IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i23p4420-d982182.html
   My bibliography  Save this article

A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions

Author

Listed:
  • Li-Peng Shao

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China)

  • Jia-Jia Chen

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China)

  • Lu-Wen Pan

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China)

  • Zi-Juan Yang

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, China)

Abstract

This paper addresses the deregulated electricity market arising in a distribution system with an electricity transaction. Under such an environment, the distribution system operator (DSO) with a distributed generator faces the challenge of electricity price uncertainty in a spot market. In this context, a credibility theory-based robust optimization model with multiple transactions is established to hedge the uncertain spot price of the DSO. Firstly, on the basis of credibility theory, the spot price is taken as a fuzzy variable and a risk aversion-based fuzzy opportunity constraint is proposed. Then, to exploit the resiliency of multiple transactions on hedging against uncertain spot price, the spot market, option contract and bilateral contract integrating power flow constraints are studied, because it is imperative for DSO to consider the operational constraints of the local network in the electricity market. Finally, the clear equivalence class is adopted to transform the risk aversion constraint into a deterministic robust optimization one. Under the premise of considering the expected cost of the DSO, the optimal electricity transaction strategy that maximizes resistance to uncertain spot price is pursued. The rationality and effectiveness of the model are verified with a modified 15-node network. The results show that the introduction of option contracts and bilateral contracts reduces the electricity transaction cost of DSO by USD 28.5. In addition, under the same risk aversion factor, the cost of the proposed model is reduced by USD 195.18 compared with robust optimization, which avoids the over-conservatism of traditional robust optimization.

Suggested Citation

  • Li-Peng Shao & Jia-Jia Chen & Lu-Wen Pan & Zi-Juan Yang, 2022. "A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions," Mathematics, MDPI, vol. 10(23), pages 1-20, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:23:p:4420-:d:982182
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/23/4420/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/23/4420/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nojavan, Sayyad & Najafi-Ghalelou, Afshin & Majidi, Majid & Zare, Kazem, 2018. "Optimal bidding and offering strategies of merchant compressed air energy storage in deregulated electricity market using robust optimization approach," Energy, Elsevier, vol. 142(C), pages 250-257.
    2. Peng, Xu & Tao, Xiaoma, 2018. "Cooperative game of electricity retailers in China's spot electricity market," Energy, Elsevier, vol. 145(C), pages 152-170.
    3. Fotouhi Ghazvini, Mohammad Ali & Soares, João & Horta, Nuno & Neves, Rui & Castro, Rui & Vale, Zita, 2015. "A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers," Applied Energy, Elsevier, vol. 151(C), pages 102-118.
    4. Moradi, Mohammad H. & Eskandari, Mohsen, 2014. "A hybrid method for simultaneous optimization of DG capacity and operational strategy in microgrids considering uncertainty in electricity price forecasting," Renewable Energy, Elsevier, vol. 68(C), pages 697-714.
    5. David Esteban Rodriguez & Alfredo Trespalacios & David Galeano, 2021. "Risk Transfer in an Electricity Market," Mathematics, MDPI, vol. 9(21), pages 1-12, October.
    6. Wozabal, David & Rameseder, Gunther, 2020. "Optimal bidding of a virtual power plant on the Spanish day-ahead and intraday market for electricity," European Journal of Operational Research, Elsevier, vol. 280(2), pages 639-655.
    7. Mei, Fei & Zhang, Jiatang & Lu, Jixiang & Lu, Jinjun & Jiang, Yuhan & Gu, Jiaqi & Yu, Kun & Gan, Lei, 2021. "Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations," Energy, Elsevier, vol. 219(C).
    8. Haokun Su & Xiangang Peng & Hanyu Liu & Huan Quan & Kaitong Wu & Zhiwen Chen, 2022. "Multi-Step-Ahead Electricity Price Forecasting Based on Temporal Graph Convolutional Network," Mathematics, MDPI, vol. 10(14), pages 1-16, July.
    9. Johansson, Petter & Vendel, Martin & Nuur, Cali, 2020. "Integrating distributed energy resources in electricity distribution systems: An explorative study of challenges facing DSOs in Sweden," Utilities Policy, Elsevier, vol. 67(C).
    10. Miguel Pinhão & Miguel Fonseca & Ricardo Covas, 2022. "Electricity Spot Price Forecast by Modelling Supply and Demand Curve," Mathematics, MDPI, vol. 10(12), pages 1-20, June.
    11. Chen, J.J. & Qi, B.X. & Rong, Z.K. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement," Energy, Elsevier, vol. 217(C).
    12. Villanueva-Rosario, Junior Alexis & Santos-García, Félix & Aybar-Mejía, Miguel Euclides & Mendoza-Araya, Patricio & Molina-García, Angel, 2022. "Coordinated ancillary services, market participation and communication of multi-microgrids: A review," Applied Energy, Elsevier, vol. 308(C).
    13. Charwand, Mansour & Gitizadeh, Mohsen & Siano, Pierluigi, 2017. "A new active portfolio risk management for an electricity retailer based on a drawdown risk preference," Energy, Elsevier, vol. 118(C), pages 387-398.
    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. Francisco Germán Badía & María D. Berrade, 2023. "Special Issue “Probability Theory and Stochastic Modeling with Applications”," Mathematics, MDPI, vol. 11(14), pages 1-3, July.

    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. Shiping Geng & Gengqi Wu & Caixia Tan & Dongxiao Niu & Xiaopeng Guo, 2021. "Multi-Objective Optimization of a Microgrid Considering the Uncertainty of Supply and Demand," Sustainability, MDPI, vol. 13(3), pages 1-21, January.
    2. Zhou, Kaile & Fei, Zhineng & Hu, Rong, 2023. "Hybrid robust decentralized optimization of emission-aware multi-energy microgrids considering multiple uncertainties," Energy, Elsevier, vol. 265(C).
    3. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).
    4. Benedikt Finnah, 2022. "Optimal bidding functions for renewable energies in sequential electricity markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 1-27, March.
    5. Silva, Ana R. & Pousinho, H.M.I. & Estanqueiro, Ana, 2022. "A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets," Energy, Elsevier, vol. 258(C).
    6. Reza Nadimi & Masahito Takahashi & Koji Tokimatsu & Mika Goto, 2024. "The Reliability and Profitability of Virtual Power Plant with Short-Term Power Market Trading and Non-Spinning Reserve Diesel Generator," Energies, MDPI, vol. 17(9), pages 1-19, April.
    7. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2020. "Strategic offering of a flexible producer in day-ahead and intraday power markets," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1136-1153.
    8. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    9. Gao, Yang & Ai, Qian & He, Xing & Fan, Songli, 2023. "Coordination for regional integrated energy system through target cascade optimization," Energy, Elsevier, vol. 276(C).
    10. 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.
    11. Gao, Evelyn & Sowlati, Taraneh & Akhtari, Shaghaygh, 2019. "Profit allocation in collaborative bioenergy and biofuel supply chains," Energy, Elsevier, vol. 188(C).
    12. Feng, Jie & Ran, Lun & Wang, Zhiyuan & Zhang, Mengling, 2024. "Optimal energy scheduling of virtual power plant integrating electric vehicles and energy storage systems under uncertainty," Energy, Elsevier, vol. 309(C).
    13. Ma, Cheng & Lei, Shunbo & Chen, Dong & Wang, Chong & Hatziargyriou, Nikos D. & Song, Ziyou, 2025. "Sequential service restoration with grid-interactive flexibility from building AC systems for resilient microgrids under endogenous and exogenous uncertainties," Applied Energy, Elsevier, vol. 377(PB).
    14. 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).
    15. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    16. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    17. Jun Dong & Yuanyuan Wang & Xihao Dou & Zhengpeng Chen & Yaoyu Zhang & Yao Liu, 2021. "Research on Decision Optimization Model of Microgrid Participating in Spot Market Transaction," Sustainability, MDPI, vol. 13(12), pages 1-26, June.
    18. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    19. Yanbin Li & Feng Zhang & Yun Li & Bingkang Li & Zhen Li, 2019. "Evaluating the Power Grid Investment Behavior in China: From the Perspective of Government Supervision," Energies, MDPI, vol. 12(21), pages 1-23, November.
    20. Fontecha, John E. & Nikolaev, Alexander & Walteros, Jose L. & Zhu, Zhenduo, 2022. "Scientists wanted? A literature review on incentive programs that promote pro-environmental consumer behavior: Energy, waste, and water," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).

    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:jmathe:v:10:y:2022:i:23:p:4420-:d:982182. 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.