A model for Long-term Industrial Energy Forecasting (LIEF)

Technical Report · Sat Feb 01 00:00:00 EST 1992

DOI:https://doi.org/10.2172/5718054· OSTI ID:5718054

Ross, M ^[1]; Hwang, R ^[2]

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1. Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.
2. Lawrence Berkeley Lab., CA (United States)

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

• Research Organization: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE; USDOE, Washington, DC (United States)
• DOE Contract Number: AC03-76SF00098
• OSTI ID: 5718054
• Report Number(s): LBL-31861; ON: DE92009502
• Country of Publication: United States
• Language: English

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
29 ENERGY PLANNING
POLICY AND ECONOMY
ENERGY DEMAND
FORECASTING
INDUSTRY
DECISION MAKING
ELECTRIC POWER
ENERGY CONSUMPTION
MATHEMATICAL MODELS
PRICES
PRODUCTION
DEMAND
POWER
320301* - Energy Conservation
Consumption
& Utilization- Industrial & Agricultural Processes- Energy Sources
292000 - Energy Planning & Policy- Supply
Demand & Forecasting