ME-Green: Manufacturing for Environment by Generating Renewable Energy in Enterprise Networks
ME-Green: Manufacturing for Environment by Generating Renewable Energy in Enterprise Networks
批准号:
1704933
负责人:
Tongdan Jin
金额:
$19.93万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-07-15 至 2021-06-30
中文摘要
本研究的目标是模拟和设计一种具有间歇性可再生能源的并网发电系统,以实现零碳工业运营。将讨论制造业面临的三个基本问题:1)通过部署风能、太阳能和其他绿色能源来实现能源独立在经济上是可变的吗?2)使用间歇性电力运营净零碳设施在技术上是否可行,以及3)分布式能源资源(DER)能否通过形成虚拟发电厂来积极参与需求响应,以提供双向能量流动?为了回答这些问题,将开发多目标随机规划模型来优化DER的规模、选址和维护,以最大限度地降低能源成本,同时确保可靠性、弹性和电能质量。主要的DER机组包括风力涡轮机、太阳能光伏、热电联产、电动汽车和电池组。研究假设是,世界各地的几乎任何制造工厂都可以以负担得起的成本100%使用现场风能和太阳能。这一假设将在世界各地不同气候条件的地方得到验证。研究活动包括分析、系统建模和优化以及模拟,以解决与电力间歇、电压稳定性、需求响应、生产-库存计划、电网弹性和交通电气化相关的运营挑战。本研究试图通过间歇可再生能源的整合,为企业系统寻求一种零碳能源解决方案。虽然现场发电和微电网已经被工业所采用,但对投资回报、负荷损失风险以及与公用电网的相互作用进行深入研究的文献仍然很少。在方法上,将采用两阶段优化算法。在第一阶段,将优化DER装置的规模和选址。在第二阶段,将制定将设备生命周期成本降至最低的维护策略。两阶段决策过程能够在初始搜索中消除劣解。在建模中,将采用一种概率措施,通过最小化DER和微电网恢复时间来确保电网对自然灾害或极端事件的恢复时间。这项研究旨在帮助美国制造业通过从电力密集型、碳生产商向环境友好和能源独立的实体转型,获得前所未有的竞争优势。
英文摘要
The goal of this research is to model and design a grid-connected onsite generation system featuring intermittent renewable power to realize zero-carbon industrial operations. Three fundamental questions will be addressed that are confronted by the manufacturing industries: 1) is it economically variable to deploy wind, solar and other green power to achieve energy independency, 2) is it technically feasible to operate a net-zero carbon facility using intermittent power, and 3) can distributed energy resources (DER)actively participate in demand responses by forming a virtual power plant to provide two-way energy flow? To answer these questions, multi-criteria stochastic programming models will be developed to optimize the DER sizing, siting, and maintenance for minimizing energy cost with ensuring reliability, resilience and power quality. Primary DER units include wind turbine, solar photovoltaics, combined heat and power, electric vehicles, and battery banks.The research hypothesis is that that virtually any manufacturing facility around the world could be powered with 100 percent onsite wind and solar power at an affordable cost. This hypothesis will be tested in various locations around the world with diverse climatic conditions. Research activities include analytics, system modeling and optimization, and simulation to address the operational challenges pertaining to power intermittency, voltage stability, demand response, production-inventory schedule, grid resilience, and transportation electrification. This research makes an attempt to seek a zero-carbon energy solution for enterprise systems through the integration of intermittent renewable power. Though onsite generation and microgrids have been adopted by industries, an in-depth study on return-on-investment, loss-of-load risks, and interaction with utility grid is still rare in the literature. Methodologically, a two-stage optimization algorithm will be employed. In stage 1, the sizing and siting of DER units will be optimized. In stage 2, the maintenance policy to minimize the equipment lifecycle cost will be established. A two-stage decision process is able to eliminate inferior solutions in the initial search. In modeling, a probabilistic measure to ensure grid resilience by minimizing the DER and microgrid recovery time against natural disasters or extreme events will be employed. This research is targeted to assist the U.S. manufacturing industry in gaining unprecedented competitive advantages by transforming from power-intensive, carbon producers to environmentally-benign and energy-independent entities.
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A two-stage stochastic aggregate production planning model with renewable energy prosumers,” in Proceedings of the 2021 Institute of Industrial and Systems Engineers (IISE) Virtual Conference, May 22-25, 2021, pp. 223-228.
可再生能源产消者的两阶段随机总生产规划模型,2021 年工业与系统工程师协会 (IISE) 虚拟会议记录,2021 年 5 月 22-25 日,第 223-228 页。
DOI:
--
发表时间:
2021
期刊:
Proceedings of the 2021 Institute of Industrial and Systems Engineers (IISE
影响因子:
--
作者:
[Islam, S., Novoa, C., Jin, T.]
通讯作者:
Jin, T.
DOI:
10.1109/access.2020.2993020
发表时间:
2020-05
期刊:
IEEE Access
影响因子:
3.9
作者:
[Honggang Wang;T. Jin]
通讯作者:
Honggang Wang;T. Jin
DOI:
10.1080/00207543.2017.1394593
发表时间:
2018-09
期刊:
International Journal of Production Research
影响因子:
9.2
作者:
[T. Jin;Tianqin Shi;T. Park]
通讯作者:
T. Jin;Tianqin Shi;T. Park
Optimal sizing of renewable microgrid for flow shop systems under island operations
岛屿运营下流水车间系统可再生微电网的最佳规模
DOI:
--
发表时间:
2020
期刊:
Procedia manufacturing
影响因子:
--
作者:
[Jin, T., Subramanyam, V., Castillo-Villar, K., Sun, F.]
通讯作者:
Sun, F.
DOI:
10.1109/greentech.2018.00018
发表时间:
2018-04
期刊:
2018 IEEE Green Technologies Conference (GreenTech)
影响因子:
--
作者:
[T. Jin;Nhi Mai;Yi Ding;L. Vo;Rana Dawud]
通讯作者:
T. Jin;Nhi Mai;Yi Ding;L. Vo;Rana Dawud
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