A model based on multivariate regression analysis to model the historical behavior of U.S. manufacturing energy consumption is presented. The model relates the energy consumption to important factors such as energy prices, structural shift, etc., that affect the energy consumption. The model has the advantages of being simple and able to incorporate the effect of energy measures on energy consumption. The energy savings resulting from Industrial Assessment Center (IAC) program recommendations are incorporated into the model to project the impact of IAC energy conservation recommendations on future U.S. manufacturing energy consumption. This projection assumes that these recommendations are adopted gradually over all small-to-medium U.S. manufacturing plants. The results include the projected energy consumption with and without the impact of IAC recommendations; this will give more insight on the impact of the IAC program in future U.S. manufacturing energy consumption. The results shown that the energy consumption of the U.S. manufacturing sector would increase by 10.5% from 2005 to 2015, but if the IAC recommendations are implemented on a gradual basis to all small to medium size plants, the energy consumption is forecasted to rise by only 7.8%.
[1]
J. A. Eggebrecht,et al.
Benefits of Multi-day Industrial Center Assessments for Large Energy- Intensive Facilities 1
,
2003
.
[2]
Elizabeth A. Peck,et al.
Introduction to Linear Regression Analysis
,
2001
.
[3]
Patrick E. Phelan,et al.
Forecasting the electricity consumption of the Mexican border states maquiladoras
,
2004
.
[4]
J. M. Roop,et al.
Analysis of energy-efficiency investment decisions by small and medium-sized manufacturers
,
1996
.
[5]
Steven C. Wheelwright,et al.
Forecasting methods and applications.
,
1979
.