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Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks

Author

Listed:
  • Bishnu P. Bhattarai

    (Idaho National Laboratory, Idaho Falls, ID 83415, USA)

  • Kurt S. Myers

    (Idaho National Laboratory, Idaho Falls, ID 83415, USA)

  • Birgitte Bak-Jensen

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark)

  • Sumit Paudyal

    (Department of Electrical and Computer Engineering, Michigan Technological University, Houghton, MI 49931, USA)

Abstract

This paper presents a multi-timescale control strategy to deploy electric vehicle (EV) demand flexibility for simultaneously providing power balancing, grid congestion management, and economic benefits to participating actors. First, an EV charging problem is investigated from consumer, aggregator, and distribution system operator’s perspectives. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating multi-time scale controls that work from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical residential distribution grid. The simulation results demonstrate that HCA efficiently utilizes demand flexibility stemming from EVs to solve grid unbalancing and congestions with simultaneous maximization of economic benefits to the participating actors. This is ensured by enabling EV participation in day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to five times the cost they were paying without control.

Suggested Citation

  • Bishnu P. Bhattarai & Kurt S. Myers & Birgitte Bak-Jensen & Sumit Paudyal, 2017. "Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks," Energies, MDPI, vol. 10(1), pages 1-18, January.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:1:p:37-:d:86689
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    References listed on IDEAS

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    3. Kohlhepp, Peter & Harb, Hassan & Wolisz, Henryk & Waczowicz, Simon & Müller, Dirk & Hagenmeyer, Veit, 2019. "Large-scale grid integration of residential thermal energy storages as demand-side flexibility resource: A review of international field studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 527-547.
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    5. Solanke, Tirupati U. & Khatua, Pradeep K. & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao, 2021. "Control and management of a multilevel electric vehicles infrastructure integrated with distributed resources: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
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    8. S. Muhammad Bagher Sadati & Jamal Moshtagh & Miadreza Shafie-khah & João P. S. Catalão, 2017. "Risk-Based Bi-Level Model for Simultaneous Profit Maximization of a Smart Distribution Company and Electric Vehicle Parking Lot Owner," Energies, MDPI, vol. 10(11), pages 1-16, October.

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