IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i11p1891-d119382.html
   My bibliography  Save this article

Transactive-Market-Based Operation of Distributed Electrical Energy Storage with Grid Constraints

Author

Listed:
  • M. Nazif Faqiry

    (Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA)

  • Lawryn Edmonds

    (Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA)

  • Haifeng Zhang

    (Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA)

  • Amin Khodaei

    (Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80210, USA)

  • Hongyu Wu

    (Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA)

Abstract

In a transactive energy market, distributed energy resources (DERs) such as dispatchable distributed generators (DGs), electrical energy storages (EESs), distribution-scale load aggregators (LAs), and renewable energy sources (RESs) have to earn their share of supply or demand through a bidding process. In such a market, the distribution system operator (DSO) may optimally schedule these resources, first in a forward market, i.e., day-ahead, and in a real-time market later on, while maintaining a reliable and economic distribution grid. In this paper, an efficient day-ahead scheduling of these resources, in the presence of interaction with wholesale market at the locational marginal price (LMP), is studied. Due to inclusion of EES units with integer constraints, a detailed mixed integer linear programming (MILP) formulation that incorporates simplified DistFlow equations to account for grid constraints is proposed. Convex quadratic line and transformer apparent power flow constraints have been linearized using an outer approximation. The proposed model schedules DERs based on distribution locational marginal price (DLMP), which is obtained as the Lagrange multiplier of the real power balance constraint at each distribution bus while maintaining physical grid constraints such as line limits, transformer limits, and bus voltage magnitudes. Case studies are performed on a modified IEEE 13-bus system with high DER penetration. Simulation results show the validity and efficiency of the proposed model.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:11:p:1891-:d:119382
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/11/1891/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/11/1891/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kristoffersen, Trine Krogh & Capion, Karsten & Meibom, Peter, 2011. "Optimal charging of electric drive vehicles in a market environment," Applied Energy, Elsevier, vol. 88(5), pages 1940-1948, May.
    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. Wentao Yang & Fushuan Wen & Ke Wang & Yuchun Huang & Md. Abdus Salam, 2018. "Modeling of a District Heating System and Optimal Heat-Power Flow," Energies, MDPI, vol. 11(4), pages 1-19, April.
    2. Ghaemi, Sina & Li, Xinyu & Mulder, Machiel, 2023. "Economic feasibility of green hydrogen in providing flexibility to medium-voltage distribution grids in the presence of local-heat systems," Applied Energy, Elsevier, vol. 331(C).
    3. Schwidtal, J.M. & Piccini, P. & Troncia, M. & Chitchyan, R. & Montakhabi, M. & Francis, C. & Gorbatcheva, A. & Capper, T. & Mustafa, M.A. & Andoni, M. & Robu, V. & Bahloul, M. & Scott, I.J. & Mbavarir, 2023. "Emerging business models in local energy markets: A systematic review of peer-to-peer, community self-consumption, and transactive energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    4. 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.
    5. Hyung Tae Kim & Young Gyu Jin & Yong Tae Yoon, 2019. "An Economic Analysis of Load Leveling with Battery Energy Storage Systems (BESS) in an Electricity Market Environment: The Korean Case," Energies, MDPI, vol. 12(9), pages 1-16, April.
    6. Capper, Timothy & Gorbatcheva, Anna & Mustafa, Mustafa A. & Bahloul, Mohamed & Schwidtal, Jan Marc & Chitchyan, Ruzanna & Andoni, Merlinda & Robu, Valentin & Montakhabi, Mehdi & Scott, Ian J. & Franci, 2022. "Peer-to-peer, community self-consumption, and transactive energy: A systematic literature review of local energy market models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    7. Stefano Bracco, 2020. "A Study for the Optimal Exploitation of Solar, Wind and Hydro Resources and Electrical Storage Systems in the Bormida Valley in the North of Italy," Energies, MDPI, vol. 13(20), pages 1-26, October.
    8. Edmonds, Lawryn & Derby, Melanie & Hill, Mary & Wu, Hongyu, 2021. "Coordinated operation of water and electricity distribution networks with variable renewable energy and distribution locational marginal pricing," Renewable Energy, Elsevier, vol. 177(C), pages 1438-1450.
    9. Faqiry, M. Nazif & Edmonds, Lawryn & Wu, Hongyu & Pahwa, Anil, 2020. "Distribution locational marginal price-based transactive day-ahead market with variable renewable generation," Applied Energy, Elsevier, vol. 259(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. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
    2. Biegel, Benjamin & Hansen, Lars Henrik & Stoustrup, Jakob & Andersen, Palle & Harbo, Silas, 2014. "Value of flexible consumption in the electricity markets," Energy, Elsevier, vol. 66(C), pages 354-362.
    3. Shi You & Junjie Hu & Charalampos Ziras, 2016. "An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †," Energies, MDPI, vol. 9(11), pages 1-18, November.
    4. Kuang, Yanqing & Chen, Yang & Hu, Mengqi & Yang, Dong, 2017. "Influence analysis of driver behavior and building category on economic performance of electric vehicle to grid and building integration," Applied Energy, Elsevier, vol. 207(C), pages 427-437.
    5. Brouwer, Anne Sjoerd & Kuramochi, Takeshi & van den Broek, Machteld & Faaij, André, 2013. "Fulfilling the electricity demand of electric vehicles in the long term future: An evaluation of centralized and decentralized power supply systems," Applied Energy, Elsevier, vol. 107(C), pages 33-51.
    6. Frew, Bethany A. & Becker, Sarah & Dvorak, Michael J. & Andresen, Gorm B. & Jacobson, Mark Z., 2016. "Flexibility mechanisms and pathways to a highly renewable US electricity future," Energy, Elsevier, vol. 101(C), pages 65-78.
    7. Jip Kim & Seung Wan Kim & Young Gyu Jin & Jong-Keun Park & Yong Tae Yoon, 2016. "Optimal Coordinated Management of a Plug-In Electric Vehicle Charging Station under a Flexible Penalty Contract for Voltage Security," Energies, MDPI, vol. 9(7), pages 1-15, July.
    8. Shimi Sudha Letha & Math H. J. Bollen & Tatiano Busatto & Angela Espin Delgado & Enock Mulenga & Hamed Bakhtiari & Jil Sutaria & Kazi Main Uddin Ahmed & Naser Nakhodchi & Selçuk Sakar & Vineetha Ravin, 2023. "Power Quality Issues of Electro-Mobility on Distribution Network—An Overview," Energies, MDPI, vol. 16(13), pages 1-21, June.
    9. Huber, Julian & Dann, David & Weinhardt, Christof, 2020. "Probabilistic forecasts of time and energy flexibility in battery electric vehicle charging," Applied Energy, Elsevier, vol. 262(C).
    10. Schill, Wolf-Peter & Gerbaulet, Clemens, 2015. "Power System Impacts of Electric Vehicles in Germany: Charging with Coal or Renewables," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 156, pages 185-196.
    11. Li, Jinghua & Fang, Jiakun & Zeng, Qing & Chen, Zhe, 2016. "Optimal operation of the integrated electrical and heating systems to accommodate the intermittent renewable sources," Applied Energy, Elsevier, vol. 167(C), pages 244-254.
    12. Schücking, Maximilian & Jochem, Patrick & Fichtner, Wolf & Wollersheim, Olaf & Stella, Kevin, 2017. "Charging strategies for economic operations of electric vehicles in commercial applications," MPRA Paper 91599, University Library of Munich, Germany.
    13. Tong-Bou Chang & Jer-Jia Sheu & Jhong-Wei Huang, 2020. "High-Efficiency HVAC System with Defog/Dehumidification Function for Electric Vehicles," Energies, MDPI, vol. 14(1), pages 1-12, December.
    14. Shepero, Mahmoud & Munkhammar, Joakim & Widén, Joakim & Bishop, Justin D.K. & Boström, Tobias, 2018. "Modeling of photovoltaic power generation and electric vehicles charging on city-scale: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 61-71.
    15. Vachirasricirikul, Sitthidet & Ngamroo, Issarachai, 2011. "Robust controller design of heat pump and plug-in hybrid electric vehicle for frequency control in a smart microgrid based on specified-structure mixed H2/H∞ control technique," Applied Energy, Elsevier, vol. 88(11), pages 3860-3868.
    16. Zheng, Menglian & Wang, Xinhao & Meinrenken, Christoph J. & Ding, Yi, 2018. "Economic and environmental benefits of coordinating dispatch among distributed electricity storage," Applied Energy, Elsevier, vol. 210(C), pages 842-855.
    17. Verzijlbergh, Remco & Brancucci Martínez-Anido, Carlo & Lukszo, Zofia & de Vries, Laurens, 2014. "Does controlled electric vehicle charging substitute cross-border transmission capacity?," Applied Energy, Elsevier, vol. 120(C), pages 169-180.
    18. Felix Guthoff & Nikolai Klempp & Kai Hufendiek, 2021. "Quantification of the Flexibility Potential through Smart Charging of Battery Electric Vehicles and the Effects on the Future Electricity Supply System in Germany," Energies, MDPI, vol. 14(9), pages 1-20, April.
    19. Zhaoxi Liu & Qiuwei Wu & Arne Hejde Nielsen & Yun Wang, 2014. "Day-Ahead Energy Planning with 100% Electric Vehicle Penetration in the Nordic Region by 2050," Energies, MDPI, vol. 7(3), pages 1-17, March.
    20. Welzel, Fynn & Klinck, Carl-Friedrich & Pohlmann, Yannick & Bednarczyk, Mats, 2021. "Grid and user-optimized planning of charging processes of an electric vehicle fleet using a quantitative optimization model," Applied Energy, Elsevier, vol. 290(C).

    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:10:y:2017:i:11:p:1891-:d:119382. 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.