Superstructure-based mixed-integer nonlinear programming framework for hybrid heat sources driven organic Rankine cycle optimization

Superstructure-based mixed integer nonlinear programming framework for hybrid heat sources driven organic Rankine cycles optimization is addressed. [Display omitted] •Simultaneous optimization for hybrid heat sources-ORC integration.•Superstructure model to identify optimal match of working fluid an...

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Published in:Applied energy Vol. 307; p. 118277
Main Authors: Liang, Zheng, Liang, Yingzong, Luo, Xianglong, Chen, Jianyong, Yang, Zhi, Wang, Chao, Chen, Ying
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.02.2022
Subjects:
algorithms
cyclohexanes
electricity
energy efficiency
heat
Heat exchanger network
heat exchangers
Hybrid heat source
hybrids
Integration
Organic Rankine cycle
Simultaneous optimization
solar energy
Simultaneous optimization
Integration
Heat exchanger network
Organic Rankine cycle
Hybrid heat source
ISSN:0306-2619, 1872-9118
Online Access:Get full text
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Summary:Superstructure-based mixed integer nonlinear programming framework for hybrid heat sources driven organic Rankine cycles optimization is addressed. [Display omitted] •Simultaneous optimization for hybrid heat sources-ORC integration.•Superstructure model to identify optimal match of working fluid and heat sources.•Tailored multi-step algorithm for global optimization of large size design problems.•Case studies show SWHORCs generally outperform SWPORCs in NPO and efficiency.•Toluene-SWHORC achieves the highest efficiency of 19.73% for waste heat at 473.15 K. Organic Rankine cycle (ORC) is a promising technology capable of harnessing low-grade energy, e.g. renewable energy and waste heat, and converting it into electricity. Conventional ORC often operates with single heat source, which can be unfavorable to its efficiency due to the poor matching between its working fluid and heat source. Implementing hybrid heat sources is generally more energy-efficient as multiple heat sources can effectively match with the working fluid, however, the design can be a challenging task. This study proposes a superstructure-based method for the ORC design that simultaneously synthesizes heat exchanger network for hybrid heat sources and working fluid, and optimizes the ORC and heat sources' parameters. A mixed-integer nonlinear programming model is formulated to achieve the simultaneous optimization. We also develop a tailored multi-step initialization algorithm to facilitate the optimization. The model is applied to the design and analysis of ORCs driven by solar energy and waste heat with four different working fluids. Results demonstrate that the hybrid heat source-driven ORC improves the system performance. Cyclohexane is found to be the optimal working fluid for the proposed ORC system with a 48.19% increase in net power output compared with the single heat source-driven ORCs running separately.
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ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2021.118277