Data-Driven Stochastic Robust Optimization for Industrial Energy System Considering Renewable Energy Penetration-Reference-Cited by-同舟云学术

Data-Driven Stochastic Robust Optimization for Industrial Energy System Considering Renewable Energy Penetration

Published:2022-03-04 Issue:11 Volume:10 Page:3690-3703
ISSN:2168-0485
Container-title:ACS Sustainable Chemistry & Engineering
language:en
Short-container-title:ACS Sustainable Chem. Eng.

Author:

Shen Feifei¹^ORCID,Zhao Liang¹²^ORCID,Du Wenli¹²^ORCID,Zhong Weimin¹²^ORCID,Peng Xin¹²^ORCID,Qian Feng¹²^ORCID

Affiliation:

1. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

2. Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Renewable Energy, Sustainability and the Environment,General Chemical Engineering,Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acssuschemeng.2c00211

Reference61 articles.

1. Low-carbon roadmap of chemical production: A case study of ethylene in China

2. Technologies and policies to decarbonize global industry: Review and assessment of mitigation drivers through 2070

3. Data-driven adaptive robust optimization for energy systems in ethylene plant under demand uncertainty

4. Modeling and Optimization of a Large-Scale Ethylene Plant Energy System with Energy Structure Analysis and Management

5. Renewable energy in eco-industrial parks and urban-industrial symbiosis: A literature review and a conceptual synthesis

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