Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies
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An optimization-based supply chain management framework for statewide analyses of renewable ammonia production to electricity generation systems for Texas. With optimized renewable ammonia production plants of differing capacities (i.e. 300, 1200, 2100, and 3000 tons per day), renewable technologies (solar and wind), transportation means (railroad and truck), and conversion technologies (gas turbines and fuel cells), the optimal statewide supply chains are obtained by solving a mixed-integer linear programming (MILP) model that minimizes total cost of energy supply chain. The mathematical model includes facilities (renewable power plants and ammonia production pla`nts) and its capacity by county, transportation costs and its mean, type of conversion plant and its costs, water resources, and electricity demand. The solutions of the proposed MILP optimization model provide meaningful topology of energy supply chain including optimal location of facilities and their configuration, optimal transportation network with means and flows, and configuration of conversion plants. Sensitivity analyses of various cases modifying parameters associated in supply chain problem are completed, and economic study results are compared in different scenarios. The results show that annualized cost for replacing electricity demand of the largest 5 counties in Texas is $41.6/GJ-yr and replacing entire Texas demand is $24.6/GJ-yr.
Song, Haneol (2018). Developing a Framework for Ammonia Energy Carrier Supply Chain Optimization Incorporating Renewable Production Technologies. Master's thesis, Texas A & M University. Available electronically from