Zhen Yang

Dr. Zhen Yang

Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2021 in Energy Conversion and Management
Verified
Journal Article
Closed access
SHShuozhuo Hu
Shuozhuo Hu
Zhen YangZhen Yang
Zhen Yang
JLJian Li
Jian Li
YDYuanyuan Duan
Yuanyuan Duan

1 February 2021 in Energy Conversion and Management
Verified
Journal Article
Closed access
SHShuozhuo Hu
Shuozhuo Hu
Zhen YangZhen Yang
Zhen Yang
JLJian Li
Jian Li
Yuanyuan DuanYuanyuan Duan
Yuanyuan Duan


15 July 2022 in Journal of Cleaner Production
Verified
Journal Article
Closed access
JYJingze Yang
Jingze Yang
Zhen YangZhen Yang
Zhen Yang
YDYuanyuan Duan
Yuanyuan Duan


11 October 2021 in Energies
Verified
Journal Article
Open access
PDF file
SHShuozhuo Hu
Shuozhuo Hu
Zhen YangZhen Yang
Zhen Yang
JLJian Li
Jian Li
Yuanyuan DuanYuanyuan Duan
Yuanyuan Duan
Organic Rankine cycle (ORC) is considered a promising heat-to-power technology to utilize waste heat and renewable energy, including solar, biomass and geothermal. However, since the thermodynamic, economic and environmental performance is usually conflict, the single objective design could no longer meet the requirements of the ORC system, putting forward urgent requirements for multi-objective optimization, which has attracted increasing attention with lots of papers published. However, due to these different decision variables, optimization objectives and approaches, existing research is significantly different from each other and is difficult to compare without a systematic summary. Therefore, this paper provides an overview of ORC multi-objective research from three perspectives: optimization objective, method and optimization parameters. Based on the classification of different objectives, this work summarizes the involved variables and provides a recommendation for selecting appropriate objectives in different scenarios. For the optimization method, this work compares different approaches and reveals their advantages and disadvantages. Finally, the decision variables are reviewed and classified into four levels. Then the integrated design approach considering “system-process-component-fluid” is proposed and recommended for further development.