IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i4p1645-d1060289.html
   My bibliography  Save this article

System and Market-Wide Impact Analysis of Coordinated Demand Response and Battery Storage Operation by a Load-Serving Entity

Author

Listed:
  • Pakeeza Bano

    (US Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan)

  • Kashif Imran

    (US Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan)

  • Abdul Kashif Janjua

    (Department of Electrical Technology, National Skills University, Islamabad 44000, Pakistan)

  • Abdullah Abusorrah

    (Department of Electrical and Computer Engineering, Faculty of Engineering, K. A. CARE Energy Research and Innovation Center, Jeddah 21589, Saudi Arabia
    Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Kinza Fida

    (US Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan)

  • Hesham Alhumade

    (Department of Chemical and Materials Engineering, Faculty of Engineering, K. A. CARE Energy Research and Innovation Center, Jeddah 21589, Saudi Arabia)

Abstract

Because of electricity markets, environmental concerns, transmission constraints, and variable renewable energy sources (VRES), coordinated operation of demand response (DR) and battery energy storage systems (BESS) has become critical. In turn, the optimal coordinated operation of DR and BESS by an entity can affect overall electricity market outcomes and transmission network conditions. The coordinated operation is desirable for the profit-seeking entity, but it may adversely affect the cost and revenues of other market participants or cause system congestion. Though few coordinated operation models already exist, our aim in this research is to provide a novel multi-objective optimization-based methodology for the coordinated operation of DR and BESS to boost market profit. Moreover, another goal is to simultaneously study the combined effects of such coordinated models on transmission networks and electricity markets for the first time. This paper has proposed a new method for coordinated DR and BESS utilization by a load-serving entity (LSE) to increase its profit. Moreover, it has employed agent-based modeling of the electricity systems (AMES) for testing our coordinated DR and BESS method under day-ahead market and transmission system conditions. Simulation results of case studies indicate that the operating costs of all LSEs decreased, and there was as much as 98,260 $/day in cost savings for BESS deploying LSE1. Although revenues of cheaper generation companies (GenCos) decreased, those of expensive GenCos increased or showed mixed trends. For example, GenCo 3 exhibits an 8765 $/day decrease in revenue for 25% BESS capacity, whereas a 6328 $/day increase in revenue for 37.5% BESS capacity. The variance of LMPs, widely used as a risk index, greatly decreased for the LSE utilizing the coordinated methodology, somewhat decreased for other LSEs but increased for cheaper GenCos with no LSE at the local node. Since BESS deployment decisions of an LSE can have system-wide or market-wide consequences, simulation analysis before deployment can help reduce market distortions or system congestions.

Suggested Citation

  • Pakeeza Bano & Kashif Imran & Abdul Kashif Janjua & Abdullah Abusorrah & Kinza Fida & Hesham Alhumade, 2023. "System and Market-Wide Impact Analysis of Coordinated Demand Response and Battery Storage Operation by a Load-Serving Entity," Energies, MDPI, vol. 16(4), pages 1-22, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1645-:d:1060289
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/4/1645/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/4/1645/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Clastres, Cédric & Khalfallah, Haikel, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Energy Economics, Elsevier, vol. 98(C).
    2. Zeyue Sun & Mohsen Eskandari & Chaoran Zheng & Ming Li, 2022. "Handling Computation Hardness and Time Complexity Issue of Battery Energy Storage Scheduling in Microgrids by Deep Reinforcement Learning," Energies, MDPI, vol. 16(1), pages 1-20, December.
    3. Poullikkas, Andreas, 2013. "A comparative overview of large-scale battery systems for electricity storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 778-788.
    4. 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.
    5. Lorenzi, Guido & Silva, Carlos Augusto Santos, 2016. "Comparing demand response and battery storage to optimize self-consumption in PV systems," Applied Energy, Elsevier, vol. 180(C), pages 524-535.
    6. Zipeng Liang & Haoyong Chen & Xiaojuan Wang & Idris Ibn Idris & Bifei Tan & Cong Zhang, 2018. "An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty," Energies, MDPI, vol. 11(8), pages 1-22, August.
    7. Sun, Lingling & Qiu, Jing & Han, Xiao & Yin, Xia & Dong, Zhaoyang, 2020. "Per-use-share rental strategy of distributed BESS in joint energy and frequency control ancillary services markets," Applied Energy, Elsevier, vol. 277(C).
    8. Draheim, Patrick & Schlachter, Uli & Wigger, Henning & Worschech, Alena & Brand, Urte & Diekmann, Theys & Schuldt, Frank & Hanke, Benedikt & von Maydell, Karsten & Vogt, Thomas, 2020. "Business case analysis of hybrid systems consisting of battery storage and power-to-heat on the German energy market," Utilities Policy, Elsevier, vol. 67(C).
    9. Zheng, Menglian & Meinrenken, Christoph J. & Lackner, Klaus S., 2014. "Agent-based model for electricity consumption and storage to evaluate economic viability of tariff arbitrage for residential sector demand response," Applied Energy, Elsevier, vol. 126(C), pages 297-306.
    10. Cédric Clastres & Haikel Khalfallah, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Post-Print hal-03193212, HAL.
    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. Parra, David & Swierczynski, Maciej & Stroe, Daniel I. & Norman, Stuart.A. & Abdon, Andreas & Worlitschek, Jörg & O’Doherty, Travis & Rodrigues, Lucelia & Gillott, Mark & Zhang, Xiaojin & Bauer, Chris, 2017. "An interdisciplinary review of energy storage for communities: Challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 730-749.
    2. Specht, Jan Martin & Madlener, Reinhard, 2023. "Quantifying value pools for distributed flexible energy assets," Energy, Elsevier, vol. 263(PB).
    3. Haikel Khalfallah & Bibata Sagnon, 2023. "Coordination séquentielle des investissements dans la production d'électricité et dans le réseau électrique : le rôle des incitations renouvelables," Working Papers 2023-04, Grenoble Applied Economics Laboratory (GAEL).
    4. Mohammad Hossein Nejati Amiri & Mehdi Mehdinejad & Amin Mohammadpour Shotorbani & Heidarali Shayanfar, 2023. "Heuristic Retailer’s Day-Ahead Pricing Based on Online-Learning of Prosumer’s Optimal Energy Management Model," Energies, MDPI, vol. 16(3), pages 1-21, January.
    5. Jaszczur, Marek & Hassan, Qusay & Abdulateef, Ammar M. & Abdulateef, Jasim, 2021. "Assessing the temporal load resolution effect on the photovoltaic energy flows and self-consumption," Renewable Energy, Elsevier, vol. 169(C), pages 1077-1090.
    6. Dong, Jun & Jiang, Yuzheng & Liu, Dongran & Dou, Xihao & Liu, Yao & Peng, Shicheng, 2022. "Promoting dynamic pricing implementation considering policy incentives and electricity retailers’ behaviors: An evolutionary game model based on prospect theory," Energy Policy, Elsevier, vol. 167(C).
    7. Jaszczur, Marek & Hassan, Qusay, 2020. "An optimisation and sizing of photovoltaic system with supercapacitor for improving self-consumption," Applied Energy, Elsevier, vol. 279(C).
    8. Francesco Lo Franco & Mattia Ricco & Riccardo Mandrioli & Gabriele Grandi, 2020. "Electric Vehicle Aggregate Power Flow Prediction and Smart Charging System for Distributed Renewable Energy Self-Consumption Optimization," Energies, MDPI, vol. 13(19), pages 1-25, September.
    9. Faezeh Akhavizadegan & Lizhi Wang & James McCalley, 2020. "Scenario Selection for Iterative Stochastic Transmission Expansion Planning," Energies, MDPI, vol. 13(5), pages 1-18, March.
    10. Yuhong Wang & Lei Chen & Hong Zhou & Xu Zhou & Zongsheng Zheng & Qi Zeng & Li Jiang & Liang Lu, 2021. "Flexible Transmission Network Expansion Planning Based on DQN Algorithm," Energies, MDPI, vol. 14(7), pages 1-21, April.
    11. Yin, Rumeng & He, Jiang, 2023. "Design of a photovoltaic electric bike battery-sharing system in public transit stations," Applied Energy, Elsevier, vol. 332(C).
    12. Zhao, Bo & Xue, Meidong & Zhang, Xuesong & Wang, Caisheng & Zhao, Junhui, 2015. "An MAS based energy management system for a stand-alone microgrid at high altitude," Applied Energy, Elsevier, vol. 143(C), pages 251-261.
    13. Hamed Moazami Goodarzi & Mohammad Hosein Kazemi, 2017. "A Novel Optimal Control Method for Islanded Microgrids Based on Droop Control Using the ICA-GA Algorithm," Energies, MDPI, vol. 10(4), pages 1-17, April.
    14. Ghadi, Mojtaba Jabbari & Azizivahed, Ali & Mishra, Dillip Kumar & Li, Li & Zhang, Jiangfeng & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Application of small-scale compressed air energy storage in the daily operation of an active distribution system," Energy, Elsevier, vol. 231(C).
    15. Katsanevakis, Markos & Stewart, Rodney A. & Lu, Junwei, 2017. "Aggregated applications and benefits of energy storage systems with application-specific control methods: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 719-741.
    16. Li Li & Yalin Lei & Dongyang Pan, 2015. "Economic and environmental evaluation of coal production in China and policy implications," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 1125-1141, June.
    17. Drysdale, Brian & Wu, Jianzhong & Jenkins, Nick, 2015. "Flexible demand in the GB domestic electricity sector in 2030," Applied Energy, Elsevier, vol. 139(C), pages 281-290.
    18. Pavlos Nikolaidis & Andreas Poullikkas, 2022. "A Thorough Emission-Cost Analysis of the Gradual Replacement of Carbon-Rich Fuels with Carbon-Free Energy Carriers in Modern Power Plants: The Case of Cyprus," Sustainability, MDPI, vol. 14(17), pages 1-18, August.
    19. Collath, Nils & Cornejo, Martin & Engwerth, Veronika & Hesse, Holger & Jossen, Andreas, 2023. "Increasing the lifetime profitability of battery energy storage systems through aging aware operation," Applied Energy, Elsevier, vol. 348(C).
    20. Sun, Xiaoqin & Lin, Yian & Zhu, Ziyang & Li, Jie, 2022. "Optimized design of a distributed photovoltaic system in a building with phase change materials," Applied Energy, Elsevier, vol. 306(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:jeners:v:16:y:2023:i:4:p:1645-:d:1060289. 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.