TITLE:
Very Short-Term Generating Power Forecasting for Wind Power Generators Based on Time Series Analysis
AUTHORS:
Atsushi Yona, Tomonobu Senjyu, Funabashi Toshihisa, Chul-Hwan Kim
KEYWORDS:
Very Short-Term Ahead Forecasting; Wind Power Generation; Wind Speed Forecasting; Time Series Analysis
JOURNAL NAME:
Smart Grid and Renewable Energy,
Vol.4 No.2,
May
29,
2013
ABSTRACT: In recent years, there has been introduction of alternative energy sources such as wind energy. However, wind speed is not constant and wind power output is proportional to the cube of the wind speed. In order to control the power output for wind power generators as accurately as possible, a method of wind speed estimation is required. In this paper, a technique considers that wind speed in the order of 1 - 30 seconds is investigated in confirming the validity of the Auto Regressive model (AR), Kalman Filter (KF) and Neural Network (NN) to forecast wind speed. This paper compares the simulation results of the forecast wind speed for the power output forecast of wind power generator by using AR, KF and NN.