IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i2p820-d1321202.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/2/820/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/2/820/
    Download Restriction: no
    ---><---

    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. 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.
    3. Shi, Yining, 2022. "Financial liberalization and house prices: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 145(C).
    4. 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).
    5. 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.
    6. 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.
    7. 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).
    8. Trianni, Andrea & Cagno, Enrico & De Donatis, Alessio, 2014. "A framework to characterize energy efficiency measures," Applied Energy, Elsevier, vol. 118(C), pages 207-220.
    9. 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.
    Full references (including those not matched with items on IDEAS)

    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. Accordini, D. & Cagno, E. & Trianni, A., 2021. "Identification and characterization of decision-making factors over industrial energy efficiency measures in electric motor systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    2. Fábio de Oliveira Neves & Henrique Ewbank & José Arnaldo Frutuoso Roveda & Andrea Trianni & Fernando Pinhabel Marafão & Sandra Regina Monteiro Masalskiene Roveda, 2022. "Economic and Production-Related Implications for Industrial Energy Efficiency: A Logistic Regression Analysis on Cross-Cutting Technologies," Energies, MDPI, vol. 15(4), pages 1-19, February.
    3. Monjurul Hasan, A S M & Trianni, Andrea & Shukla, Nagesh & Katic, Mile, 2022. "A novel characterization based framework to incorporate industrial energy management services," Applied Energy, Elsevier, vol. 313(C).
    4. Paramonova, Svetlana & Nehler, Therese & Thollander, Patrik, 2021. "Technological change or process innovation – An empirical study of implemented energy efficiency measures from a Swedish industrial voluntary agreements program," Energy Policy, Elsevier, vol. 156(C).
    5. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.
    6. Andrea Trianni & Davide Accordini & Enrico Cagno, 2020. "Identification and Categorization of Factors Affecting the Adoption of Energy Efficiency Measures within Compressed Air Systems," Energies, MDPI, vol. 13(19), pages 1-51, October.
    7. Therese Nehler, 2018. "A Systematic Literature Review of Methods for Improved Utilisation of the Non-Energy Benefits of Industrial Energy Efficiency," Energies, MDPI, vol. 11(12), pages 1-27, November.
    8. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    9. Wang, Zhenfeng & Xu, Guangyin & Wang, Heng & Ren, Jingzheng, 2019. "Distributed energy system for sustainability transition: A comprehensive assessment under uncertainties based on interval multi-criteria decision making method by coupling interval DEMATEL and interva," Energy, Elsevier, vol. 169(C), pages 750-761.
    10. Cagno, Enrico & Accordini, Davide & Trianni, Andrea & Katic, Mile & Ferrari, Nicolò & Gambaro, Federico, 2022. "Understanding the impacts of energy efficiency measures on a Company’s operational performance: A new framework," Applied Energy, Elsevier, vol. 328(C).
    11. Kalantzis, Fotios & Niczyporuk, Hanna, 2021. "Can European businesses achieve productivity gains from investments in energy efficiency?," EIB Working Papers 2021/07, European Investment Bank (EIB).
    12. Olsthoorn, Mark & Schleich, Joachim & Hirzel, Simon, 2017. "Adoption of Energy Efficiency Measures for Non-residential Buildings: Technological and Organizational Heterogeneity in the Trade, Commerce and Services Sector," Ecological Economics, Elsevier, vol. 136(C), pages 240-254.
    13. Yanfeng Liu & Yaxing Wang & Xi Luo, 2020. "Design and Operation Optimization of Distributed Solar Energy System Based on Dynamic Operation Strategy," Energies, MDPI, vol. 14(1), pages 1-26, December.
    14. Wang, Xuan & Shu, Gequn & Tian, Hua & Wang, Rui & Cai, Jinwen, 2020. "Operation performance comparison of CCHP systems with cascade waste heat recovery systems by simulation and operation optimisation," Energy, Elsevier, vol. 206(C).
    15. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    16. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    17. Huang, Jinbo & Li, Zhigang & Wu, Q.H., 2017. "Coordinated dispatch of electric power and district heating networks: A decentralized solution using optimality condition decomposition," Applied Energy, Elsevier, vol. 206(C), pages 1508-1522.
    18. Chen, Yizhong & He, Li & Li, Jing, 2017. "Stochastic dominant-subordinate-interactive scheduling optimization for interconnected microgrids with considering wind-photovoltaic-based distributed generations under uncertainty," Energy, Elsevier, vol. 130(C), pages 581-598.
    19. Afzali, Sayyed Faridoddin & Mahalec, Vladimir, 2017. "Optimal design, operation and analytical criteria for determining optimal operating modes of a CCHP with fired HRSG, boiler, electric chiller and absorption chiller," Energy, Elsevier, vol. 139(C), pages 1052-1065.
    20. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.

    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:gam:jsusta:v:16:y:2024:i:2:p:820-:d:1321202. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.