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Coordinated augmented-output model predictive control for frequency regulation using electric vehicles in low-inertia power systems

Author

Listed:
  • Torkan, Ramin
  • Wang, Zhanle
  • Tang, Yili

Abstract

Increasing renewable energy integration reduces system inertia, resulting in significant frequency stability challenges in low-inertia power systems, such as larger frequency deviations and higher rates of change of frequency following disturbances. Electric vehicles (EVs) offer fast frequency response capabilities effective against rapid frequency fluctuations. However, many existing EV-based frequency-control strategies treat EVs as standalone dynamic models and do not provide unified, constraint-aware co-optimization with conventional governor response and do not explicitly account for the rate of change of frequency within the predictive control objective. This study proposes a unified and coordinated model predictive control (MPC) strategy that simultaneously manages a fleet of EVs and a conventional generator to maintain system frequency in low-inertia grids. The MPC incorporates detailed EV dynamics and constraints alongside generator limitations. Its key novelty lies in an augmented-output formulation that dynamically balances the fast frequency response of EVs with the slower generator response, jointly penalizing frequency deviation and a model-based rate of change of frequency estimate in the cost function. Simulation results demonstrate better performance than other control methods at different levels of renewable energy penetration and under two types of disturbances. Specifically, the coordinated approach improves post-disturbance frequency nadir by more than 0.2 Hz and reduces initial rate of change of frequency while always respecting EV and generator operational constraints. The proposed coordinated approach maintains frequency reliably within operational bounds during large disturbances at high renewable penetration as opposed to violating frequency boundaries without control. For system operators, this tighter frequency containment reduces operational risk and enables higher renewable integration in low-inertia power systems.

Suggested Citation

  • Torkan, Ramin & Wang, Zhanle & Tang, Yili, 2026. "Coordinated augmented-output model predictive control for frequency regulation using electric vehicles in low-inertia power systems," Applied Energy, Elsevier, vol. 409(C).
    • Handle: RePEc:eee:appene:v:409:y:2026:i:c:s0306261926001261
    DOI: 10.1016/j.apenergy.2026.127474
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    References listed on IDEAS

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    1. Hermans, B.A.L.M. & Walker, S. & Ludlage, J.H.A. & Özkan, L., 2024. "Model predictive control of vehicle charging stations in grid-connected microgrids: An implementation study," Applied Energy, Elsevier, vol. 368(C).
    2. Irfan, Muhammad & Deilami, Sara & Huang, Shujuan & Tahir, Tayyab & Veettil, Binesh Puthen, 2024. "Optimizing load frequency control in microgrid with vehicle-to-grid integration in Australia: Based on an enhanced control approach," Applied Energy, Elsevier, vol. 366(C).
    3. Oshnoei, Arman & Kheradmandi, Morteza & Blaabjerg, Frede & Hatziargyriou, Nikos D. & Muyeen, S.M. & Anvari-Moghaddam, Amjad, 2022. "Coordinated control scheme for provision of frequency regulation service by virtual power plants," Applied Energy, Elsevier, vol. 325(C).
    4. Liu, Hui & Huang, Kai & Wang, Ni & Qi, Junjian & Wu, Qiuwei & Ma, Shicong & Li, Canbing, 2019. "Optimal dispatch for participation of electric vehicles in frequency regulation based on area control error and area regulation requirement," Applied Energy, Elsevier, vol. 240(C), pages 46-55.
    5. Li, Pengfei & Hu, Weihao & Xu, Xiao & Huang, Qi & Liu, Zhou & Chen, Zhe, 2019. "A frequency control strategy of electric vehicles in microgrid using virtual synchronous generator control," Energy, Elsevier, vol. 189(C).
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