IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v312y2024ics0360544224031761.html
   My bibliography  Save this article

A game-based power system planning approach considering real options and coordination of all types of participants

Author

Listed:
  • Yang, Nan
  • Xiong, Zhendong
  • Ding, Li
  • Liu, Yikui
  • Wu, Lei
  • Liu, Zhao
  • Shen, Xun
  • Zhu, Binxin
  • Li, Zhenhua
  • Huang, Yuehua

Abstract

With the ongoing advancement of global power marketization, the increasing diversity of stakeholders in the power market and their interactions have a significant impact on power system planning and operation. Traditional methods employ game theory to describe the interactions among market participants. However, these approaches fail to include all relevant participant types and overlook the long-term uncertainty value of planning schemes. Therefore, this paper proposes a game theory-based power system planning approach considering real options (RO) and coordination of all types of participants. First, the dynamic gaming interaction among supply-transmission-demand is studied, and the independent system operator is integrated into the game planning framework based on the overall perspective of power market operation. Moreover, the new power supply, grid planning, and operation of distributed generation (DG) are taken as decision variables based on the RO theory, and a game decision model of all participants in the power system planning considering the investment uncertainty is constructed. Finally, the iterative search algorithm is employed to solve the model, and the framework is validated based on the IEEE 30-bus system. The results indicate that through collaborative planning involving various market participants, Generation Companies and Transmission Companies expand their investments to maximize profits, while large power consumers reduce their investment in DG and instead increase their direct power purchases to lower costs. Moreover, these participants are inclined to pursue projects with higher asset value volatility, which further enhances their profit. By integrating RO theory with game theory, the proposed approach establishes a comprehensive planning framework that effectively addresses investment uncertainty. This integration enables market participants to make more optimal decisions, ultimately leading to an enhancement in the long-term economic performance of the power system.

Suggested Citation

  • Yang, Nan & Xiong, Zhendong & Ding, Li & Liu, Yikui & Wu, Lei & Liu, Zhao & Shen, Xun & Zhu, Binxin & Li, Zhenhua & Huang, Yuehua, 2024. "A game-based power system planning approach considering real options and coordination of all types of participants," Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:energy:v:312:y:2024:i:c:s0360544224031761
    DOI: 10.1016/j.energy.2024.133400
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224031761
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2024.133400?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. Zhou, Qun & Tesfatsion, Leigh & Liu, Chen-Ching & Chu, Ron F. & Sun, Wei, 2013. "A Nash Approach to Planning Merchant Transmission for Renewable Resource Integration," Staff General Research Papers Archive 36496, Iowa State University, Department of Economics.
    2. Jeon, Chanwoong & Lee, Jeongjin & Shin, Juneseuk, 2015. "Optimal subsidy estimation method using system dynamics and the real option model: Photovoltaic technology case," Applied Energy, Elsevier, vol. 142(C), pages 33-43.
    3. Josue Campos do Prado & Wei Qiao & Liyan Qu & Julio Romero Agüero, 2019. "The Next-Generation Retail Electricity Market in the Context of Distributed Energy Resources: Vision and Integrating Framework," Energies, MDPI, vol. 12(3), pages 1-24, February.
    4. Bruno, Sergio & Ahmed, Shabbir & Shapiro, Alexander & Street, Alexandre, 2016. "Risk neutral and risk averse approaches to multistage renewable investment planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 250(3), pages 979-989.
    5. Peng, Xu & Tao, Xiaoma, 2018. "Cooperative game of electricity retailers in China's spot electricity market," Energy, Elsevier, vol. 145(C), pages 152-170.
    6. Pringles, Rolando & Olsina, Fernando & Garcés, Francisco, 2015. "Real option valuation of power transmission investments by stochastic simulation," Energy Economics, Elsevier, vol. 47(C), pages 215-226.
    7. Chen, J.J. & Qi, B.X. & Peng, K. & Li, Y. & Zhao, Y.L., 2020. "Conditional value-at-credibility for random fuzzy wind power in demand response integrated multi-period economic emission dispatch," Applied Energy, Elsevier, vol. 261(C).
    8. Chen, Shaoqing & Chen, Bin, 2015. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis," Applied Energy, Elsevier, vol. 138(C), pages 99-107.
    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. Wenjie Pan & Jun Han & Chao Cai & Haofei Chen & Hong Liu & Zhengyang Xu, 2025. "Holistic Hosting Capacity Enhancement Through Sensitivity-Driven Flexibility Deployment and Uncertainty-Aware Optimization in Modern Distribution Networks," Energies, MDPI, vol. 18(3), pages 1-30, February.

    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. Assereto, Martina & Byrne, Julie, 2021. "No real option for solar in Ireland: A real option valuation of utility scale solar investment in Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    2. Pringles, Rolando & Olsina, Fernando & Penizzotto, Franco, 2020. "Valuation of defer and relocation options in photovoltaic generation investments by a stochastic simulation-based method," Renewable Energy, Elsevier, vol. 151(C), pages 846-864.
    3. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    4. Tiruwork B. Tibebu & Eric Hittinger & Qing Miao & Eric Williams, 2024. "Adoption Model Choice Affects the Optimal Subsidy for Residential Solar," Energies, MDPI, vol. 17(3), pages 1-19, February.
    5. Work, James & Hauer, Grant & Luckert, M.K. (Marty), 2018. "What ethanol prices would induce growers to switch from agriculture to poplar in Alberta? A multiple options approach," Journal of Forest Economics, Elsevier, vol. 33(C), pages 51-62.
    6. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    7. Gkousis, Spiros & Welkenhuysen, Kris & Harcouët-Menou, Virginie & Pogacnik, Justin & Laenen, Ben & Compernolle, Tine, 2024. "Integrated geo-techno-economic and real options analysis of the decision to invest in a medium enthalpy deep geothermal heating plant. A case study in Northern Belgium," Energy Economics, Elsevier, vol. 134(C).
    8. Jungmin An & Dong-Kwan Kim & Jinyeong Lee & Sung-Kwan Joo, 2021. "Least Squares Monte Carlo Simulation-Based Decision-Making Method for Photovoltaic Investment in Korea," Sustainability, MDPI, vol. 13(19), pages 1-14, September.
    9. Dai, Jiangyu & Wu, Shiqiang & Han, Guoyi & Weinberg, Josh & Xie, Xinghua & Wu, Xiufeng & Song, Xingqiang & Jia, Benyou & Xue, Wanyun & Yang, Qianqian, 2018. "Water-energy nexus: A review of methods and tools for macro-assessment," Applied Energy, Elsevier, vol. 210(C), pages 393-408.
    10. Wang, Moran & Guo, Xiaolong & Wang, Shouyang, 2022. "Financial hedging in two-stage sustainable commodity supply chains," European Journal of Operational Research, Elsevier, vol. 303(2), pages 803-818.
    11. Borrett, Stuart R. & Sheble, Laura & Moody, James & Anway, Evan C., 2018. "Bibliometric review of ecological network analysis: 2010–2016," Ecological Modelling, Elsevier, vol. 382(C), pages 63-82.
    12. Zhang, Xinhua & Yang, Hongming & Yu, Qian & Qiu, Jing & Zhang, Yongxi, 2018. "Analysis of carbon-abatement investment for thermal power market in carbon-dispatching mode and policy recommendations," Energy, Elsevier, vol. 149(C), pages 954-966.
    13. Chen, Shaoqing & Chen, Bin, 2017. "Coupling of carbon and energy flows in cities: A meta-analysis and nexus modelling," Applied Energy, Elsevier, vol. 194(C), pages 774-783.
    14. Gao, Evelyn & Sowlati, Taraneh & Akhtari, Shaghaygh, 2019. "Profit allocation in collaborative bioenergy and biofuel supply chains," Energy, Elsevier, vol. 188(C).
    15. Sun, Xudong & Li, Jiashuo & Qiao, Han & Zhang, Bo, 2017. "Energy implications of China's regional development: New insights from multi-regional input-output analysis," Applied Energy, Elsevier, vol. 196(C), pages 118-131.
    16. Zhang, M.M. & Wang, Qunwei & Zhou, Dequn & Ding, H., 2019. "Evaluating uncertain investment decisions in low-carbon transition toward renewable energy," Applied Energy, Elsevier, vol. 240(C), pages 1049-1060.
    17. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "Low-carbon economic dispatch and energy sharing method of multiple Integrated Energy Systems from the perspective of System of Systems," Energy, Elsevier, vol. 244(PA).
    18. Liu, Yang & Jiang, Zhigao & Guo, Bowei, 2022. "Assessing China’s provincial electricity spot market pilot operations: Lessons from Guangdong province," Energy Policy, Elsevier, vol. 164(C).
    19. Davi Valladão & Thuener Silva & Marcus Poggi, 2019. "Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns," Annals of Operations Research, Springer, vol. 282(1), pages 379-405, November.
    20. Lisardo Prieto González & Anna Fensel & Juan Miguel Gómez Berbís & Angela Popa & Antonio de Amescua Seco, 2021. "A Survey on Energy Efficiency in Smart Homes and Smart Grids," Energies, MDPI, vol. 14(21), pages 1-16, November.

    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:energy:v:312:y:2024:i:c:s0360544224031761. 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/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.