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Nonlinear, stochastic model for energy investment in manufacturing

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  • Pena-Taveras, M.S.
  • Cambel, A.B.

Abstract

The rapid introduction of technological innovations into the manufacturing sector of the U.S. economy make it desirable to improve our understanding of investment patterns in the energy sector. Specifically, it is useful to be able to compare investments in efficient, new equipment with continued high fuel consumption due to inefficient equipment. A nonlinear, stochastic model is developed using the Schumpeter Clock Model in economics together with the Ising model of magnetic polarization. This model is validated by using actual economic data for the period 1961–1980. It is seen that the proposed model brings out fluctuations that are not evident with linear models. Overlooking such fluctuations can mislead the decision maker who, in order to maximize profit, must make judicious choices that have long-term implications.

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  • Pena-Taveras, M.S. & Cambel, A.B., 1989. "Nonlinear, stochastic model for energy investment in manufacturing," Energy, Elsevier, vol. 14(7), pages 421-433.
    • Handle: RePEc:eee:energy:v:14:y:1989:i:7:p:421-433
    DOI: 10.1016/0360-5442(89)90138-2
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    Cited by:

    1. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.

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