IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v234y2024ics0960148124013090.html
   My bibliography  Save this article

Optimal investment of distribution energy resources via energy performance contracts: An evolutionary game approach

Author

Listed:
  • Zhang, Lizhong
  • Xiang, Yue

Abstract

Investment in distributed energy resources (DERs) is crucial for the expansion of distribution networks. However, traditional methods often lack comprehensive project management throughout their entire lifecycle and precise matching between distribution network operator (DNO) and energy consumer (EC) at the investment level. To address these issues, this paper proposes a novel investment model based on energy performance contracts (EPCs). Three EPC mechanisms are introduced: energy shared savings model (ESSM), energy guaranteed saving model (EGSM), and energy cost trust model (ECTM). Additionally, DERs investment strategies under EPC mechanisms are proposed to satisfy full-process management of project and precise matching between EC and DNO. The investment and operation problem is solved by an evolutionary game theory that ensures bounded rational agent to achieve satisfactory expected returns through repeated dynamic games. Results from the case study of an actual urban 37-bus system demonstrate that different EPC mechanisms are suitable for various scenarios depending on the EC's profit demand and project scale. The proposed model provides a comprehensive framework for DERs investment, considering the interests of both DNO and EC, and promotes the optimal expansion of distribution networks in a more practical and effective manner.

Suggested Citation

  • Zhang, Lizhong & Xiang, Yue, 2024. "Optimal investment of distribution energy resources via energy performance contracts: An evolutionary game approach," Renewable Energy, Elsevier, vol. 234(C).
    • Handle: RePEc:eee:renene:v:234:y:2024:i:c:s0960148124013090
    DOI: 10.1016/j.renene.2024.121241
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124013090
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.121241?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. Tsao, Yu-Chung & Vu, Thuy-Linh, 2023. "Distributed energy storage system planning in relation to renewable energy investment," Renewable Energy, Elsevier, vol. 218(C).
    2. Yao, Haotian & Xiang, Yue & Liu, Junyong, 2022. "Exploring multiple investment strategies for non-utility-owned DGs: A decentralized risked-based approach," Applied Energy, Elsevier, vol. 326(C).
    3. Zhang, Mingming & Nie, Jinchen & Su, Bin & Liu, Liyun, 2024. "An option game model applicable to multi-agent cooperation investment in energy storage projects," Energy Economics, Elsevier, vol. 131(C).
    4. Duan, Pengfei & Zhao, Bingxu & Zhang, Xinghui & Fen, Mengdan, 2023. "A day-ahead optimal operation strategy for integrated energy systems in multi-public buildings based on cooperative game," Energy, Elsevier, vol. 275(C).
    5. Wang, Yifei & Wang, Xiuli & Shao, Chengcheng & Gong, Naiwei, 2020. "Distributed energy trading for an integrated energy system and electric vehicle charging stations: A Nash bargaining game approach," Renewable Energy, Elsevier, vol. 155(C), pages 513-530.
    6. Xiang, Yue & Lu, Yu & Liu, Junyong, 2023. "Deep reinforcement learning based topology-aware voltage regulation of distribution networks with distributed energy storage," Applied Energy, Elsevier, vol. 332(C).
    7. Lu, Yu & Xiang, Yue & Huang, Yuan & Yu, Bin & Weng, Liguo & Liu, Junyong, 2023. "Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load," Energy, Elsevier, vol. 271(C).
    8. Nazari, AmirAli & Keypour, Reza & Amjady, Nima, 2021. "Joint investment of community energy storage systems in distribution networks using modified Nash bargaining theory," Applied Energy, Elsevier, vol. 301(C).
    9. Ehsan, Ali & Yang, Qiang, 2018. "Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques," Applied Energy, Elsevier, vol. 210(C), pages 44-59.
    10. Wang, Chengshan & Lv, Chaoxian & Li, Peng & Song, Guanyu & Li, Shuquan & Xu, Xiandong & Wu, Jianzhong, 2018. "Modeling and optimal operation of community integrated energy systems: A case study from China," Applied Energy, Elsevier, vol. 230(C), pages 1242-1254.
    11. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
    12. Xiang, Yue & Dai, Jiakun & Xue, Ping & Liu, Junyong, 2023. "Autonomous topology planning for distribution network expansion: A learning-based decoupled optimization method," Applied Energy, Elsevier, vol. 348(C).
    13. Zeng, Bo & Wen, Junqiang & Shi, Jinyue & Zhang, Jianhua & Zhang, Yuying, 2016. "A multi-level approach to active distribution system planning for efficient renewable energy harvesting in a deregulated environment," Energy, Elsevier, vol. 96(C), pages 614-624.
    14. Zhang, Kaoshe & Gao, Congchong & Zhang, Gang & Xie, Tuo & Li, Hua, 2024. "Electricity and heat sharing strategy of regional comprehensive energy multi-microgrid based on double-layer game," Energy, Elsevier, vol. 293(C).
    15. Dong, Lei & Zhang, Shiming & Zhang, Tao & Wang, Zibo & Qiao, Ji & Pu, Tianjiao, 2024. "DSO-prosumers dual-layer game optimization based on risk price guidance in a P2P energy market environment," Applied Energy, Elsevier, vol. 361(C).
    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. Yao, Haotian & Xiang, Yue & Liu, Junyong, 2022. "Exploring multiple investment strategies for non-utility-owned DGs: A decentralized risked-based approach," Applied Energy, Elsevier, vol. 326(C).
    2. Jianxun Luo & Wei Zhang & Hui Wang & Wenmiao Wei & Jinpeng He, 2023. "Research on Data-Driven Optimal Scheduling of Power System," Energies, MDPI, vol. 16(6), pages 1-15, March.
    3. Xie, Shiwei & Hu, Zhijian & Zhou, Daming & Li, Yan & Kong, Shunfei & Lin, Weiwei & Zheng, Yunfei, 2018. "Multi-objective active distribution networks expansion planning by scenario-based stochastic programming considering uncertain and random weight of network," Applied Energy, Elsevier, vol. 219(C), pages 207-225.
    4. Kandpal, Bakul & Backe, Stian & Crespo del Granado, Pedro, 2024. "Enhancing bargaining power for energy communities in renewable power purchase agreements using Gaussian learning and fixed price bargaining," Energy, Elsevier, vol. 309(C).
    5. Zhao, Bingxu & Cao, Xiaodong & Duan, Pengfei, 2024. "Cooperative operation of multiple low-carbon microgrids: An optimization study addressing gaming fraud and multiple uncertainties," Energy, Elsevier, vol. 297(C).
    6. Zhang, Kaoshe & Gao, Congchong & Zhang, Gang & Xie, Tuo & Li, Hua, 2024. "Electricity and heat sharing strategy of regional comprehensive energy multi-microgrid based on double-layer game," Energy, Elsevier, vol. 293(C).
    7. Xinxin Liu & Nan Li & Feng Liu & Hailin Mu & Longxi Li & Xiaoyu Liu, 2021. "Optimal Design on Fossil-to-Renewable Energy Transition of Regional Integrated Energy Systems under CO 2 Emission Abatement Control: A Case Study in Dalian, China," Energies, MDPI, vol. 14(10), pages 1-25, May.
    8. Guo, Tianyu & Guo, Qi & Huang, Libin & Guo, Haiping & Lu, Yuanhong & Tu, Liang, 2023. "Microgrid source-network-load-storage master-slave game optimization method considering the energy storage overcharge/overdischarge risk," Energy, Elsevier, vol. 282(C).
    9. Lu, Yu & Xiang, Yue & Huang, Yuan & Yu, Bin & Weng, Liguo & Liu, Junyong, 2023. "Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load," Energy, Elsevier, vol. 271(C).
    10. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    11. Yang, Jie & Yu, Fan & Ma, Kai & Yang, Bo & Yue, Zhiyuan, 2024. "Optimal scheduling of electric-hydrogen integrated charging station for new energy vehicles," Renewable Energy, Elsevier, vol. 224(C).
    12. Yang, Ting & Zhao, Liyuan & Li, Wei & Zomaya, Albert Y., 2021. "Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning," Energy, Elsevier, vol. 235(C).
    13. Mingshan Mo & Xinrui Xiong & Yunlong Wu & Zuyao Yu, 2023. "Deep-Reinforcement-Learning-Based Low-Carbon Economic Dispatch for Community-Integrated Energy System under Multiple Uncertainties," Energies, MDPI, vol. 16(22), pages 1-18, November.
    14. Zhu, Xingxu & Hou, Xiangchen & Li, Junhui & Yan, Gangui & Li, Cuiping & Wang, Dongbo, 2023. "Distributed online prediction optimization algorithm for distributed energy resources considering the multi-periods optimal operation," Applied Energy, Elsevier, vol. 348(C).
    15. Zhao, Yincheng & Zhang, Guozhou & Hu, Weihao & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2023. "Meta-learning based voltage control strategy for emergency faults of active distribution networks," Applied Energy, Elsevier, vol. 349(C).
    16. Mohseni, Soheil & Brent, Alan C. & Burmester, Daniel, 2020. "A comparison of metaheuristics for the optimal capacity planning of an isolated, battery-less, hydrogen-based micro-grid," Applied Energy, Elsevier, vol. 259(C).
    17. Wang, Zibo & Yu, Xiaodan & Mu, Yunfei & Jia, Hongjie, 2020. "A distributed Peer-to-Peer energy transaction method for diversified prosumers in Urban Community Microgrid System," Applied Energy, Elsevier, vol. 260(C).
    18. Chen, Yang & Park, Byungkwon & Kou, Xiao & Hu, Mengqi & Dong, Jin & Li, Fangxing & Amasyali, Kadir & Olama, Mohammed, 2020. "A comparison study on trading behavior and profit distribution in local energy transaction games," Applied Energy, Elsevier, vol. 280(C).
    19. Amro M Elshurafa & Abdel Rahman Muhsen, 2019. "The Upper Limit of Distributed Solar PV Capacity in Riyadh: A GIS-Assisted Study," Sustainability, MDPI, vol. 11(16), pages 1-20, August.
    20. Jerónimo Ramos-Teodoro & Adrián Giménez-Miralles & Francisco Rodríguez & Manuel Berenguel, 2020. "A Flexible Tool for Modeling and Optimal Dispatch of Resources in Agri-Energy Hubs," Sustainability, MDPI, vol. 12(21), pages 1-24, October.

    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:renene:v:234:y:2024:i:c:s0960148124013090. 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.journals.elsevier.com/renewable-energy .

    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.