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Environmental sustainability

Optimizing Bioenergy Supply Chains for Cost Efficiency and Sustainability

Strategic Insights

— 2 min read

A team of researchers from the Indian Institute of Technology Roorkee has published a new study on optimizing bioenergy supply chains to reduce greenhouse gas emissions and combat climate change. The study introduces a novel Mixed Integer Linear Programming (MILP) model that integrates both fixed depots and portable depots for biomass preprocessing, allowing for the optimization of the collection, transportation, and preprocessing of forest residue as biomass feedstock. According to the research, the inclusion of portable depots can reduce total costs by up to 26.94% through savings in transportation costs, and enhance the efficiency of the bioenergy supply chain.

Key Takeaways:

  • The research introduces a novel MILP model that optimizes the biomass supply chain by integrating both fixed depots and portable depots for biomass preprocessing.
  • The model determines the optimal number and location of fixed depots and portable depots to balance costs associated with transportation, processing, and facility setup.
  • The inclusion of portable depots can reduce total costs by up to 26.94% through savings in transportation costs.
  • The approach also enhances the efficiency of the bioenergy supply chain, enabling it to respond better to variable biomass availability and reduce environmental impacts.
  • The applicability of the optimization model is demonstrated through a real-life case study of a power plant in the state of Oregon, USA.
  • The research provides valuable quantitative decision support for policymakers and energy stakeholders aiming to optimize bioenergy supply chains and contribute to global renewable energy targets.
  • The study's authors include Amit Upadhyay, Gaurav Bhatt, and Kamalakanta Sahoo from the Indian Institute of Technology Roorkee.

Statistics:

  • The research found that the inclusion of portable depots can reduce total costs by up to 26.94%.
  • The model optimizes the collection, transportation, and preprocessing of forest residue as biomass feedstock.
  • The approach enhances the efficiency of the bioenergy supply chain, enabling it to respond better to variable biomass availability.
  • The research demonstrated the applicability of the optimization model through a real-life case study of a power plant in the state of Oregon, USA.
  • The study's results provide valuable quantitative decision support for policymakers and energy stakeholders aiming to optimize bioenergy supply chains.

Sources:

  • NewsRx. Data from Indian Institute of Technology Roorkee Advance Knowledge in Renewable Energy (Biomass Supply Chain Network Design: Integrating Fixed and Portable Preprocessing Depots for Cost Efficiency and Sustainability). Ecology, Environment & Conservation. July 11, 2025; p 62.
  • Indian Institute of Technology Roorkee. Biomass Supply Chain Network Design: Integrating Fixed and Portable Preprocessing Depots for Cost Efficiency and Sustainability. Applied Energy, 2025;389.
  • Elsevier Sci Ltd. Applied Energy. (www.elsevier.com; www.journals.elsevier.com/applied-energy/)

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