IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v284y2021ics030626192031597x.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192031597X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2020.116197?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. Best, Robert E. & Flager, Forest & Lepech, Michael D., 2015. "Modeling and optimization of building mix and energy supply technology for urban districts," Applied Energy, Elsevier, vol. 159(C), pages 161-177.
    2. Luo, Xing & Wang, Jihong & Krupke, Christopher & Wang, Yue & Sheng, Yong & Li, Jian & Xu, Yujie & Wang, Dan & Miao, Shihong & Chen, Haisheng, 2016. "Modelling study, efficiency analysis and optimisation of large-scale Adiabatic Compressed Air Energy Storage systems with low-temperature thermal storage," Applied Energy, Elsevier, vol. 162(C), pages 589-600.
    3. Budt, Marcus & Wolf, Daniel & Span, Roland & Yan, Jinyue, 2016. "A review on compressed air energy storage: Basic principles, past milestones and recent developments," Applied Energy, Elsevier, vol. 170(C), pages 250-268.
    4. Cappa, Francesco & Facci, Andrea Luigi & Ubertini, Stefano, 2015. "Proton exchange membrane fuel cell for cooperating households: A convenient combined heat and power solution for residential applications," Energy, Elsevier, vol. 90(P2), pages 1229-1238.
    5. Bokrantz, Rasmus & Fredriksson, Albin, 2017. "Necessary and sufficient conditions for Pareto efficiency in robust multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 262(2), pages 682-692.
    6. Wang, Jiangjiang & Lu, Zherui & Li, Meng & Lior, Noam & Li, Weihua, 2019. "Energy, exergy, exergoeconomic and environmental (4E) analysis of a distributed generation solar-assisted CCHP (combined cooling, heating and power) gas turbine system," Energy, Elsevier, vol. 175(C), pages 1246-1258.
    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. 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).
    2. 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).
    3. 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).
    4. 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).
    5. 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.
    6. 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).
    7. 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.
    8. 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).

    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. Cheayb, Mohamad & Marin Gallego, Mylène & Tazerout, Mohand & Poncet, Sébastien, 2022. "A techno-economic analysis of small-scale trigenerative compressed air energy storage system," Energy, Elsevier, vol. 239(PA).
    2. Guo, Cong & Xu, Yujie & Zhang, Xinjing & Guo, Huan & Zhou, Xuezhi & Liu, Chang & Qin, Wei & Li, Wen & Dou, Binlin & Chen, Haisheng, 2017. "Performance analysis of compressed air energy storage systems considering dynamic characteristics of compressed air storage," Energy, Elsevier, vol. 135(C), pages 876-888.
    3. He, Yang & MengWang, & Chen, Haisheng & Xu, Yujie & Deng, Jianqiang, 2021. "Thermodynamic research on compressed air energy storage system with turbines under sliding pressure operation," Energy, Elsevier, vol. 222(C).
    4. He, Yang & Chen, Haisheng & Xu, Yujie & Deng, Jianqiang, 2018. "Compression performance optimization considering variable charge pressure in an adiabatic compressed air energy storage system," Energy, Elsevier, vol. 165(PB), pages 349-359.
    5. Hao, Yinping & He, Qing & Du, Dongmei, 2020. "A trans-critical carbon dioxide energy storage system with heat pump to recover stored heat of compression," Renewable Energy, Elsevier, vol. 152(C), pages 1099-1108.
    6. Luo, Xing & Dooner, Mark & He, Wei & Wang, Jihong & Li, Yaowang & Li, Decai & Kiselychnyk, Oleh, 2018. "Feasibility study of a simulation software tool development for dynamic modelling and transient control of adiabatic compressed air energy storage with its electrical power system applications," Applied Energy, Elsevier, vol. 228(C), pages 1198-1219.
    7. Wang, Zhiwen & Xiong, Wei & Ting, David S.-K. & Carriveau, Rupp & Wang, Zuwen, 2016. "Conventional and advanced exergy analyses of an underwater compressed air energy storage system," Applied Energy, Elsevier, vol. 180(C), pages 810-822.
    8. Sarmast, Sepideh & Rouindej, Kamyar & Fraser, Roydon A. & Dusseault, Maurice B., 2024. "Optimizing near-adiabatic compressed air energy storage (NA-CAES) systems: Sizing and design considerations," Applied Energy, Elsevier, vol. 357(C).
    9. Liu, Zhan & Liu, Zihui & Xin, Xuan & Yang, Xiaohu, 2020. "Proposal and assessment of a novel carbon dioxide energy storage system with electrical thermal storage and ejector condensing cycle: Energy and exergy analysis," Applied Energy, Elsevier, vol. 269(C).
    10. Guo, Chaobin & Pan, Lehua & Zhang, Keni & Oldenburg, Curtis M. & Li, Cai & Li, Yi, 2016. "Comparison of compressed air energy storage process in aquifers and caverns based on the Huntorf CAES plant," Applied Energy, Elsevier, vol. 181(C), pages 342-356.
    11. Zhan, Junpeng & Ansari, Osama Aslam & Liu, Weijia & Chung, C.Y., 2019. "An accurate bilinear cavern model for compressed air energy storage," Applied Energy, Elsevier, vol. 242(C), pages 752-768.
    12. Roos, P. & Haselbacher, A., 2022. "Analytical modeling of advanced adiabatic compressed air energy storage: Literature review and new models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    13. Li, Ruixiong & Wang, Huanran & Zhang, Haoran, 2019. "Dynamic simulation of a cooling, heating and power system based on adiabatic compressed air energy storage," Renewable Energy, Elsevier, vol. 138(C), pages 326-339.
    14. Guo, Chaobin & Zhang, Keni & Pan, Lehua & Cai, Zuansi & Li, Cai & Li, Yi, 2017. "Numerical investigation of a joint approach to thermal energy storage and compressed air energy storage in aquifers," Applied Energy, Elsevier, vol. 203(C), pages 948-958.
    15. Courtois, Nicolas & Najafiyazdi, Mostafa & Lotfalian, Reza & Boudreault, Richard & Picard, Mathieu, 2021. "Analytical expression for the evaluation of multi-stage adiabatic-compressed air energy storage (A-CAES) systems cycle efficiency," Applied Energy, Elsevier, vol. 288(C).
    16. Cheayb, Mohamad & Marin Gallego, Mylène & Tazerout, Mohand & Poncet, Sébastien, 2019. "Modelling and experimental validation of a small-scale trigenerative compressed air energy storage system," Applied Energy, Elsevier, vol. 239(C), pages 1371-1384.
    17. Han, Ji & Miao, Shihong & Chen, Zhe & Liu, Zhou & Li, Yaowang & Yang, Weichen & Liu, Ziwen, 2021. "Multi-View clustering and discrete consensus based tri-level coordinated control of wind farm and adiabatic compressed air energy storage for providing frequency regulation service," Applied Energy, Elsevier, vol. 304(C).
    18. Sciacovelli, Adriano & Li, Yongliang & Chen, Haisheng & Wu, Yuting & Wang, Jihong & Garvey, Seamus & Ding, Yulong, 2017. "Dynamic simulation of Adiabatic Compressed Air Energy Storage (A-CAES) plant with integrated thermal storage – Link between components performance and plant performance," Applied Energy, Elsevier, vol. 185(P1), pages 16-28.
    19. Guo, Huan & Xu, Yujie & Chen, Haisheng & Guo, Cong & Qin, Wei, 2017. "Thermodynamic analytical solution and exergy analysis for supercritical compressed air energy storage system," Applied Energy, Elsevier, vol. 199(C), pages 96-106.
    20. Peng, Hao & Yang, Yu & Li, Rui & Ling, Xiang, 2016. "Thermodynamic analysis of an improved adiabatic compressed air energy storage system," Applied Energy, Elsevier, vol. 183(C), pages 1361-1373.

    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:appene:v:284:y:2021:i:c:s030626192031597x. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.