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Comprehensive performance evaluation of Wind-Solar-CCHP system based on emergy analysis and multi-objective decision method

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  • Qian, Jiaxin
  • Wu, Jiahui
  • Yao, Lei
  • Mahmut, Saniye
  • Zhang, Qiang

Abstract

To make full use of abundant new energy sources and meet the diverse energy demands of users, a system with new energy resources could be used to realize a combined cooling, heating, and power (CCHP) system. Environmental pressure can be reduced when new energy is used as a heat source or auxiliary power source. However, many kinds of energy can lead to uncertainty, low energy utilization rate, and high cost with the increasing types of energy. Therefore, an evaluation method of the advantages and disadvantages of a CCHP system coupled with wind and solar (Wind-Solar-CCHP) is needed. Firstly, emergy theory is introduced to evaluate the sustainable development level of the two systems, and a new comprehensive evaluation index system is established by combining emergy indexes with traditional indicators. Secondly, a multi-objective decision-making (MODM) method is proposed based on fuzzy-analytic hierarchy process (Fuzzy-AHP), anti-entropy weighting (AEW), and game theory to calculate the weights of these indexes. Then, the Kendall rank correlation coefficient is used to determine the correlation between the CCHP and Wind-Solar-CCHP systems. Taking the CCHP system as a reference, the integrated performance of the systems is analyzed by using the fuzzy comprehensive evaluation (FCE) method. Finally, an example of a hotel in a city in western China is selected for verification. The accuracy and robustness of the proposed method were verified by sensitivity analysis. The obtained experimental results indicate that the comprehensive performance of the Wind-Solar-CCHP system was superior to that of the CCHP system. Compared with other methods in the literature, the proposed method could achieve unification of subjective and objective attribute weights, overcome the limitations of the existing single evaluation method, and make the evaluation results more accurate. Moreover, these research results can provide a reference for the comprehensive utilization of new energy in China.

Suggested Citation

  • Qian, Jiaxin & Wu, Jiahui & Yao, Lei & Mahmut, Saniye & Zhang, Qiang, 2021. "Comprehensive performance evaluation of Wind-Solar-CCHP system based on emergy analysis and multi-objective decision method," Energy, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:energy:v:230:y:2021:i:c:s0360544221010276
    DOI: 10.1016/j.energy.2021.120779
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    as
    1. Yang, Kun & Ding, Yan & Zhu, Neng & Yang, Fan & Wang, Qiaochu, 2018. "Multi-criteria integrated evaluation of distributed energy system for community energy planning based on improved grey incidence approach: A case study in Tianjin," Applied Energy, Elsevier, vol. 229(C), pages 352-363.
    2. Haisheng Chen & Xinjing Zhang & Jinchao Liu & Chunqing Tan, 2013. "Compressed Air Energy Storage," Chapters, in: Ahmed F. Zobaa (ed.), Energy Storage - Technologies and Applications, IntechOpen.
    3. Ma, Weiwu & Fang, Song & Liu, Gang, 2017. "Hybrid optimization method and seasonal operation strategy for distributed energy system integrating CCHP, photovoltaic and ground source heat pump," Energy, Elsevier, vol. 141(C), pages 1439-1455.
    4. Yang, Jin & Chen, Bin, 2016. "Emergy-based sustainability evaluation of wind power generation systems," Applied Energy, Elsevier, vol. 177(C), pages 239-246.
    5. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    6. Ren, Hongbo & Gao, Weijun & Zhou, Weisheng & Nakagami, Ken'ichi, 2009. "Multi-criteria evaluation for the optimal adoption of distributed residential energy systems in Japan," Energy Policy, Elsevier, vol. 37(12), pages 5484-5493, December.
    7. Si, Tong & Wang, Chunbo & Liu, Ruiqi & Guo, Yusheng & Yue, Shuang & Ren, Yujie, 2020. "Multi-criteria comprehensive energy efficiency assessment based on fuzzy-AHP method: A case study of post-treatment technologies for coal-fired units," Energy, Elsevier, vol. 200(C).
    8. Chen, Jialing & Li, Xian & Dai, Yanjun & Wang, Chi-Hwa, 2021. "Energetic, economic, and environmental assessment of a Stirling engine based gasification CCHP system," Applied Energy, Elsevier, vol. 281(C).
    9. 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).
    10. Bai, Zhang & Liu, Taixiu & Liu, Qibin & Lei, Jing & Gong, Liang & Jin, Hongguang, 2018. "Performance investigation of a new cooling, heating and power system with methanol decomposition based chemical recuperation process," Applied Energy, Elsevier, vol. 229(C), pages 1152-1163.
    Full references (including those not matched with items on IDEAS)

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    4. 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).
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    6. Karaaslan, Abdulkerim & Gezen, Mesliha, 2022. "The evaluation of renewable energy resources in Turkey by integer multi-objective selection problem with interval coefficient," Renewable Energy, Elsevier, vol. 182(C), pages 842-854.
    7. Zhao, Junjie & Luo, Xiaobing & Tu, Zhengkai & Hwa Chan, Siew, 2023. "A novel CCHP system based on a closed PEMEC-PEMFC loop with water self-supply," Applied Energy, Elsevier, vol. 338(C).

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