IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v206y2023icp72-85.html
   My bibliography  Save this article

Optimal design of a novel hybrid renewable energy CCHP system considering long and short-term benefits

Author

Listed:
  • Ma, Zherui
  • Dong, Fuxiang
  • Wang, Jiangjiang
  • Zhou, Yuan
  • Feng, Yingsong

Abstract

The combination of biomass and solar energy in the combined cooling heating and power (CCHP) system is conducive to reducing carbon dioxide emissions of the system. To improve the system's economic performance under the punishment of carbon tax, this paper optimizes the system from system design and operation strategies. A hybrid renewable energy CCHP system with shaft power distribution structure of an internal combustion engine (ICE) is proposed. By optimizing the shaft power distribution of ICE, the direct drive heat pump is realized, and the efficiency of the shaft power of ICE is improved. A double-layer optimization method considering the long and short-term benefits is proposed based on the system, fully improving the system economy in design and operation. The case study shows that the CCHP system reduces the annual cost by 40.37% and the CO2 emission by 88.93% compared with the separate production system. Compared with the non-shaft power distribution system, the maximum daily operation cost is saved by 557.11CNY. Compared with the hourly optimization method, the proposed optimization method based on total daily benefit reduces the annual cost by 7.73% and CO2 emission by 35.87%, and the utilization rate of the energy storage device is higher.

Suggested Citation

  • Ma, Zherui & Dong, Fuxiang & Wang, Jiangjiang & Zhou, Yuan & Feng, Yingsong, 2023. "Optimal design of a novel hybrid renewable energy CCHP system considering long and short-term benefits," Renewable Energy, Elsevier, vol. 206(C), pages 72-85.
  • Handle: RePEc:eee:renene:v:206:y:2023:i:c:p:72-85
    DOI: 10.1016/j.renene.2023.02.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123001593
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2023.02.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ting, Chen-Ching & Lee, Jing-Nang & Shen, Chun-Hong, 2008. "Development of a wind forced chiller and its efficiency analysis," Applied Energy, Elsevier, vol. 85(12), pages 1190-1197, December.
    2. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    3. Wang, Jiangjiang & Mao, Tianzhi & Sui, Jun & Jin, Hongguang, 2015. "Modeling and performance analysis of CCHP (combined cooling, heating and power) system based on co-firing of natural gas and biomass gasification gas," Energy, Elsevier, vol. 93(P1), pages 801-815.
    4. Situmorang, Yohanes Andre & Zhao, Zhongkai & Yoshida, Akihiro & Abudula, Abuliti & Guan, Guoqing, 2020. "Small-scale biomass gasification systems for power generation (<200 kW class): A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    5. Sheykhi, Mohammad & Chahartaghi, Mahmood & Safaei Pirooz, Amir Ali & Flay, Richard G.J., 2020. "Investigation of the effects of operating parameters of an internal combustion engine on the performance and fuel consumption of a CCHP system," Energy, Elsevier, vol. 211(C).
    6. Jarungthammachote, S. & Dutta, A., 2007. "Thermodynamic equilibrium model and second law analysis of a downdraft waste gasifier," Energy, Elsevier, vol. 32(9), pages 1660-1669.
    7. Uris, María & Linares, José Ignacio & Arenas, Eva, 2015. "Size optimization of a biomass-fired cogeneration plant CHP/CCHP (Combined heat and power/Combined heat, cooling and power) based on Organic Rankine Cycle for a district network in Spain," Energy, Elsevier, vol. 88(C), pages 935-945.
    8. Li, Yang & Feng, Bo & Li, Guoqing & Qi, Junjian & Zhao, Dongbo & Mu, Yunfei, 2018. "Optimal distributed generation planning in active distribution networks considering integration of energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1073-1081.
    9. Wang, Jiangjiang & Ma, Chaofan & Wu, Jing, 2019. "Thermodynamic analysis of a combined cooling, heating and power system based on solar thermal biomass gasification☆," Applied Energy, Elsevier, vol. 247(C), pages 102-115.
    10. Wang, Yuwei & Tang, Liu & Yang, Yuanjuan & Sun, Wei & Zhao, Huiru, 2020. "A stochastic-robust coordinated optimization model for CCHP micro-grid considering multi-energy operation and power trading with electricity markets under uncertainties," Energy, Elsevier, vol. 198(C).
    11. Skorek-Osikowska, Anna & Bartela, Łukasz & Kotowicz, Janusz & Sobolewski, Aleksander & Iluk, Tomasz & Remiorz, Leszek, 2014. "The influence of the size of the CHP (combined heat and power) system integrated with a biomass fueled gas generator and piston engine on the thermodynamic and economic effectiveness of electricity an," Energy, Elsevier, vol. 67(C), pages 328-340.
    12. Zhang, Shenxi & Cheng, Haozhong & Wang, Dan & Zhang, Libo & Li, Furong & Yao, Liangzhong, 2018. "Distributed generation planning in active distribution network considering demand side management and network reconfiguration," Applied Energy, Elsevier, vol. 228(C), pages 1921-1936.
    13. 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.
    14. Zhang, Guoqing & Wang, Jiangjiang & Ren, Fukang & Liu, Yi & Dong, Fuxiang, 2021. "Collaborative optimization for multiple energy stations in distributed energy network based on electricity and heat interchanges," Energy, Elsevier, vol. 222(C).
    15. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    16. Meriño Stand, L. & Valencia Ochoa, G. & Duarte Forero, J., 2021. "Energy and exergy assessment of a combined supercritical Brayton cycle-orc hybrid system using solar radiation and coconut shell biomass as energy source," Renewable Energy, Elsevier, vol. 175(C), pages 119-142.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guan, Zhimin & Lu, Chunyan & Li, Yiming & Wang, Jiangjiang, 2023. "Chance-constrained optimization of hybrid solar combined cooling, heating and power system considering energetic, economic, environmental, and flexible performances," Renewable Energy, Elsevier, vol. 212(C), pages 908-920.
    2. Ai, Tianchao & Chen, Hongwei & Zhong, Fanghao & Jia, Jiandong & Song, Yangfan, 2023. "Multi-objective optimization of a novel CCHP system with organic flash cycle based on different operating strategies," Energy, Elsevier, vol. 276(C).
    3. Cai, Shanshan & Wang, Wenli & Zou, Yuqi & Li, Song & Tu, Zhengkai, 2023. "Performance and sustainability assessment of PEMFC/solar-driven CCP systems with different energy storage devices," Energy, Elsevier, vol. 278(PB).
    4. Dong, Fuxiang & Wang, Jiangjiang & Xu, Hangwei & Zhang, Xutao, 2024. "A robust real-time energy scheduling strategy of integrated energy system based on multi-step interval prediction of uncertainties," Energy, Elsevier, vol. 300(C).
    5. Zhao, Xiangming & Guo, Jianxiang & He, Maogang, 2023. "Multi-objective optimization and improvement of multi-energy combined cooling, heating and power system based on system simplification," Renewable Energy, Elsevier, vol. 217(C).
    6. Zhu, Xiaoxuan & Wang, Peng & Zhang, Hui & Wang, Shiqiang & Xv, Shuaiquan & Liu, Hailong & Zhang, Yihua & Zhao, Dong & Han, Jitian, 2024. "A highly efficient, low-carbon CCHP system and its comprehensive optimization for an integrated medical and nursing complex," Renewable Energy, Elsevier, vol. 227(C).
    7. Zheng, Xidong & Chen, Huangbin & Jin, Tao, 2024. "A new optimization approach considering demand response management and multistage energy storage: A novel perspective for Fujian Province," Renewable Energy, Elsevier, vol. 220(C).
    8. Ren, Xin-Yu & Li, Ling-Ling & Ji, Bing-Xiang & Liu, Jia-Qi, 2024. "Design and analysis of solar hybrid combined cooling, heating and power system: A bi-level optimization model," Energy, Elsevier, vol. 292(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ren, Fukang & Lin, Xiaozhen & Wei, Ziqing & Zhai, Xiaoqiang & Yang, Jianrong, 2022. "A novel planning method for design and dispatch of hybrid energy systems," Applied Energy, Elsevier, vol. 321(C).
    2. Han, Zepeng & Wang, Jiangjiang & Cui, Zhiheng & Lu, Chunyan & Qi, Xiaoling, 2021. "Multi-objective optimization and exergoeconomic analysis for a novel full-spectrum solar-assisted methanol combined cooling, heating, and power system," Energy, Elsevier, vol. 237(C).
    3. Ahmed M. Salem & Harnek S. Dhami & Manosh C. Paul, 2022. "Syngas Production and Combined Heat and Power from Scottish Agricultural Waste Gasification—A Computational Study," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    4. Jie, Pengfei & Zhao, Wanyue & Yan, Fuchun & Man, Xiaoxin & Liu, Chunhua, 2022. "Economic, energetic and environmental optimization of hybrid biomass gasification-based combined cooling, heating and power system based on an improved operating strategy," Energy, Elsevier, vol. 240(C).
    5. Li, Xian & Kan, Xiang & Sun, Xiangyu & Zhao, Yao & Ge, Tianshu & Dai, Yanjun & Wang, Chi-Hwa, 2019. "Performance analysis of a biomass gasification-based CCHP system integrated with variable-effect LiBr-H2O absorption cooling and desiccant dehumidification," Energy, Elsevier, vol. 176(C), pages 961-979.
    6. Qi, Haijie & Yue, Hong & Zhang, Jiangfeng & Lo, Kwok L., 2021. "Optimisation of a smart energy hub with integration of combined heat and power, demand side response and energy storage," Energy, Elsevier, vol. 234(C).
    7. Adnan, Muflih A. & Hossain, Mohammad M. & Kibria, Md Golam, 2020. "Biomass upgrading to high-value chemicals via gasification and electrolysis: A thermodynamic analysis," Renewable Energy, Elsevier, vol. 162(C), pages 1367-1379.
    8. Li, Yang & Yang, Zhen & Li, Guoqing & Mu, Yunfei & Zhao, Dongbo & Chen, Chen & Shen, Bo, 2018. "Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: A bi-level programming approach via real-time pricing," Applied Energy, Elsevier, vol. 232(C), pages 54-68.
    9. Ge, Yongkai & Ma, Yue & Wang, Qingrui & Yang, Qing & Xing, Lu & Ba, Shusong, 2023. "Techno-economic-environmental assessment and performance comparison of a building distributed multi-energy system under various operation strategies," Renewable Energy, Elsevier, vol. 204(C), pages 685-696.
    10. Wu, Raphael & Sansavini, Giovanni, 2021. "Energy trilemma in active distribution network design: Balancing affordability, sustainability and security in optimization-based decision-making," Applied Energy, Elsevier, vol. 304(C).
    11. Yang, Dongfeng & Jiang, Chao & Cai, Guowei & Yang, Deyou & Liu, Xiaojun, 2020. "Interval method based optimal planning of multi-energy microgrid with uncertain renewable generation and demand," Applied Energy, Elsevier, vol. 277(C).
    12. Jin Wu & Jiangjiang Wang & Jing Wu & Chaofan Ma, 2019. "Exergy and Exergoeconomic Analysis of a Combined Cooling, Heating, and Power System Based on Solar Thermal Biomass Gasification," Energies, MDPI, vol. 12(12), pages 1-19, June.
    13. Das, Choton K. & Bass, Octavian & Kothapalli, Ganesh & Mahmoud, Thair S. & Habibi, Daryoush, 2018. "Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm," Applied Energy, Elsevier, vol. 232(C), pages 212-228.
    14. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Shi, Lin & Li, Bingkang, 2023. "TimeGAN based distributionally robust optimization for biomass-photovoltaic-hydrogen scheduling under source-load-market uncertainties," Energy, Elsevier, vol. 284(C).
    15. Panda, Deepak Kumar & Das, Saptarshi, 2021. "Economic operational analytics for energy storage placement at different grid locations and contingency scenarios with stochastic wind profiles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    16. Li, Bingkang & Zhao, Huiru & Wang, Xuejie & Zhao, Yihang & Zhang, Yuanyuan & Lu, Hao & Wang, Yuwei, 2022. "Distributionally robust offering strategy of the aggregator integrating renewable energy generator and energy storage considering uncertainty and connections between the mid-to-long-term and spot elec," Renewable Energy, Elsevier, vol. 201(P1), pages 400-417.
    17. Hang Liu & Yongcheng Wang & Shilin Nie & Yi Wang & Yu Chen, 2022. "Multistage Economic Scheduling Model of Micro-Energy Grids Considering Flexible Capacity Allocation," Sustainability, MDPI, vol. 14(15), pages 1-29, July.
    18. Alessandro Saldarini & Michela Longo & Morris Brenna & Dario Zaninelli, 2023. "Battery Electric Storage Systems: Advances, Challenges, and Market Trends," Energies, MDPI, vol. 16(22), pages 1-30, November.
    19. Sepideh Rezaeeian & Narges Bayat & Abbas Rabiee & Saman Nikkhah & Alireza Soroudi, 2022. "Optimal Scheduling of Reconfigurable Microgrids in Both Grid-Connected and Isolated Modes Considering the Uncertainty of DERs," Energies, MDPI, vol. 15(15), pages 1-18, July.
    20. Li, Yang & Feng, Bo & Wang, Bin & Sun, Shuchao, 2022. "Joint planning of distributed generations and energy storage in active distribution networks: A Bi-Level programming approach," Energy, Elsevier, vol. 245(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:206:y:2023:i:c:p:72-85. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.