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GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

Author

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  • David P. Chassin
  • Jason C. Fuller
  • Ned Djilali

Abstract

Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control system design, and integration of wind power in a smart grid.

Suggested Citation

  • David P. Chassin & Jason C. Fuller & Ned Djilali, 2014. "GridLAB-D: An Agent-Based Simulation Framework for Smart Grids," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-12, June.
    • Handle: RePEc:hin:jnljam:492320
    DOI: 10.1155/2014/492320
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    1. Morstyn, Thomas & Collett, Katherine A. & Vijay, Avinash & Deakin, Matthew & Wheeler, Scot & Bhagavathy, Sivapriya M. & Fele, Filiberto & McCulloch, Malcolm D., 2020. "OPEN: An open-source platform for developing smart local energy system applications," Applied Energy, Elsevier, vol. 275(C).
    2. Feng, Wei & Jin, Ming & Liu, Xu & Bao, Yi & Marnay, Chris & Yao, Cheng & Yu, Jiancheng, 2018. "A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools," Applied Energy, Elsevier, vol. 228(C), pages 1656-1668.
    3. Hanif, Sarmad & Mukherjee, Monish & Poudel, Shiva & Yu, Min Gyung & Jinsiwale, Rohit A. & Hardy, Trevor D. & Reeve, Hayden M., 2023. "Analyzing at-scale distribution grid response to extreme temperatures," Applied Energy, Elsevier, vol. 337(C).
    4. Helder Pereira & Bruno Ribeiro & Luis Gomes & Zita Vale, 2022. "Smart Grid Ecosystem Modeling Using a Novel Framework for Heterogenous Agent Communities," Sustainability, MDPI, vol. 14(23), pages 1-20, November.
    5. Vázquez-Canteli, José R. & Nagy, Zoltán, 2019. "Reinforcement learning for demand response: A review of algorithms and modeling techniques," Applied Energy, Elsevier, vol. 235(C), pages 1072-1089.
    6. Azraff Bin Rozmi, Mohd Daniel & Thirunavukkarasu, Gokul Sidarth & Jamei, Elmira & Seyedmahmoudian, Mehdi & Mekhilef, Saad & Stojcevski, Alex & Horan, Ben, 2019. "Role of immersive visualization tools in renewable energy system development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    7. Wang, Beibei & Chen, Li & Wang, Jiale & Zhao, Shengnan, 2022. "Microgrid distributed energy resources planning based on a long-term dynamic microsimulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 236-253.
    8. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    9. Foti, Magda & Vavalis, Manolis, 2019. "Blockchain based uniform price double auctions for energy markets," Applied Energy, Elsevier, vol. 254(C).
    10. Thomas Betten & Shivenes Shammugam & Roberta Graf, 2020. "Adjustment of the Life Cycle Inventory in Life Cycle Assessment for the Flexible Integration into Energy Systems Analysis," Energies, MDPI, vol. 13(17), pages 1-19, August.
    11. Kyungjin Yoo & Seth Blumsack, 2018. "The Political Complexity of Regional Electricity Policy Formation," Complexity, Hindawi, vol. 2018, pages 1-18, December.
    12. Sonja Kolen & Stefan Dähling & Timo Isermann & Antonello Monti, 2018. "Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent-Based Modeling and Simulation," Complexity, Hindawi, vol. 2018, pages 1-16, February.
    13. Battula, Swathi & Tesfatsion, Leigh & McDermott, Thomas E., 2020. "An ERCOT test system for market design studies," Applied Energy, Elsevier, vol. 275(C).

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