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Expansion of isolated electrical systems in the Amazon: An approach using fuzzy multi-objective mathematical programming

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  • Bitar, Sandro D.B.
  • da Costa Junior, Carlos T.
  • Barreiros, José A.L.
  • Neto, João C. do L.

Abstract

This paper examines some problems encountered in the expansion of isolated electrical systems (IES) in the Amazon region, more precisely, the thermoelectric systems used in that region. Supposing a certain degree of uncertainty in energy consumption, we evaluate the expansion of thermoelectric power from firewood and diesel fuel, together with variations for costs, CO2 emissions, and number of direct jobs (NDJ) generated with the use of these technologies. The analysis is accomplished by using fuzzy multi-objective mathematical programming, and interpreting each objective function both by itself and in combination with the others, through a fuzzy multi-objective parametrization. The scenarios are defined by the energy consumption percentage increase, limited to be below some admissible maximum value, while still considering variations in the installed power. The costs, CO2 emission, and the NDJ generated are analyzed and compared with the largest values obtained with the model of crisp mathematical programming, used for the original configuration. Finally, in Section 4, we present the results and respective analyses for the finished simulation.

Suggested Citation

  • Bitar, Sandro D.B. & da Costa Junior, Carlos T. & Barreiros, José A.L. & Neto, João C. do L., 2009. "Expansion of isolated electrical systems in the Amazon: An approach using fuzzy multi-objective mathematical programming," Energy Policy, Elsevier, vol. 37(10), pages 3899-3905, October.
    • Handle: RePEc:eee:enepol:v:37:y:2009:i:10:p:3899-3905
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    2. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
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    Cited by:

    1. Neto, João C. do L. & da Costa Junior, Carlos T. & Bitar, Sandro D.B. & Junior, Walter B., 2011. "Forecasting of energy and diesel consumption and the cost of energy production in isolated electrical systems in the Amazon using a fuzzification process in time series models," Energy Policy, Elsevier, vol. 39(9), pages 4947-4955, September.
    2. 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.
    3. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.

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