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Designing a sustainable stochastic electricity generation network with hybrid production strategies

Author

Listed:
  • Vinay Gonela
  • Dalila Salazar
  • Jun Zhang
  • Atif Osmani
  • Iddrisu Awudu
  • Barbara Altman

Abstract

This paper aims to design a sustainable stochastic electricity production network where fossil fuels-based, biomass-based, and co-firing-based production strategies are simultaneously considered in order to take advantage of all the three production strategies. A multi-objective stochastic mixed integer linear programming model is proposed to achieve economic feasibility, as well as environmental and social benefits under multiple uncertainties. The model is solved by using the improved augmented epsilon constraint method. A case study is used to illustrate the effectiveness of the proposed model. Pareto optimal analysis is conducted to understand the trade-off between economic, environmental, and social aspects of sustainability.

Suggested Citation

  • Vinay Gonela & Dalila Salazar & Jun Zhang & Atif Osmani & Iddrisu Awudu & Barbara Altman, 2019. "Designing a sustainable stochastic electricity generation network with hybrid production strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2304-2326, April.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:8:p:2304-2326
    DOI: 10.1080/00207543.2018.1516900
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    Cited by:

    1. Becker, Tristan & Wolff, Michael & Linzenich, Anika & Engelmann, Linda & Arning, Katrin & Ziefle, Martina & Walther, Grit, 2024. "An integrated bi-objective optimization model accounting for the social acceptance of renewable fuel production networks," European Journal of Operational Research, Elsevier, vol. 315(1), pages 354-367.
    2. Tautenhain, Camila P.S. & Barbosa-Povoa, Ana Paula & Mota, Bruna & Nascimento, Mariá C.V., 2021. "An efficient Lagrangian-based heuristic to solve a multi-objective sustainable supply chain problem," European Journal of Operational Research, Elsevier, vol. 294(1), pages 70-90.
    3. Yunusoglu, Pinar & Ozsoydan, Fehmi Burcin & Bilgen, Bilge, 2024. "A machine learning-based two-stage approach for the location of undesirable facilities in the biomass-to-bioenergy supply chain," Applied Energy, Elsevier, vol. 362(C).

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