Title :
GM (1,1) model application in power load forecasting based on moving average method
Author :
Qian Zhu ; Xiangdan Jia
Author_Institution :
Econ. & Bus. Dept., Hebei Finance Univ., Baoding, China
Abstract :
Grey prediction has advantages of need less historical data, foperating speed is fast, algorithm is simple, easy to test, so it is suitable for use in power load forecasting. But grey model has some limitations, the data dispersion degree is more bigger, the gray is also more bigger, it will reduce the accuracy of prediction. This paper adopts the moving average method to improve the raw data, so as to increase the data weights, while avoiding predicted value excessive volatility, So it can improve the load forecast accuracy.
Keywords :
load forecasting; data dispersion degree; grey model; grey prediction; moving average method; power load forecasting; Analytical models; Data models; Error analysis; Load forecasting; Load modeling; Mathematical model; Predictive models; Grey prediction; Load forecasting; Prediction accuracy; Sliding average method;
Conference_Titel :
Instrumentation and Measurement, Sensor Network and Automation (IMSNA), 2013 2nd International Symposium on
Conference_Location :
Toronto, ON
DOI :
10.1109/IMSNA.2013.6743271
