FMRG: Cyber: Manufacturing USA: Exploiting Spatio-Temporal Interdependency Between Electrochemical Manufacturing and Power Grid to Optimize Flexibility and Sustainability

FMRG:网络:美国制造:利用电化学制造和电网之间的时空相互依赖性来优化灵活性和可持续性

基本信息

  • 批准号:
    2328160
  • 负责人:
  • 金额:
    $ 299.95万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-01 至 2027-08-31
  • 项目状态:
    未结题

项目摘要

The chemical manufacturing sector and the power grid are becoming increasingly coupled. This is driven by their shared interest in decarbonizing operations: the chemical sector is aiming to decarbonize via electrification of key technologies, while the grid is aiming to decarbonize via adoption of renewable (wind/solar) power. As such, mitigating the inherent intermittency of renewable power is a grand challenge that needs to be overcome to achieve decarbonization of both sectors. This will require the design of new and flexible technologies that can shift power demands from the seconds to seasons timescale and from the local to the national level. The chemical sector is uniquely positioned to help provide these unprecedented levels of flexibility. This can be achieved via modular electrochemical (EC) technologies that use highly intermittent power to produce chemicals in a distributed manner and via the efficient production of energy carriers (e.g., hydrogen, ammonia, formic acid) that can be used to store, transport, and re-generate power. To realize this vision, a paradigm shift under which EC technologies are co-designed with electricity markets is needed; specifically, EC technologies need to be designed as flexibility providers that actively participate in electricity markets and such markets need to properly remunerate flexibility services. More broadly, EC technologies are vital sector-coupling assets that can provide flexibility to enable risk mitigation (e.g., extreme weather, cyber-attacks) and can play a key role in ensuring that the power grid and chemical supply chains operate in a reliable, sustainable, and economic manner. Accordingly, This Future CyberManufacturing research grant will boost American chemical manufacturing and advance the prosperity and welfare of the United States. The project will also lead to new design principles, simulation models, data, and technologies that enhance the training of the next-generation workforce of chemical engineers, electrical engineers, and chemists to leverage multiscale thinking to develop technologies and solutions. The project will also lead to new business practices that foster coordination between chemical and power sectors with the goal of helping accelerate the adoption of new technologies and decarbonization efforts. The goal of this Future Manufacturing project is to conduct fundamental computational and experimental research to design new and flexible electrochemical (EC) technologies that best integrate with the power grid and with chemical supply chains, to identify key aspects that limit flexibility of these technologies, and to determine how to best exploit their flexibility to achieve economic and sustainability goals at a societal scale. Specifically, an interdisciplinary team will: (i) develop infrastructure-level modeling techniques that capture the multiscale coupling between the chemical and power sectors that capture different types of EC technologies and help identify amounts and types of flexibility needed; (ii) develop device-level models for EC technologies that capture the interplay between flexibility and design (e.g., cell capacity, ramping capacity, efficiency, durability); (iii) develop density functional theory models that help identify electrode materials to meet design specifications; and (iv) develop experimental procedures to evaluate different reaction chemistries, materials, and EC configurations (e.g., coupled, decoupled, tandem, cascade), and to collect key data that informs modeling and economic/environmental assessments. These capabilities will be combined via convergent studies that will answer questions of societal and industrial relevance. The convergent research approach will lead to new design principles, simulation models, data, and technologies that will serve as the backbone of a workforce development plan that will train a new generation of chemical engineers, electrical engineers, and chemists that leverage multiscale thinking to develop technologies and solutions. The project will lead to new business practices that foster coordination between the chemical and power sectors with the goal of helping accelerate the adoption of EC technologies and decarbonization efforts. This Future Manufacturing award was supported by the Divisions of Civil, Mechanical and Manufacturing Innovation (CMMI), Chemical, Bioengineering, Environmental and Transport Systems (CBET), Engineering Education and Centers (EEC), Chemistry (CHE), and the Division of Mathematical Sciences (DMS).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
化工制造业和电网正变得越来越紧密。这是由于他们对脱碳操作的共同兴趣:化工行业的目标是通过关键技术的电气化来实现脱碳,而电网的目标是通过采用可再生(风能/太阳能)发电来实现脱碳。因此,缓解可再生能源固有的间歇性是一项需要克服的重大挑战,以实现这两个部门的脱碳。这将需要设计新的灵活技术,将电力需求从几秒钟的时间尺度转移到季节尺度,从地方层面转移到国家层面。化工行业处于独特的地位,可以帮助提供这些前所未有的灵活性水平。这可以通过模块化电化学(EC)技术实现,该技术使用高度间歇性的电力以分布式方式生产化学品,并通过高效地生产可用于存储、运输和重新产生电力的能量载体(例如氢、氨、甲酸)来实现。为了实现这一愿景,需要转变模式,在这种模式下,EC技术与电力市场共同设计;具体地说,EC技术需要被设计为积极参与电力市场的灵活性提供者,而此类市场需要适当地支付灵活性服务的报酬。更广泛地说,EC技术是至关重要的部门耦合资产,可以提供灵活性以实现风险缓解(例如极端天气、网络攻击),并可以在确保电网和化学品供应链以可靠、可持续和经济的方式运行方面发挥关键作用。相应地,这项未来网络制造研究拨款将促进美国的化学制造业,促进美国的繁荣和福利。该项目还将产生新的设计原则、模拟模型、数据和技术,以加强对下一代化学工程师、电气工程师和化学家的培训,以利用多尺度思维开发技术和解决方案。该项目还将产生新的商业做法,促进化学和电力部门之间的协调,目的是帮助加快采用新技术和脱碳努力。这个未来制造项目的目标是进行基本的计算和实验研究,以设计与电网和化学品供应链最佳集成的新的灵活的电化学(EC)技术,找出限制这些技术灵活性的关键方面,并确定如何最好地利用它们的灵活性来实现社会规模的经济和可持续发展目标。具体地说,一个跨学科团队将:(I)开发基础设施级建模技术,捕捉化学和电力部门之间的多尺度耦合,捕捉不同类型的EC技术,并帮助确定所需的灵活性的数量和类型;(Ii)为EC技术开发设备级模型,捕捉灵活性与设计(例如,电池容量、斜坡容量、效率、耐用性)之间的相互作用;(Iii)开发密度泛函理论模型,帮助确定满足设计规范的电极材料;以及(4)制定实验程序,以评估不同的反应化学成分、材料和EC配置(例如,耦合、分离、串联、级联),并收集关键数据,为建模和经济/环境评估提供信息。这些能力将通过融合研究结合在一起,这些研究将回答与社会和行业相关的问题。融合的研究方法将产生新的设计原则、模拟模型、数据和技术,作为劳动力发展计划的支柱,该计划将培养利用多尺度思维开发技术和解决方案的新一代化学工程师、电气工程师和化学家。该项目将导致新的商业做法,促进化学和电力部门之间的协调,目的是帮助加快采用EC技术和脱碳努力。该奖项由土木工程、机械和制造业创新(CMMI)、化学、生物工程、环境和运输系统(CBET)、工程教育和中心(EEC)、化学(CHE)和数学科学部(DMS)支持。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Victor Zavala Tejeda其他文献

Victor Zavala Tejeda的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Victor Zavala Tejeda', 18)}}的其他基金

NEW AND SCALABLE PARADIGMS FOR DATA-DRIVEN MODEL PREDICTIVE CONTROL
数据驱动模型预测控制的新的、可扩展的范式
  • 批准号:
    2315963
  • 财政年份:
    2023
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
EFRI DCheM: Distributed Photosynthetic Recovery of Livestock Waste Nutrients for Sustainable Production of Fertilizers
EFRI DCheM:畜牧废物养分的分布式光合回收用于肥料的可持续生产
  • 批准号:
    2132036
  • 财政年份:
    2021
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
CAREER: OPTIMIZATION FORMULATIONS AND ALGORITHMS FOR THE ANALYSIS AND DESIGN OF HIERARCHICAL MODULAR SYSTEMS
职业:分层模块化系统分析和设计的优化公式和算法
  • 批准号:
    1748516
  • 财政年份:
    2018
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
BIGDATA: IA: Collaborative Research: Data-Driven, Multi-Scale Design of Liquid-Crystals for Wearable Sensors for Monitoring Human Exposure and Air Quality
大数据:IA:协作研究:用于监测人体暴露和空气质量的可穿戴传感器的数据驱动、多尺度液晶设计
  • 批准号:
    1837812
  • 财政年份:
    2018
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
CRISP 2.0 Type 2: Collaborative Research: Exploiting Interdependencies Between Computing and Electrical Power Infrastructures to Maximize Resilience and Flexibility
CRISP 2.0 类型 2:协作研究:利用计算和电力基础设施之间的相互依赖性来最大限度地提高弹性和灵活性
  • 批准号:
    1832208
  • 财政年份:
    2018
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
Multi-Stakeholder Decision-Making for the Development of Livestock Waste-to-Biogas Systems
畜牧废物转化沼气系统发展的多方利益相关者决策
  • 批准号:
    1604374
  • 财政年份:
    2016
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
Multi-Scale Predictive Control of Coupled Energy Networks
耦合能源网络的多尺度预测控制
  • 批准号:
    1609183
  • 财政年份:
    2016
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant

相似国自然基金

Cyber体系脆弱性仿真分析方法研究
  • 批准号:
    61403400
  • 批准年份:
    2014
  • 资助金额:
    24.0 万元
  • 项目类别:
    青年科学基金项目
基于复杂网络理论的Cyber体系效能仿真分析方法研究
  • 批准号:
    61374179
  • 批准年份:
    2013
  • 资助金额:
    77.0 万元
  • 项目类别:
    面上项目
面向智能电网基础设施Cyber-Physical安全的自治愈基础理论研究
  • 批准号:
    61300132
  • 批准年份:
    2013
  • 资助金额:
    23.0 万元
  • 项目类别:
    青年科学基金项目
Cyber攻击对国家关键基础设施级联失效影响建模仿真研究
  • 批准号:
    61174035
  • 批准年份:
    2011
  • 资助金额:
    58.0 万元
  • 项目类别:
    面上项目
基于Cyber空间的体系脆弱性仿真分析方法研究
  • 批准号:
    61174156
  • 批准年份:
    2011
  • 资助金额:
    59.0 万元
  • 项目类别:
    面上项目

相似海外基金

FMRG: Cyber: Manufacturing USA: Material-on-demand manufacturing through convergence of manufacturing, AI and materials science
FMRG:网络:美国制造:通过制造、人工智能和材料科学的融合实现按需制造材料
  • 批准号:
    2328395
  • 财政年份:
    2024
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
FMRG: Cyber: Manufacturing USA: NextG-Enabled Manufacturing of the Future (NextGEM)
FMRG:网络:美国制造:支持 NextG 的未来制造 (NextGEM)
  • 批准号:
    2328260
  • 财政年份:
    2024
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
FMRG: Cyber: Manufacturing USA: Manufacturing of Next-Generation Perovskite Semiconductors at Scale
FMRG:网络:美国制造:大规模制造下一代钙钛矿半导体
  • 批准号:
    2328010
  • 财政年份:
    2023
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
FMRG: Cyber: Scalable Precision Manufacturing of Programmable Polymer Nanoparticles Using Low-temperature Initiated Chemical Vapor Deposition Guided by Artificial Intelligence
FMRG:网络:利用人工智能引导的低温引发化学气相沉积进行可编程聚合物纳米粒子的可扩展精密制造
  • 批准号:
    2229092
  • 财政年份:
    2023
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
FMRG: Cyber: Cyber-Coordinated Analytical Framework for Multi-stage Distributed Future Manufacturing Systems
FMRG:网络:多阶段分布式未来制造系统的网络协调分析框架
  • 批准号:
    2412020
  • 财政年份:
    2023
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
FMRG: Cyber: Manufacturing USA: Cyber-Enabled, High-Throughput Manufacturing of Multi-Material, 3D Nanostructures
FMRG:网络:美国制造:网络支持的多材料、3D 纳米结构的高通量制造
  • 批准号:
    2229036
  • 财政年份:
    2022
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Continuing Grant
FMRG: Eco: Cyber Enabled Transformation to Circular Supply Chains for Sustainable Pharmaceutical Manufacturing Networks
FMRG:Eco:通过网络实现循环供应链转型,实现可持续药品制造网络
  • 批准号:
    2229250
  • 财政年份:
    2022
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
FMRG: Manufacturing USA: Cyber: Data-Driven Methods for Future Cyber Manufacturing as a Service
FMRG:美国制造:网络:未来网络制造即服务的数据驱动方法
  • 批准号:
    2229260
  • 财政年份:
    2022
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Continuing Grant
FMRG: Cyber: Cyber-Coordinated Analytical Framework for Multi-stage Distributed Future Manufacturing Systems
FMRG:网络:多阶段分布式未来制造系统的网络协调分析框架
  • 批准号:
    2134409
  • 财政年份:
    2021
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
FMRG: Manufacturing USA: Cyber: Privacy-Preserving Tiny Machine Learning Edge Analytics to Enable AI-Commons for Secure Manufacturing
FMRG:美国制造业:网络:保护隐私的小型机器学习边缘分析,以实现 AI 共享以实现安全制造
  • 批准号:
    2134667
  • 财政年份:
    2021
  • 资助金额:
    $ 299.95万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了