Optimization Models for Sustainable Development of Energy Supply Chains

CAFARO, DIEGO C.

Buenos Aires

Workshop; Pan-American Advanced Studies Institute on Optimization and Data Science for Net-Zero Carbon and Sustainability; 2023

Carnegie Mellon University, Universidad Nacional del Sur

In the coming years the world expects a substantial growth in demand for energy products, while the need to reduce GHG emissions is unavoidable. Since the operation of supply chains accounts for more than 80% of the environmental impact of goods and services, tracking the carbon intensity (CI) of energy products appears as a key measure to quantify carbon footprint along their value chains. This indicator will also constitute a key factor of survival, competitiveness and validity in the market for many companies in the near future. In this context, the optimal design, planning and operation of energy supply chains require rigorous techniques to make energy products accessible and affordable to all, under CI limitations. Unlike the tracking of other intensive properties, the CI associated to product flows depends on numerous decisions such as the network topology, the selection of means of transportation, their speed, the production processes, and the energy used at each facility, among others. The need to manage alternative energy sources globally, together with final markets imposing different CI limitations, makes detailed monitoring of CI a critical task. This presentation introduces a series of mixed-integer optimization models to help energy companies boost their transition to a more sustainable matrix. We address the optimal design and expansion planning of shale oil and gas gathering networks through pipelines; the supply of water, its processing, recycling and reutilization; the integrated design and operation of bioprocesses to produce renewable natural gas from residues; the optimal placement and interconnection of turbines on a windfarm; and the planning of green and blue hydrogen supplies across the globe. For the latter case in particular we assess the impacts of the CI on the optimal solutions and how companies could effectively manage their CI targets to remain competitive.