Data-driven robust optimization for optimal scheduling of power to methanol

Zheng, Yi; You, Shi; Li, Ximei; Bindner, Henrik W.; Münster, Marie

doi:10.1016/j.enconman.2022.115338

Cited by 25 publications

(11 citation statements)

References 32 publications

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“…The distillation capital cost is calculated by scaling the reference cost to the volumetric flow rate of the electrolyte calculated in (13). Likewise, based on [34,35], if there is byproduct hydrogen, then the PSA capital cost is calculated by scaling the reference cost to the total gas flow rate (calculated in ( 14)).…”

Section: Linear Model Of Cesmentioning

confidence: 99%

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Green economic analysis for multi‐energy system with linearized CO₂ electrolysis model

Song

Wang

Hesamzadeh

et al. 2023

IET Generation Trans & Dist

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CO2 electrolysis system (CES), as a type of carbon capture, utilization, and storage, has significant potential for achieving carbon neutrality. By utilizing surplus renewable energy, CES can convert CO2 into valuable electrochemical products. This paper studies the advantages brought by the application of CES to the green economic operation of multi‐energy system. Firstly, a linear model based on the CES's operation data is developed to characterize its dynamic behaviour. In addition, a two‐stage stochastic programming model for the operation of CES within multi‐energy system is studied. Finally, a creative optimal‐operation‐based end‐of‐life net present value (OENPV) is proposed to assess the long‐term investment of CES. The results of the cases in different seasons and electrochemical products show that the application of CES not only brings significant carbon reduction to the multi‐energy system, but also alleviates the curtailment of renewable energy. Additionally, according to the OENPV analysis outcome, the production of formic acid gives the system the shortest return on investment, which is the fourth year of the 20‐year assessment cycle.

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Section: Linear Model Of Cesmentioning

confidence: 99%

“…Ref. [13] studies the optimal dispatch of the power-to-methanol process in an MES of wind power and biomass plant, and uses a data-driven robust method to consider the price uncertainty. Ref.…”

Section: Introductionmentioning

confidence: 99%

Green economic analysis for multi‐energy system with linearized CO₂ electrolysis model

Song

Wang

Hesamzadeh

et al. 2023

IET Generation Trans & Dist

View full text Add to dashboard Cite

show abstract

“…Bødal and M. Korpås 28 developed a two‐stage stochastic model in a rolling horizon framework to consider uncertainties and used the model to study hydrogen production from electrolysis in a future scenario of a remote region in Norway with a focus on scheduling. Zheng et al 29 modeled and optimized the operation of a grid‐connected power‐to‐methanol system considering its flexibility.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Several works have been done with a focus on optimizing the scheduling of electrified processes. [26][27][28][29][30][31][32][33][34] For example, Brée et al 26 formulated and solved a model for the optimal scheduling of a chloralkali plant operating under different modes utilizing Demand Side Management.…”

Section: Literature Reviewmentioning

confidence: 99%

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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“…Several works have been done with a focus on optimizing the scheduling of electrified processes, such as [26,27,28,29,30,31,32,33,34]. For example, Brée et al [26] formulated and solved a model for the optimal scheduling of a chloralkali plant operating under different modes utilizing Demand Side Management.…”

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

Data-driven robust optimization for optimal scheduling of power to methanol

Cited by 25 publications

References 32 publications

Green economic analysis for multi‐energy system with linearized CO₂ electrolysis model

Green economic analysis for multi‐energy system with linearized CO₂ electrolysis model

Distributed manufacturing for electrified chemical processes in a microgrid

Distributed Manufacturing for Electrified Chemical Processes in a Microgrid

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Data-driven robust optimization for optimal scheduling of power to methanol

Cited by 25 publications

References 32 publications

Green economic analysis for multi‐energy system with linearized CO2 electrolysis model

Green economic analysis for multi‐energy system with linearized CO2 electrolysis model

Distributed manufacturing for electrified chemical processes in a microgrid

Distributed Manufacturing for Electrified Chemical Processes in a Microgrid

Contact Info

Product

Resources

About

Green economic analysis for multi‐energy system with linearized CO₂ electrolysis model

Green economic analysis for multi‐energy system with linearized CO₂ electrolysis model