Short -term wind power plant predicting with Artificial Neural Network

In modern years, wind energy has a significant development in the world. However, one of the major issues of power generated from wind is its uncertainty and resultant power. To solve the above- said problem, few approaches have been presented. In recent times, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. The Back-propagation (BP) neural network is then provided with the data to establish the relationship between the inputs and the output. Measured wind speeds, temperature, pressure and wind speed predicted outputs with each 10-min resolution for 15^th January 2015(24 hours) an existing wind power station, located at VSB-TUO, Ostrava, are integrated to form three types of input neuron numbers. In this, paper presents a short -term power prediction for a wind power plant located at VSB-TUO, Ostrava using multilayer ANN approach. Simulation results are reported, showing that the estimated wind speed values (predicted by the proposed network) are in good agreement with the experimental measured values.