IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i12p9433-d1169186.html
   My bibliography  Save this article

Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control

Author

Listed:
  • Evan S. Jones

    (SPARK Laboratory, ECE Department, University of Kentucky, Lexington, KY 40506, USA)

  • Rosemary E. Alden

    (SPARK Laboratory, ECE Department, University of Kentucky, Lexington, KY 40506, USA)

  • Huangjie Gong

    (ABB USRC, 1021 Main Campus Dr, Raleigh, NC 27606, USA)

  • Dan M. Ionel

    (SPARK Laboratory, ECE Department, University of Kentucky, Lexington, KY 40506, USA)

Abstract

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.

Suggested Citation

  • Evan S. Jones & Rosemary E. Alden & Huangjie Gong & Dan M. Ionel, 2023. "Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9433-:d:1169186
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/12/9433/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/12/9433/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Naval, Natalia & Yusta, Jose M., 2021. "Virtual power plant models and electricity markets - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    2. Huangjie Gong & Rosemary E. Alden & Aron Patrick & Dan M. Ionel, 2022. "Forecast of Community Total Electric Load and HVAC Component Disaggregation through a New LSTM-Based Method," Energies, MDPI, vol. 15(9), pages 1-17, April.
    3. Huangjie Gong & Dan M. Ionel, 2021. "Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage," Energies, MDPI, vol. 14(18), pages 1-16, September.
    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. Jin-Li Hu, 2022. "Energy Resilience in Presence of Natural and Social Uncertainties," Energies, MDPI, vol. 15(18), pages 1-3, September.
    2. 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.
    3. Kaiss, Mateus & Wan, Yihao & Gebbran, Daniel & Vila, Clodomiro Unsihuay & Dragičević, Tomislav, 2025. "Review on Virtual Power Plants/Virtual Aggregators: Concepts, applications, prospects and operation strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    4. Gustavo Adolfo Gómez-Ramírez & Carlos Meza & Gonzalo Mora-Jiménez & José Rodrigo Rojas Morales & Luis García-Santander, 2023. "The Central American Power System: Achievements, Challenges, and Opportunities for a Green Transition," Energies, MDPI, vol. 16(11), pages 1-20, May.
    5. Zheng, Zixuan & Li, Jie & Liu, Xiaoming & Huang, Chunjun & Hu, Wenxi & Xiao, Xianyong & Zhang, Shu & Zhou, Yongjun & Yue, Song & Zong, Yi, 2025. "A De-aggregation strategy based optimal co-scheduling of heterogeneous flexible resources in virtual power plant," Applied Energy, Elsevier, vol. 383(C).
    6. Haji Bashi, Mazaher & De Tommasi, Luciano & Le Cam, Andreea & Relaño, Lorena Sánchez & Lyons, Padraig & Mundó, Joana & Pandelieva-Dimova, Ivanka & Schapp, Henrik & Loth-Babut, Karolina & Egger, Christ, 2023. "A review and mapping exercise of energy community regulatory challenges in European member states based on a survey of collective energy actors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
    7. Jiang, Yuzheng & Dong, Jun & Huang, Hexiang, 2024. "Optimal bidding strategy for the price-maker virtual power plant in the day-ahead market based on multi-agent twin delayed deep deterministic policy gradient algorithm," Energy, Elsevier, vol. 306(C).
    8. Forero-Quintero, Jose-Fernando & Villafáfila-Robles, Roberto & Barja-Martinez, Sara & Munné-Collado, Ingrid & Olivella-Rosell, Pol & Montesinos-Miracle, Daniel, 2022. "Profitability analysis on demand-side flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    9. Martin Bichler & Hans Ulrich Buhl & Johannes Knörr & Felipe Maldonado & Paul Schott & Stefan Waldherr & Martin Weibelzahl, 2022. "Electricity Markets in a Time of Change: A Call to Arms for Business Research," Schmalenbach Journal of Business Research, Springer, vol. 74(1), pages 77-102, March.
    10. Weigang Jin & Peihua Wang & Jiaxin Yuan, 2024. "Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era," Energies, MDPI, vol. 17(22), pages 1-24, November.
    11. Yan, Xingyu & Gao, Ciwei & Francois, Bruno, 2025. "Multi-objective optimization of a virtual power plant with mobile energy storage for a multi-stakeholders energy community," Applied Energy, Elsevier, vol. 386(C).
    12. Mostafa Darvishi & Mehrdad Tahmasebi & Ehsan Shokouhmand & Jagadeesh Pasupuleti & Pitshou Bokoro & Jwan Satei Raafat, 2023. "Optimal Operation of Sustainable Virtual Power Plant Considering the Amount of Emission in the Presence of Renewable Energy Sources and Demand Response," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
    13. Godwin C. Okwuibe & Amin Shokri Gazafroudi & Sarah Hambridge & Christopher Dietrich & Ana Trbovich & Miadreza Shafie-khah & Peter Tzscheutschler & Thomas Hamacher, 2022. "Evaluation of Hierarchical, Multi-Agent, Community-Based, Local Energy Markets Based on Key Performance Indicators," Energies, MDPI, vol. 15(10), pages 1-23, May.
    14. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    15. Chia-Sheng Tu & Ming-Tang Tsai, 2025. "The Optimal Energy Management of Virtual Power Plants by Considering Demand Response and Electric Vehicles," Energies, MDPI, vol. 18(17), pages 1-18, August.
    16. Catra Indra Cahyadi & Suwarno Suwarno & Aminah Asmara Dewi & Musri Kona & Muhammad Arif & Muhammad Caesar Akbar, 2023. "Solar Prediction Strategy for Managing Virtual Power Stations," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 503-512, July.
    17. Qiu, Dawei & Baig, Aimon Mirza & Wang, Yi & Wang, Lingling & Jiang, Chuanwen & Strbac, Goran, 2024. "Market design for ancillary service provisions of inertia and frequency response via virtual power plants: A non-convex bi-level optimisation approach," Applied Energy, Elsevier, vol. 361(C).
    18. Hui Sun & Yanan Dou & Shubo Hu & Zhengnan Gao & Zhonghui Wang & Peng Yuan, 2023. "Day-Ahead Bidding Strategy of a Virtual Power Plant with Multi-Level Electric Energy Interaction in China," Energies, MDPI, vol. 16(19), pages 1-27, September.
    19. Zahid Ullah & Arshad & Hany Hassanin, 2022. "Modeling, Optimization, and Analysis of a Virtual Power Plant Demand Response Mechanism for the Internal Electricity Market Considering the Uncertainty of Renewable Energy Sources," Energies, MDPI, vol. 15(14), pages 1-16, July.
    20. Mei, Shufan & Tan, Qinliang & Trivedi, Anupam & Srinivasan, Dipti, 2024. "A two-step optimization model for virtual power plant participating in spot market based on energy storage power distribution considering comprehensive forecasting error of renewable energy output," Applied Energy, Elsevier, vol. 376(PB).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jsusta:v:15:y:2023:i:12:p:9433-:d:1169186. 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.