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Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources

Author

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  • Weiwei Cui
  • Lin Li
  • Zhiqiang Lu

Abstract

Environmentally friendly energy resources open a new opportunity to tackle the problem of energy security and climate change arising from wide use of fossil fuels. This paper focuses on optimizing the allocation of the energy generated by the renewable energy system to minimize the total electricity cost for sustainable manufacturing systems under time‐of‐use tariff by clipping the peak demand. A rolling horizon approach is adopted to handle the uncertainty caused by the weather change. A nonlinear mathematical programming model is established for each decision epoch based on the predicted energy generation and the probability distribution of power demand in the manufacturing plant. The objective function of the model is shown to be convex, Lipchitz‐continuous, and subdifferentiable. A generalized benders decomposition method based on the primal‐dual subgradient descent algorithm is proposed to solve the model. A series of numerical experiments is conducted to show the effectiveness of the solution approach and the significant benefits of using the renewable energy resources.

Suggested Citation

  • Weiwei Cui & Lin Li & Zhiqiang Lu, 2019. "Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(2), pages 154-173, March.
    • Handle: RePEc:wly:navres:v:66:y:2019:i:2:p:154-173
    DOI: 10.1002/nav.21830
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    Cited by:

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    2. Al-Madani, Mohammed Hammam Mohammed & Fernando, Yudi & Iranmanesh, Mohammad & Lim, Ming K. & Tseng, Ming-Lang, 2024. "Renewable energy supply chain in Malaysia: Fostering energy management practices and ecological performance," Renewable Energy, Elsevier, vol. 226(C).
    3. Adrian Kampa & Iwona Paprocka, 2021. "Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times," Energies, MDPI, vol. 14(21), pages 1-25, November.
    4. Govindan, Kannan & Rajeev, A. & Padhi, Sidhartha S. & Pati, Rupesh K., 2020. "Supply chain sustainability and performance of firms: A meta-analysis of the literature," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    5. Quetzalcoatl Hernandez-Escobedo & Javier Garrido & Fernando Rueda-Martinez & Gerardo Alcalá & Alberto-Jesus Perea-Moreno, 2019. "Wind Power Cogeneration to Reduce Peak Electricity Demand in Mexican States Along the Gulf of Mexico," Energies, MDPI, vol. 12(12), pages 1-22, June.
    6. Norouzi, Farshid & Hoppe, Thomas & Elizondo, Laura Ramirez & Bauer, Pavol, 2022. "A review of socio-technical barriers to Smart Microgrid development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

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