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Experimental and modeling investigation of an ICE (internal combustion engine) based micro-cogeneration device considering overheat protection controls

Author

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  • Zheng, C.Y.
  • Wu, J.Y.
  • Zhai, X.Q.
  • Yang, G.
  • Wang, R.Z.

Abstract

A dynamic simulation model for the micro-cogeneration unit based on ICE (internal combustion engine) is built as a new component on TRNSYS. This model considers dynamic processes including start-up, cool-down, and overheat protection controls. Through an experiment study, the steady and dynamic performances of the unit are presented and analyzed for calibrating the parameters of the dynamic model. Then the model is validated by the experiment data during steady and dynamic processes. The improvement of prediction accuracy of the model by considering dynamic processes is analyzed. The validation results show that the dynamic model can well predict the characteristics of the unit during start-up, cool-down, and overheat protection control processes. The cumulative prediction errors of the dynamic model decrease with the increase of the start–stop interval. By considering the dynamic processes, 5.18% and 3.2% of Qth and ηtotal cumulative prediction errors are decreased respectively when the start–stop interval is 0.5 h. The primary energy saving ratio and CO2 emission reduction ratio increases with the increase of the start–stop interval. The start–stop interval for the unit in this paper should be longer than 0.5 h, or the energy consumption of micro-cogeneration unit would be larger than that of conventional system.

Suggested Citation

  • Zheng, C.Y. & Wu, J.Y. & Zhai, X.Q. & Yang, G. & Wang, R.Z., 2016. "Experimental and modeling investigation of an ICE (internal combustion engine) based micro-cogeneration device considering overheat protection controls," Energy, Elsevier, vol. 101(C), pages 447-461.
  • Handle: RePEc:eee:energy:v:101:y:2016:i:c:p:447-461
    DOI: 10.1016/j.energy.2016.02.030
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    References listed on IDEAS

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    1. Zheng, C.Y. & Wu, J.Y. & Zhai, X.Q., 2014. "A novel operation strategy for CCHP systems based on minimum distance," Applied Energy, Elsevier, vol. 128(C), pages 325-335.
    2. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa, 2010. "Optimization of capacity and operation for CCHP system by genetic algorithm," Applied Energy, Elsevier, vol. 87(4), pages 1325-1335, April.
    3. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    4. Martínez-Lera, S. & Ballester, J., 2010. "A novel method for the design of CHCP (combined heat, cooling and power) systems for buildings," Energy, Elsevier, vol. 35(7), pages 2972-2984.
    5. Moradi, Mohammad H. & Hajinazari, Mehdi & Jamasb, Shahriar & Paripour, Mahmoud, 2013. "An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming," Energy, Elsevier, vol. 49(C), pages 86-101.
    6. Hawkes, Adam & Leach, Matthew, 2005. "Impacts of temporal precision in optimisation modelling of micro-Combined Heat and Power," Energy, Elsevier, vol. 30(10), pages 1759-1779.
    7. Cho, Heejin & Smith, Amanda D. & Mago, Pedro, 2014. "Combined cooling, heating and power: A review of performance improvement and optimization," Applied Energy, Elsevier, vol. 136(C), pages 168-185.
    8. Sanaye, Sepehr & Khakpaay, Navid, 2014. "Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems," Energy, Elsevier, vol. 72(C), pages 145-158.
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    3. Hu, Yiwei & Luo, Kaiqi & Zhao, Dan & Chi, Jiaxin & Chen, Geng & Chen, Yuanhang & Luo, Ercang & Xu, Jingyuan, 2024. "Thermoacoustic micro-CHP system for low-grade thermal energy utilization in residential buildings," Energy, Elsevier, vol. 298(C).
    4. Wang, Xuan & Shu, Gequn & Tian, Hua & Wang, Rui & Cai, Jinwen, 2020. "Operation performance comparison of CCHP systems with cascade waste heat recovery systems by simulation and operation optimisation," Energy, Elsevier, vol. 206(C).
    5. Karimi, Ali & Gimelli, Alfredo & Iossa, Raffaele & Muccillo, Massimiliano, 2024. "Techno-economic simulation and sensitivity analysis of modular cogeneration with organic rankine cycle and battery energy storage system for enhanced energy performance," Energy, Elsevier, vol. 295(C).
    6. Dominik Kryzia & Marta Kuta & Dominika Matuszewska & Piotr Olczak, 2020. "Analysis of the Potential for Gas Micro-Cogeneration Development in Poland Using the Monte Carlo Method," Energies, MDPI, vol. 13(12), pages 1-24, June.
    7. Edisson S. Castaño Mesa & Sebastián H. Quintana & Iván D. Bedoya, 2023. "Development of a Dual Fuel ICE-Based Micro-CHP System and Experimental Evaluation of Its Performance at Light Loads Using Natural Gas as Primary Fuel," Energies, MDPI, vol. 16(17), pages 1-24, August.
    8. Praveen Cheekatamarla & Ahmad Abu-Heiba, 2020. "A Comprehensive Review and Qualitative Analysis of Micro-Combined Heat and Power Modeling Approaches," Energies, MDPI, vol. 13(14), pages 1-26, July.
    9. Li, Xian & Shen, Ye & Kan, Xiang & Hardiman, Timothy Kurnia & Dai, Yanjun & Wang, Chi-Hwa, 2018. "Thermodynamic assessment of a solar/autothermal hybrid gasification CCHP system with an indirectly radiative reactor," Energy, Elsevier, vol. 142(C), pages 201-214.

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