Green Ammonia Supply Chain Design for Maritime Transportation

Wang, Hanchu; Daoutidis, Pródromos; Zhang, Qi

doi:10.1016/b978-0-323-85159-6.50098-1

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…Li et al 37 proposed a co‐planning approach for the regional wind resources‐based ammonia industry and the electric network to optimize the wind‐to‐ammonia configuration and the expansion of the electrical network with ammonia demand being satisfied locally rather than transporting ammonia and for a one‐time demand. Other papers have also considered supply chain optimization of electrified plants 38‐42 . All these papers do not consider mode‐based production of chemicals as well as local microgrid‐based production, and most of them also do not consider multiple time scales and multiple products (chemicals) requirements in a network.…”

Section: Literature Reviewmentioning

confidence: 99%

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Distributed manufacturing for electrified chemical processes in a microgrid

Ramanujam,

Constante‐Flores,

2023

AIChE Journal

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To alleviate the greenhouse gas emissions by the chemical industry, electrification has been proposed as a solution where electricity from renewable sources is used to power processes. The adoption of renewable energy is complicated by its spatial and temporal variations. To address this challenge, we investigate the potential of distributed manufacturing for electrified chemical processes installed in a microgrid. We propose a multiscale mixed‐integer linear programming model for locating modular electrified plants, renewable‐based generating units, and power lines in a microgrid that includes monthly transportation and hourly scheduling decisions. We propose a K‐means clustering‐based aggregation disaggregation matheuristic to solve the model efficiently. The model and algorithm are tested using a case study with 20 candidate locations in Western Texas. Additionally, we define a new concept, “the Value of the Multi‐scale Model,” to demonstrate the additional economic benefits of our model compared with a single‐scale model.

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Section: Literature Reviewmentioning

confidence: 99%

“…Other papers have also considered supply chain optimization of electrified plants. [38][39][40][41][42] All these papers do not consider mode-based production of chemicals as well as local microgrid-based production, and most of them also do not consider multiple time scales and multiple products (chemicals) requirements in a network.…”

Section: Literature Reviewmentioning

confidence: 99%

Distributed manufacturing for electrified chemical processes in a microgrid

Ramanujam,

Constante‐Flores,

2023

AIChE Journal

View full text Add to dashboard Cite

show abstract

“…Li et al [37] proposed a co-planning approach for the regional wind resources-based ammonia industry and the electric network to optimize the wind-to-ammonia configuration and the expansion of the electrical network with ammonia demand being satisfied locally rather than transporting ammonia and for a one-time demand. Other papers such as [38,39,40,41,42] have also considered supply chain optimization of electrified plants. All these papers do not consider mode-based production of chemicals as well as local microgrid-based production, and most of them also do not consider multiple time scales and multiple products (chemicals) requirements in a network.…”

Section: Literature Reviewmentioning

confidence: 99%

Distributed Manufacturing for Electrified Chemical Processes in a Microgrid

Ramanujam

Constante-Flores

Can

2023

Preprint

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To alleviate the greenhouse gas emissions by the chemical industry, electrification has been proposed as a solution where electricity from renewable sources is used to power processes. The adoption of renewable energy is complicated by its spatial and temporal variations. To address this challenge, we investigate the potential of distributed manufacturing for electrified chemical processes installed in a microgrid. We propose a multi-scale mixed-integer linear programming model for locating modular electrified plants, renewable-based generating units, and power lines in a microgrid that includes monthly transportation and hourly scheduling decisions. We propose a K-means clustering-based aggregation disaggregation matheuristic to solve the model efficiently. The model and algorithm are tested using a case study with 20 candidate locations in Western Texas. Additionally, we define a new concept, “the Value of the Multi-scale Model”, to demonstrate the additional economic benefits of our model compared with a single-scale model.

show abstract