind speed prediction based on RSCMAC

Abstract

Wind power is an intermittent and unstable energy. In recent years, wind power system installation fields are getting more and more, the installation capacities are getting larger and larger, therefore, the stability of the wind power system is becoming very important. This research completed building a wind power system model and developed extremely short term wind power forecasting system. In the part of building wind turbine model, it is based on realistic wind turbine operational data and applies to a traditional wind turbine mathematical model to find the best Betz coefficient of a wind turbine model Vestas 80 (Denmark), then based on Recurrent S_CMAC_GBF (RSCMAC) to build a new RSCMAC wind turbine model. Comparison confirmed the better results of RSCMAC wind turbine model achieved. In the part of developing extremely short term wind speed forecasting system, the meteorological stations were set up around the forecasting fields to collect relevant information and based on RSCMAC to develop an extremely term wind speed forecasting system; the results show the forecast feasibility and effect. In the future, this forecasting system can be applied as the reference for the application of wind farm evaluation or wind energy prediction.