Bioenergy supply chain optimization for addressing energy deficiency: A dynamic model for large-scale network designs

• Published in: Journal of cleaner production 2021-10, Vol.318, p.128495, Article 128495
• Main Authors: Rafique, Raza, Jat, Mohsin, Hakeem-Ur-Rehman, Chudhery, Muhammad Adnan Zahid
• Format: Article
• Language: English
• Subjects: Bioenergy; Mixed integer linear programming; Supply chain design; Sustainable energy development
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2021.128495

This study is motivated by the challenges faced by weak economies in addressing their energy deficiency. A gradual and strategic development of a sustainable bioenergy system is proposed as an opportunity to alleviate the connected energy and economy issues through a cleaner energy-mix. The optimization model presented in this study designs a bioenergy supply chain over multiple periods with the objective to minimize the energy gap under budget and biomass availability constraints. The dynamic elements of the model capture the interplay between population size, energy demand, biomass availability, energy consumption, and the Gross Domestic Product. A salient feature of the model is the consideration of an end-to-end bioenergy supply network from biomass reserves to the electricity demand zones. Besides facility setup and operating costs, the model considers biofuel transportation costs and transmission yield losses. The model is extensively analyzed through a case study. Practical insights about budget allocation and system expansion are discussed based on the case study. The analysis highlights that the cost for the optimum development of a bioenergy system can significantly vary over the planning horizon. The optimum setup starts as a highly centralized system and evolves into a largely decentralized system in which powerplants source biofuel and supply power locally. •Strategic development of a bioenergy system can address poor energy-economy nexus.•A multi-period optimization model for bioenergy supply chain designing is presented.•Dynamics of energy demand, consumption, and budget availability are considered.•Decentralized bioenergy systems are efficient.