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Multidisciplinary design optimization of distributed energy generation systems: The trade-offs between life cycle environmental and economic impacts

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  • Yan, Junchen
  • Broesicke, Osvaldo A.
  • Tong, Xin
  • Wang, Dong
  • Li, Duo
  • Crittenden, John C.

Abstract

Distributed energy systems (DES) are the focus of increasing attention because they have the potential to enhance the sustainability performance of energy generation. Previous DES researches evaluated various distributed energy technologies and systems from different aspects. However, there is still a research gap to evaluate and compare the multiple technology combinations and sizes for finding optimal energy solutions under various scenarios. This study aims to determine the best combination of technologies and their corresponding sizes for DES for various building types and climate zones in terms of life cycle environmental and economic impact. We developed parametric models (which considers dynamic hour by hour energy demand) for six commercially available distributed energy technologies and simulated the performance of them under various conditions. Then, we used a novel approach – multidisciplinary design optimization (MDO) to examine the billions of options (e.g., technologies, sizes, climate zone, Etc.) and identified the Pareto front with the optimal environmental and economic impact. According to MDO simulations, the microturbine-solar PVs-lithium ion battery and solid oxide fuel cells-solar PVs-lithium ion battery are two optimal combinations of technologies for three commercial building types for five climate zones. The DES can primarily reduce the environmental impact compared to conventional centralized energy production (CCEP) by 16–61% in all scenarios. However, the life cycle cost of DES is higher than CCEP, especially for SOFC-based DES. The microturbine-based DES is more cost-competitive and economical (about 65%, 32%, and 64% lower than SOFC-based DES for the small, medium, and large office, respectively).

Suggested Citation

  • Yan, Junchen & Broesicke, Osvaldo A. & Tong, Xin & Wang, Dong & Li, Duo & Crittenden, John C., 2021. "Multidisciplinary design optimization of distributed energy generation systems: The trade-offs between life cycle environmental and economic impacts," Applied Energy, Elsevier, vol. 284(C).
    • Handle: RePEc:eee:appene:v:284:y:2021:i:c:s030626192031597x
    DOI: 10.1016/j.apenergy.2020.116197
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    Cited by:

    1. Khaled M. A. Salim & Ruhanita Maelah & Hawa Hishamuddin & Amizawati Mohd Amir & Mohd Nizam Ab Rahman, 2022. "Two Decades of Life Cycle Sustainability Assessment of Solid Oxide Fuel Cells (SOFCs): A Review," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    2. Bai, Zhang & Yuan, Yu & Kong, Debin & Zhou, Shengdong & Li, Qi & Wang, Shuoshuo, 2023. "Potential of applying the thermochemical recuperation in combined cooling, heating and power generation: Off-design operation performance," Applied Energy, Elsevier, vol. 348(C).
    3. Guo, Jiacheng & Liu, Zhijian & Wu, Xuan & Wu, Di & Zhang, Shicong & Yang, Xinyan & Ge, Hua & Zhang, Peiwen, 2022. "Two-layer co-optimization method for a distributed energy system combining multiple energy storages," Applied Energy, Elsevier, vol. 322(C).
    4. 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.
    5. Liu, Jia & Ma, Tao & Wu, Huijun & Yang, Hongxing, 2023. "Study on optimum energy fuel mix for urban cities integrated with pumped hydro storage and green vehicles," Applied Energy, Elsevier, vol. 331(C).
    6. Ma, Huan & Sun, Qinghan & Chen, Qun & Zhao, Tian & He, Kelun, 2023. "Exergy-based flexibility cost indicator and spatio-temporal coordination principle of distributed multi-energy systems," Energy, Elsevier, vol. 267(C).
    7. Zhou, Yuan & Wang, Jiangjiang & Li, Yuxin & Wei, Changqi, 2023. "A collaborative management strategy for multi-objective optimization of sustainable distributed energy system considering cloud energy storage," Energy, Elsevier, vol. 280(C).
    8. Guo, Jiacheng & Zhang, Peiwen & Wu, Di & Liu, Zhijian & Liu, Xuan & Zhang, Shicong & Yang, Xinyan & Ge, Hua, 2022. "Multi-objective optimization design and multi-attribute decision-making method of a distributed energy system based on nearly zero-energy community load forecasting," Energy, Elsevier, vol. 239(PC).

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