Research of Power Prediction of Wind Farm Based on Sequential Index Smoothing Method

Autor: LU Yong-fang, CHENG Zhi-lei, WANG Xiao-wei, LIU Ying-ying
Jazyk: čínština
Rok vydání: 2012
Předmět:
Zdroj: Gong-kuang zidonghua, Vol 38, Iss 8, Pp 75-78 (2012)
Druh dokumentu: article
ISSN: 1671-251X
Popis: In view of problems that existing wind power prediction methods have short prediction time and low prediction accuracy, and it ca't track characteristics of volatility and intermittent of wind power generation to get reliable prediction, the paper put forward a new prediction method based on sequential index smoothing method (SIMS). Firstly, the method gets rid of distorted data from the original data by use of exponential smoothing method to get more ruled power data. Then it uses feedback time sequence method to predict power data. Using the method to make a prediction for the next day of four wind turbines for a large wind farm, the result is coincided with the actual measured data, which proved the method is feasibility.
Databáze: Directory of Open Access Journals