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Cost–Benefit Analysis of Distributed Energy Systems Considering the Monetization of Indirect Benefits

Author

Listed:
  • Yutong Zhao

    (State Grid Beijing Electric Power Research Institute, Beijing 100075, China)

  • Shuang Zeng

    (State Grid Beijing Electric Power Research Institute, Beijing 100075, China)

  • Yifeng Ding

    (State Grid Beijing Electric Power Research Institute, Beijing 100075, China)

  • Lin Ma

    (State Grid Beijing Electric Power Research Institute, Beijing 100075, China)

  • Zhao Wang

    (State Grid Beijing Electric Power Research Institute, Beijing 100075, China)

  • Anqi Liang

    (State Grid Beijing Electric Power Research Institute, Beijing 100075, China)

  • Hongbo Ren

    (College of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai 201306, China)

Abstract

Driven by market value, a co-benefits assessment framework to encompass various benefits arising from distributed energy systems is developed. Using a monetization approach, a quantitative analysis model is established to evaluate both direct and indirect benefits. According to the simulation results of typical distributed energy systems, the distributed photovoltaic (PV) system demonstrates superior economic performance compared with the gas-fired distributed energy system, highlighting its potential for widespread commercialization. Moreover, the inclusion of indirect benefits significantly enhances the economic viability of the distributed energy system. While the PV system exhibits a more favorable promotional impact, it also renders the gas-fired distributed energy system commercially feasible.

Suggested Citation

  • Yutong Zhao & Shuang Zeng & Yifeng Ding & Lin Ma & Zhao Wang & Anqi Liang & Hongbo Ren, 2024. "Cost–Benefit Analysis of Distributed Energy Systems Considering the Monetization of Indirect Benefits," Sustainability, MDPI, vol. 16(2), pages 1-14, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:820-:d:1321202
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    References listed on IDEAS

    as
    1. 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.
    2. Hoettecke, Lukas & Schuetz, Thomas & Thiem, Sebastian & Niessen, Stefan, 2022. "Technology pathways for industrial cogeneration systems: Optimal investment planning considering long-term trends," Applied Energy, Elsevier, vol. 324(C).
    3. Zheng, C.Y. & Wu, J.Y. & Zhai, X.Q. & Wang, R.Z., 2016. "Impacts of feed-in tariff policies on design and performance of CCHP system in different climate zones," Applied Energy, Elsevier, vol. 175(C), pages 168-179.
    4. Nehler, Therese, 2018. "Linking energy efficiency measures in industrial compressed air systems with non-energy benefits – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 72-87.
    5. Ren, Hongbo & Jiang, Zipei & Wu, Qiong & Li, Qifen & Lv, Hang, 2023. "Optimal planning of an economic and resilient district integrated energy system considering renewable energy uncertainty and demand response under natural disasters," Energy, Elsevier, vol. 277(C).
    6. Trianni, Andrea & Cagno, Enrico & De Donatis, Alessio, 2014. "A framework to characterize energy efficiency measures," Applied Energy, Elsevier, vol. 118(C), pages 207-220.
    7. Wang, Yang & Kuckelkorn, Jens & Li, Daoliang & Du, Jiangtao, 2018. "Evaluation on distributed renewable energy system integrated with a Passive House building using a new energy performance index," Energy, Elsevier, vol. 161(C), pages 81-89.
    8. Shi, Yining, 2022. "Financial liberalization and house prices: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 145(C).
    9. Schweitzer, Martin & Tonn, Bruce, 2003. "Non-energy benefits of the US Weatherization Assistance Program: a summary of their scope and magnitude," Applied Energy, Elsevier, vol. 76(4), pages 321-335, December.
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