Multiperiod Modeling and Optimization of Hydrogen-Based Dense Energy Carrier Supply Chains

Author:

Kakodkar Rahul12ORCID,Allen R. Cory12,Demirhan C. Doga3,Fu Xiao4,Pappas Iosif4,Mutlu Mete3,Pistikopoulos Efstratios N.12

Affiliation:

1. Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX 77843, USA

2. Texas A&M Energy Institute, Texas A&M University, College Station, TX 77845, USA

3. Shell Technology Center Houston, Shell International Exploration and Production Inc., Houston, TX 77082, USA

4. Energy Transition Campus Amsterdam, Shell Global Solutions International B.V., 1031 HW Amsterdam, The Netherlands

Abstract

The production of hydrogen-based dense energy carriers (DECs) has been proposed as a combined solution for the storage and dispatch of power generated through intermittent renewables. Frameworks that model and optimize the production, storage, and dispatch of generated energy are important for data-driven decision making in the energy systems space. The proposed multiperiod framework considers the evolution of technology costs under different levels of promotion through research and targeted policies, using the year 2021 as a baseline. Furthermore, carbon credits are included as proposed by the 45Q tax amendment for the capture, sequestration, and utilization of carbon. The implementation of the mixed-integer linear programming (MILP) framework is illustrated through computational case studies to meet set hydrogen demands. The trade-offs between different technology pathways and contributions to system expenditure are elucidated, and promising configurations and technology niches are identified. It is found that while carbon credits can subsidize carbon capture, utilization, and sequestration (CCUS) pathways, substantial reductions in the cost of novel processes are needed to compete with extant technology pathways. Further, research and policy push can reduce the levelized cost of hydrogen (LCOH) by upwards of 2 USD/kg.

Funder

Texas A&M Energy Institute, Texas A&M University

Publisher

MDPI AG

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