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Determinants of electrical energy demand for a state; methodology and system simulation Public Deposited

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  • The determinants of electrical energy demand for the State of Oregon are represented in a mathematical model. This model is structured to operate in parallel with a computer simulation model of the state and is utilized independently to investigate electrical energy consumption during various scenarios of economic activity and energy prices. The introductory chapters discuss the importance of the inclusion into energy forecasts of the effects of significant changes in economic and demographic variables as well as consumer responses to increasing energy prices. Alternate methodologies used in forecasting are reviewed. It is argued that the determinants of electricity demand should be viewed as interrelated elements of a socio-economic system and must be addressed in concert with one another. The Oregon State Simulation Model (OSSIM) and the system simulation methodology employed in its development are described. Chapter four presents the data base, structure, and dynamics of the electrical energy demand model. Intensiveness of electricity use and economic activity are exhibited separately, to demonstrate whether increases in consumption are due to changes in intensiveness, to economic growth, or to both and in what proportion. Increasing energy prices induce electricity conservation, interfuel substitution, and changes in appliance saturation trends. These phenomena are modeled explicitly, recognizing that each can affect intensiveness of use and can be characterized by different time constants and limits. The following four chapters develop electrical energy intensiveness functions for thirty-seven consumer categories which are divided among four major sectors. The industrial sector consists of nineteen two-digit SIC groups and three irrigation regions; twelve household appliances and one residual group are included in the residential sector; the commercial sector covers all service activities with the exception of street/highway illumination, which composes the transportation sector. Underlying causes of changing electrical energy intensiveness are explored and price-independent projections of intensiveness are proposed. These projections are linear functions of time in the non-residential categories and sigmoidal functions in twelve residential categories. Results of model operation with exogenous functions of economic activity are discussed in the concluding chapter, together with a description of sensitivity testing and validation criteria. Scenarios investigated demonstrate the significance of the detailed representation of consumer responses to energy price changes. Model utility appears to lie in the ability to illustrate causes of changes in electricity consumption growth rate, to assess alternate scenarios of energy prices, and--when utilized in concert with the OSSIM--to estimate electrical energy requirements based upon self-consistent scenarios of underlying economic activity.
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