IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i14p3621-d384336.html
   My bibliography  Save this article

A Stackelberg Game-Based Approach for Transactive Energy Management in Smart Distribution Networks

Author

Listed:
  • Sara Haghifam

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51368, Iran)

  • Kazem Zare

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51368, Iran)

  • Mehdi Abapour

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51368, Iran)

  • Gregorio Muñoz-Delgado

    (E.T.S. de Ingeniería Industrial, University of Castilla–La Mancha, 13071 Ciudad Real, Spain)

  • Javier Contreras

    (E.T.S. de Ingeniería Industrial, University of Castilla–La Mancha, 13071 Ciudad Real, Spain)

Abstract

Recently, with the penetration of numerous Distributed Energy Resources (DER) in Smart Distribution Networks (SDN), Local Transactive Markets have emerged. Exchanging energy between all participants of local markets results in the satisfaction of producers and consumers. Based on these issues, this study provides a novel framework for the participation of SDN-independent entities in wholesale and local electricity markets simultaneously. In this regard, the considered system’s players, namely Distribution System Operator (DSO) and DER Aggregator (AG), take part within local as well as wholesale markets in two-day ahead and real-time stages. Moreover, to deal with the inherent conflict between the existing players’ interests, a Stackelberg game-based technique is proposed. In the raised competition, the leader, DSO, attempts to minimize its operating costs, while the follower, DER AG, tends to maximize its profit. Therefore, actors’ actions choices within both markets are made non-cooperatively. On the other hand, to handle the uncertain nature of stochastic parameters in the depicted problem, Monte Carlo Simulation (MCS), together with a fast backward/forward scenario reduction approach, is exploited. Ultimately, to evaluate the efficiency of the proposed scheme, two different case studies, with and without considering the competitive environment, are implemented on a modified IEEE-33 bus SDN.

Suggested Citation

  • Sara Haghifam & Kazem Zare & Mehdi Abapour & Gregorio Muñoz-Delgado & Javier Contreras, 2020. "A Stackelberg Game-Based Approach for Transactive Energy Management in Smart Distribution Networks," Energies, MDPI, vol. 13(14), pages 1-34, July.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3621-:d:384336
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/14/3621/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/14/3621/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M. Nazif Faqiry & Lawryn Edmonds & Haifeng Zhang & Amin Khodaei & Hongyu Wu, 2017. "Transactive-Market-Based Operation of Distributed Electrical Energy Storage with Grid Constraints," Energies, MDPI, vol. 10(11), pages 1-17, November.
    2. Akbari, Ebrahim & Hooshmand, Rahmat-Allah & Gholipour, Mehdi & Parastegari, Moein, 2019. "Stochastic programming-based optimal bidding of compressed air energy storage with wind and thermal generation units in energy and reserve markets," Energy, Elsevier, vol. 171(C), pages 535-546.
    3. Aliasghari, Parinaz & Zamani-Gargari, Milad & Mohammadi-Ivatloo, Behnam, 2018. "Look-ahead risk-constrained scheduling of wind power integrated system with compressed air energy storage (CAES) plant," Energy, Elsevier, vol. 160(C), pages 668-677.
    4. Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1, April.
    5. Dadashi, Mojtaba & Haghifam, Sara & Zare, Kazem & Haghifam, Mahmoud-Reza & Abapour, Mehdi, 2020. "Short-term scheduling of electricity retailers in the presence of Demand Response Aggregators: A two-stage stochastic Bi-Level programming approach," Energy, Elsevier, vol. 205(C).
    6. Wang, Jianxiao & Zhong, Haiwang & Wu, Chenye & Du, Ershun & Xia, Qing & Kang, Chongqing, 2019. "Incentivizing distributed energy resource aggregation in energy and capacity markets: An energy sharing scheme and mechanism design," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    7. Hatziargyriou, Nikos D. & Asimakopoulou, Georgia E., 2020. "DER integration through a monopoly DER aggregator," Energy Policy, Elsevier, vol. 137(C).
    8. Jian Wang & Qianggang Wang & Niancheng Zhou & Yuan Chi, 2017. "A Novel Electricity Transaction Mode of Microgrids Based on Blockchain and Continuous Double Auction," Energies, MDPI, vol. 10(12), pages 1-22, November.
    9. Cornélusse, Bertrand & Savelli, Iacopo & Paoletti, Simone & Giannitrapani, Antonio & Vicino, Antonio, 2019. "A community microgrid architecture with an internal local market," Applied Energy, Elsevier, vol. 242(C), pages 547-560.
    10. Cindy Paola Guzman & Nataly Bañol Arias & John Fredy Franco & Marcos J. Rider & Rubén Romero, 2020. "Enhanced Coordination Strategy for an Aggregator of Distributed Energy Resources Participating in the Day-Ahead Reserve Market," Energies, MDPI, vol. 13(8), pages 1-22, April.
    11. Fotouhi Ghazvini, Mohammad Ali & Faria, Pedro & Ramos, Sergio & Morais, Hugo & Vale, Zita, 2015. "Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market," Energy, Elsevier, vol. 82(C), pages 786-799.
    12. Yu Min Hwang & Issac Sim & Young Ghyu Sun & Heung-Jae Lee & Jin Young Kim, 2018. "Game-Theory Modeling for Social Welfare Maximization in Smart Grids," Energies, MDPI, vol. 11(9), pages 1-23, September.
    13. Bertrand Corn'elusse & Iacopo Savelli & Simone Paoletti & Antonio Giannitrapani & Antonio Vicino, 2018. "A Community Microgrid Architecture with an Internal Local Market," Papers 1810.09803, arXiv.org, revised Feb 2019.
    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. Domagoj Badanjak & Hrvoje Pandžić, 2021. "Distribution-Level Flexibility Markets—A Review of Trends, Research Projects, Key Stakeholders and Open Questions," Energies, MDPI, vol. 14(20), pages 1-26, October.
    2. Mario Tovar & Miguel Robles & Felipe Rashid, 2020. "PV Power Prediction, Using CNN-LSTM Hybrid Neural Network Model. Case of Study: Temixco-Morelos, México," Energies, MDPI, vol. 13(24), pages 1-15, December.
    3. Bogdan-Constantin Neagu & Ovidiu Ivanov & Gheorghe Grigoras & Mihai Gavrilas & Dumitru-Marcel Istrate, 2020. "New Market Model with Social and Commercial Tiers for Improved Prosumer Trading in Microgrids," Sustainability, MDPI, vol. 12(18), pages 1-43, September.
    4. Schmitt, Carlo & Schumann, Klemens & Kollenda, Katharina & Blank, Andreas & Rebenaque, Olivier & Dronne, Théo & Martin, Arnault & Vassilopoulos, Philippe & Roques, Fabien & Moser, Albert, 2022. "How will local energy markets influence the pan-European day-ahead market and transmission systems? A case study for local markets in France and Germany," Applied Energy, Elsevier, vol. 325(C).

    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. Alexandros-Georgios Chronis & Foivos Palaiogiannis & Iasonas Kouveliotis-Lysikatos & Panos Kotsampopoulos & Nikos Hatziargyriou, 2021. "Photovoltaics Enabling Sustainable Energy Communities: Technological Drivers and Emerging Markets," Energies, MDPI, vol. 14(7), pages 1-21, March.
    2. Savelli, Iacopo & Morstyn, Thomas, 2021. "Electricity prices and tariffs to keep everyone happy: A framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Omega, Elsevier, vol. 103(C).
    3. 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).
    4. Wenting Zhao & Jun Lv & Xilong Yao & Juanjuan Zhao & Zhixin Jin & Yan Qiang & Zheng Che & Chunwu Wei, 2019. "Consortium Blockchain-Based Microgrid Market Transaction Research," Energies, MDPI, vol. 12(20), pages 1-22, October.
    5. Bogdan-Constantin Neagu & Ovidiu Ivanov & Gheorghe Grigoras & Mihai Gavrilas & Dumitru-Marcel Istrate, 2020. "New Market Model with Social and Commercial Tiers for Improved Prosumer Trading in Microgrids," Sustainability, MDPI, vol. 12(18), pages 1-43, September.
    6. Tsaousoglou, Georgios & Giraldo, Juan S. & Paterakis, Nikolaos G., 2022. "Market Mechanisms for Local Electricity Markets: A review of models, solution concepts and algorithmic techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    7. Antoine Boche & Clément Foucher & Luiz Fernando Lavado Villa, 2022. "Understanding Microgrid Sustainability: A Systemic and Comprehensive Review," Energies, MDPI, vol. 15(8), pages 1-29, April.
    8. Bai, Jiayu & Wei, Wei & Chen, Laijun & Mei, Shengwei, 2020. "Modeling and dispatch of advanced adiabatic compressed air energy storage under wide operating range in distribution systems with renewable generation," Energy, Elsevier, vol. 206(C).
    9. Gayo-Abeleira, Miguel & Santos, Carlos & Javier Rodríguez Sánchez, Francisco & Martín, Pedro & Antonio Jiménez, José & Santiso, Enrique, 2022. "Aperiodic two-layer energy management system for community microgrids based on blockchain strategy," Applied Energy, Elsevier, vol. 324(C).
    10. Fioriti, Davide & Frangioni, Antonio & Poli, Davide, 2021. "Optimal sizing of energy communities with fair revenue sharing and exit clauses: Value, role and business model of aggregators and users," Applied Energy, Elsevier, vol. 299(C).
    11. Xiong, Linyun & Li, Penghan & Wang, Ziqiang & Wang, Jie, 2020. "Multi-agent based multi objective renewable energy management for diversified community power consumers," Applied Energy, Elsevier, vol. 259(C).
    12. Giovanni Gino Zanvettor & Marco Casini & Antonio Vicino, 2024. "Optimal Operation of Energy Storage Facilities in Incentive-Based Energy Communities," Energies, MDPI, vol. 17(11), pages 1-20, May.
    13. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.
    14. Àlex Alonso & Jordi de la Hoz & Helena Martín & Sergio Coronas & José Matas, 2021. "Individual vs. Community: Economic Assessment of Energy Management Systems under Different Regulatory Frameworks," Energies, MDPI, vol. 14(3), pages 1-27, January.
    15. Akbari, Ebrahim & Hooshmand, Rahmat-Allah & Gholipour, Mehdi & Parastegari, Moein, 2019. "Stochastic programming-based optimal bidding of compressed air energy storage with wind and thermal generation units in energy and reserve markets," Energy, Elsevier, vol. 171(C), pages 535-546.
    16. Fernández-Blanco, Ricardo & Morales, Juan Miguel & Pineda, Salvador, 2021. "Forecasting the price-response of a pool of buildings via homothetic inverse optimization," Applied Energy, Elsevier, vol. 290(C).
    17. Guido Cavraro & Tommaso Caldognetto & Ruggero Carli & Paolo Tenti, 2019. "A Master/Slave Approach to Power Flow and Overvoltage Control in Low-Voltage Microgrids," Energies, MDPI, vol. 12(14), pages 1-22, July.
    18. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    19. Ishizaki, Takayuki & Koike, Masakazu & Yamaguchi, Nobuyuki & Ueda, Yuzuru & Imura, Jun-ichi, 2020. "Day-ahead energy market as adjustable robust optimization: Spatio-temporal pricing of dispatchable generators, storage batteries, and uncertain renewable resources," Energy Economics, Elsevier, vol. 91(C).
    20. Denis Sidorov & Daniil Panasetsky & Nikita Tomin & Dmitriy Karamov & Aleksei Zhukov & Ildar Muftahov & Aliona Dreglea & Fang Liu & Yong Li, 2020. "Toward Zero-Emission Hybrid AC/DC Power Systems with Renewable Energy Sources and Storages: A Case Study from Lake Baikal Region," Energies, MDPI, vol. 13(5), pages 1-18, March.

    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:jeners:v:13:y:2020:i:14:p:3621-:d:384336. 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.