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Operation optimization for combined cooling, heating, and power system with condensation heat recovery

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  • Li, Fan
  • Sun, Bo
  • Zhang, Chenghui
  • Zhang, Lizhi

Abstract

Combined cooling, heating, and power (CCHP) systems can achieve highly efficient utilization of resources and energy by using waste heat recovery technology, which offers a key solution to global warming and energy security. This paper proposes a CCHP system with condensation heat recovery (CCHP-CHR). It has the advantage that the domestic hot water is produced from the condensation heat of the absorption chiller and heat pump instead of from electricity and fuel. Further, an optimization model is established for optimum operation performance, selecting energy, economy, and environment as optimization objectives. The complex model is reasonably divided into 24 sub-problems so that the Genetic Algorithm can be employed to calculate the optimal solution in sequence. Case studies, based on the typical daily load curves of a hotel building, have been conducted to verify the superiority and effectiveness of the proposed method. Compared with the traditional CCHP system, the proposed system increases the primary energy saving ratio, cost saving ratio, and carbon dioxide emission reduction ratio by 5.0%, 6.36%, and 2.74%, respectively. The proposed CCHP-CHR system improves the overall performance and enhances the technology of energy cascade utilization.

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  • Li, Fan & Sun, Bo & Zhang, Chenghui & Zhang, Lizhi, 2018. "Operation optimization for combined cooling, heating, and power system with condensation heat recovery," Applied Energy, Elsevier, vol. 230(C), pages 305-316.
    • Handle: RePEc:eee:appene:v:230:y:2018:i:c:p:305-316
    DOI: 10.1016/j.apenergy.2018.08.101
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    19. Xiao Gong & Fan Li & Bo Sun & Dong Liu, 2020. "Collaborative Optimization of Multi-Energy Complementary Combined Cooling, Heating, and Power Systems Considering Schedulable Loads," Energies, MDPI, vol. 13(4), pages 1-17, February.
    20. Li, Fan & Sun, Bo & Zhang, Chenghui & Liu, Che, 2019. "A hybrid optimization-based scheduling strategy for combined cooling, heating, and power system with thermal energy storage," Energy, Elsevier, vol. 188(C).
    21. Maier, Laura & Schönegge, Marius & Henn, Sarah & Hering, Dominik & Müller, Dirk, 2022. "Assessing mixed-integer-based heat pump modeling approaches for model predictive control applications in buildings," Applied Energy, Elsevier, vol. 326(C).
    22. Zhao, Xin & Zheng, Wenyu & Hou, Zhihua & Chen, Heng & Xu, Gang & Liu, Wenyi & Chen, Honggang, 2022. "Economic dispatch of multi-energy system considering seasonal variation based on hybrid operation strategy," Energy, Elsevier, vol. 238(PA).
    23. Fan Li & Jingxi Su & Bo Sun, 2023. "An Optimal Scheduling Method for an Integrated Energy System Based on an Improved k-Means Clustering Algorithm," Energies, MDPI, vol. 16(9), pages 1-22, April.
    24. Salata, Ferdinando & Ciancio, Virgilio & Dell'Olmo, Jacopo & Golasi, Iacopo & Palusci, Olga & Coppi, Massimo, 2020. "Effects of local conditions on the multi-variable and multi-objective energy optimization of residential buildings using genetic algorithms," Applied Energy, Elsevier, vol. 260(C).

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