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Superstructure-free synthesis and optimization of distributed industrial energy supply systems

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  • Voll, Philip
  • Lampe, Matthias
  • Wrobel, Gregor
  • Bardow, André

Abstract

A novel approach is proposed for the superstructure-free synthesis and optimization of distributed energy supply systems (DESS) by exploiting the nature of evolutionary algorithms. Current approaches require the designer to define a superstructure, which subsequently is optimized. In the presented method, the a priori specification of a superstructure is avoided: A mutation operator employs generic replacement rules to replace parts of energy supply systems by alternative designs. To minimize both the number of replacement rules and meaningless design alternatives generated during mutation, all energy conversion technologies are classified into the so-called energy conversion hierarchy (ECH). The ECH allows for an efficient definition of all reasonable connections between the regarded components, and the definition of generic replacement rules. Thereby, the hierarchy-supported approach balances richness of the available design space and computational efficiency. In addition, the convenient description of the design space allows for an easy addition of technologies into the optimization problem. The proposed approach thus provides an expandable framework for optimizing DESS. The method is applied to the synthesis of a heating and cooling system. The presented approach efficiently solves retrofit and grassroots design problems. It automatically identifies complex solutions such as trigeneration demonstrating the power of the suggested optimization framework.

Suggested Citation

  • Voll, Philip & Lampe, Matthias & Wrobel, Gregor & Bardow, André, 2012. "Superstructure-free synthesis and optimization of distributed industrial energy supply systems," Energy, Elsevier, vol. 45(1), pages 424-435.
  • Handle: RePEc:eee:energy:v:45:y:2012:i:1:p:424-435
    DOI: 10.1016/j.energy.2012.01.041
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    8. Jennings, Mark & Fisk, David & Shah, Nilay, 2014. "Modelling and optimization of retrofitting residential energy systems at the urban scale," Energy, Elsevier, vol. 64(C), pages 220-233.
    9. Chun, André & Donatelli, João Luiz Marcon & Santos, José Joaquim Conceição Soares & Zabeu, Clayton Barcelos & Carvalho, Monica, 2023. "Superstructure optimization of absorption chillers integrated with a large internal combustion engine for waste heat recovery and repowering applications: Thermodynamic and economic assessments," Energy, Elsevier, vol. 263(PE).
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    12. Ligang Wang & Zhiping Yang & Shivom Sharma & Alberto Mian & Tzu-En Lin & George Tsatsaronis & François Maréchal & Yongping Yang, 2018. "A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants," Energies, MDPI, vol. 12(1), pages 1-53, December.
    13. Sergio Rech, 2019. "Smart Energy Systems: Guidelines for Modelling and Optimizing a Fleet of Units of Different Configurations," Energies, MDPI, vol. 12(7), pages 1-36, April.
    14. Sakalis, George N. & Frangopoulos, Christos A., 2018. "Intertemporal optimization of synthesis, design and operation of integrated energy systems of ships: General method and application on a system with Diesel main engines," Applied Energy, Elsevier, vol. 226(C), pages 991-1008.
    15. Zheng, Xuyue & Qiu, Yuwei & Zhan, Xiangyan & Zhu, Xingyi & Keirstead, James & Shah, Nilay & Zhao, Yingru, 2017. "Optimization based planning of urban energy systems: Retrofitting a Chinese industrial park as a case-study," Energy, Elsevier, vol. 139(C), pages 31-41.
    16. Lin, Shan & Zhao, Li & Deng, Shuai & Zhao, Dongpeng & Wang, Wei & Chen, Mengchao, 2020. "Intelligent collaborative attainment of structure configuration and fluid selection for the Organic Rankine cycle," Applied Energy, Elsevier, vol. 264(C).
    17. Wang, Ligang & Voll, Philip & Lampe, Matthias & Yang, Yongping & Bardow, André, 2015. "Superstructure-free synthesis and optimization of thermal power plants," Energy, Elsevier, vol. 91(C), pages 700-711.
    18. Lythcke-Jørgensen, Christoffer & Ensinas, Adriano Viana & Münster, Marie & Haglind, Fredrik, 2016. "A methodology for designing flexible multi-generation systems," Energy, Elsevier, vol. 110(C), pages 34-54.
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