The demand response potential in copper production

Röben, Fritz T.C.; Liu, Diran; Reuter, M.A.; Dahmen, Manuel; Bardow, André

doi:10.1016/j.jclepro.2022.132221

Cited by 9 publications

(10 citation statements)

References 30 publications

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“…In the following, we apply the process model to three illustrative power‐intensive processes of industrial relevance to exemplify how our approach can be used as an early‐stage screening method for investigation of flexibilization measures of a given process. Based on our prior work, we have deduced the key parameters given in Table 3 for the copper electrolysis, 12 the aluminum electrolysis, 32 and the chlor‐alkali electrolysis 59 …”

Section: Analysis Of Demand Response Potentialmentioning

confidence: 99%

“…In the following, we apply the process model to three illustrative power-intensive processes of industrial relevance to exemplify how our approach can be used as an early-stage screening method for investigation of flexibilization measures of a given process. Based on our prior work, we have deduced the key parameters given in Table 3 for the copper electrolysis, 12 the aluminum electrolysis, 32 and the chlor-alkali electrolysis. 59 T A B L E 3 Overview of electrolysis process properties based on Röben et al, 12 Schäfer et al, 32 and Brée et al 59 : Assuming infinite storage capacity, that is, no scheduling-relevant storage constraints exist, the influence of the storage constraints can be effectively removed from the optimization problem in case of the copper electrolysis.…”

Section: Application To Three Illustrative Electrolysis Processesmentioning

confidence: 99%

“…Based on our prior work, we have deduced the key parameters given in Table 3 for the copper electrolysis, 12 the aluminum electrolysis, 32 and the chlor-alkali electrolysis. 59 T A B L E 3 Overview of electrolysis process properties based on Röben et al, 12 Schäfer et al, 32 and Brée et al 59 : Assuming infinite storage capacity, that is, no scheduling-relevant storage constraints exist, the influence of the storage constraints can be effectively removed from the optimization problem in case of the copper electrolysis. The relationship between power intake and production rate for the chlor-alkali electrolysis has a different form than Equation (10).…”

Section: Application To Three Illustrative Electrolysis Processesmentioning

confidence: 99%

“…Industrial consumers can adjust their production schedule to time‐varying electricity prices by means of so‐called demand response (DR) 3 . DR can be economically attractive for flexible, electricity‐intensive production processes, for example, air separation, 4 chlor‐alkali electrolysis, 5 electric arc steelmaking, 6 aluminum electrolysis, 7 cement production, 8,9 seawater desalination, 10 pulp, 11 and electrolytic copper refining 12 . Cost‐optimal DR for such processes attempts to shift load from high‐priced hours to low‐priced hours which generally correspond to hours with low and high share of renewable electricity production, respectively 13,14 .…”

Section: Introductionmentioning

confidence: 99%

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Demand response potential of industrial processes considering uncertain short‐term electricity prices

2022

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Time-varying electricity prices on the day-ahead and intraday market incentivize demand response of industrial processes. In prior work (Schäfer et al. AIChE J. 2020;66:1-14), we studied the demand response potential with a generalized process model, but neglected the intraday market. Extending our prior investigation, we account for uncertain intraday prices in a mixed-integer linear stochastic programming-based scheduling, that is, we minimize expected cost and conditional value-atrisk in a bi-objective optimization. We find that for very broad variations of the generalized process parameters, the conditional value-at-risk can be reduced significantly without drastically increasing the expected cost. Furthermore, simultaneously improving multiple process parameter leads to synergetic benefits. Moreover, the savings of three electrolysis processes can be more than doubled by marketing flexibility on the intraday market in addition to the day-ahead market. Overall, our model allows for a rapid early assessment of the demand response potential considering the two markets.

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Section: Analysis Of Demand Response Potentialmentioning

confidence: 99%

Section: Application To Three Illustrative Electrolysis Processesmentioning

confidence: 99%

Section: Application To Three Illustrative Electrolysis Processesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Demand response potential of industrial processes considering uncertain short‐term electricity prices

2022

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“…Copper is a crucial material for the future development of low-carbon technologies, including electric vehicles, wind generation, and solar photovoltaics generation [3,4], and the demand for copper is expected to increase by 275-300%, across the world, by 2050 [5]. However, copper production is an energy-intensive process that requires a lot of fossil fuels and electricity, which leads to a large amount of greenhouse gas (GHG) emissions [6,7]. China is the world's largest demand for refined copper, which made up 49% of global consumption in 2019 [8].…”

Section: Introductionmentioning

confidence: 99%

Life Cycle Energy Consumption and GHG Emissions of the Copper Production in China and the Influence of Main Factors on the above Performance

2022

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The copper demand and production in China are the largest in the world. In order to obtain the trends of the energy consumption and GHG emissions of copper production in China over a number of years, this paper uses a life cycle analysis method to calculate the above two indexes, in the years between 2004 and 2017. The life cycle energy consumption ranged between 101.78 and 31.72 GJ/t copper and the GHG emissions varied between 9.96 and 3.09 t CO2 eq/t copper due to the improvements in mining and smelting technologies. This study also analyses the influence of electricity sources, auxiliary materials consumption, and copper ore grade on the life cycle performance. Using wind or nuclear electricity instead of mixed electricity can reduce energy consumption by 63.67–76.27% or 64.23–76.94%, and GHG emissions by 64.42–77.84% or 65.08–78.63%, respectively. The GHG emissions and energy consumption of underground mining are approximately 2.97–7.03 times that of strip mining, while the influence of auxiliary materials on the above two indexes is less than 3.88%.

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Integrating process and power grid models for optimal design and demand response operation of giga‐scale green hydrogen

Tsay,

Qvist

2023

AIChE Journal

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Electrolysis‐based hydrogen production can play a significant role in industrial decarbonization, and its economic competitiveness can be promoted by designing demand response operating schemes. Nevertheless, the scale of industrial supply plants may be significantly large (on the order of gigawatts), meaning that electricity prices cannot be treated as an input for scheduling problems, that is, the “price taker” approach. This article presents a framework for the optimization of a large‐scale, electricity‐powered hydrogen production facility considering its integration with the power grid. Using a computational case study, we present an iterative scheme for integrating the process model with a model for power grid optimization and capacity expansion, taking the popular GenX model as an example.

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The demand response potential in copper production

Cited by 9 publications

References 30 publications

Demand response potential of industrial processes considering uncertain short‐term electricity prices

Demand response potential of industrial processes considering uncertain short‐term electricity prices

Life Cycle Energy Consumption and GHG Emissions of the Copper Production in China and the Influence of Main Factors on the above Performance

Integrating process and power grid models for optimal design and demand response operation of giga‐scale green hydrogen

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