Title :
Forecasting model for the solar photovoltaics consumption in United States of America
Author :
Thanh-Lam Nguyen ; Ying-Fang Huang ; Ming-Hung Shu ; Bi-Min Hsu
Author_Institution :
Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan
Abstract :
Sunlight is the most abundant energy resource for human beings. Solar photovoltaics is a green energy which is playing a critical role in helping many countries fight against climate change, ensure enough supply for power security, and reduce their dependency on energy imports. Thus, it is considered important to build a good statistical model to forecast the consumption amount so that relevant authorities can create proper policies for the stable development of this green industry. In this study, a new forecasting model named FARINA was proposed by combining the Fourier residual modification with the traditional FARINA forecasting model. In the case of forecasting the solar energy consumption in the United States of Amercia, FARIMA(1,1,1)(1,1,1)11 model has a very low value of the mean absolute percentage error (NAPE) of 0.08% and this model is strongly suggested to do the forecasting.
Keywords :
Fourier analysis; autoregressive moving average processes; climate mitigation; energy consumption; photovoltaic power systems; solar power stations; statistical analysis; sunlight; FARIMA(1,1,1)(1,1,1)11 model; FARINA forecasting model; Fourier residual modification; NAPE; United States of America; climate change; energy resource; mean absolute percentage error; power security; solar energy consumption; solar photovoltaics consumption; statistical model; sunlight; ARIMA model; FARIMA; Fourier modification; energy consumption;
Conference_Titel :
IPEC, 2012 Conference on Power & Energy
Conference_Location :
Ho Chi Minh City
DOI :
10.1109/ASSCC.2012.6523279