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Implementation and evaluation of real-time model predictive control for load fluctuations mitigation in all-electric ship propulsion systems

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  • Hou, Jun
  • Song, Ziyou
  • Park, Hyeongjun
  • Hofmann, Heath
  • Sun, Jing

Abstract

Electrification is a clear trend for both commercial and military ship development. Shipboard load fluctuations, such as propulsion-load fluctuations and pulse power loads, can significantly affect power system reliability. In order to address this issue, this paper explores a real-time model predictive control based energy management strategy for load fluctuation mitigation in all-electric ships. A battery combined with ultra-capacitor hybrid energy storage system (HESS) is used as a buffer to compensate load fluctuations from the shipboard network. In order to implement the proposed real-time MPC-based energy management strategy on a physical testbed, three special efforts have been made to enable real-time implementation: a specially tailored problem formulation, an efficient optimization algorithm and a multi-core hardware implementation. Given the multi-frequency characteristics of load fluctuations, a filter-based power split strategy is developed as a baseline control to evaluate the proposed MPC. Compared to the filter-based strategy, the experimental results show that the proposed real-time MPC achieves superior performance in terms of enhanced system reliability, improved HESS efficiency, long self-sustained time, and extended battery life. The bus voltage variation and hybrid energy storage losses can be reduced by up to 38% and 65%, respectively.

Suggested Citation

  • Hou, Jun & Song, Ziyou & Park, Hyeongjun & Hofmann, Heath & Sun, Jing, 2018. "Implementation and evaluation of real-time model predictive control for load fluctuations mitigation in all-electric ship propulsion systems," Applied Energy, Elsevier, vol. 230(C), pages 62-77.
    • Handle: RePEc:eee:appene:v:230:y:2018:i:c:p:62-77
    DOI: 10.1016/j.apenergy.2018.08.079
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    5. Haseltalab, Ali & Negenborn, Rudy R., 2019. "Model predictive maneuvering control and energy management for all-electric autonomous ships," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    6. Hou, Jun & Song, Ziyou, 2020. "A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivity," Applied Energy, Elsevier, vol. 257(C).
    7. Xie, Peilin & Tan, Sen & Bazmohammadi, Najmeh & Guerrero, Josep. M. & Vasquez, Juan. C. & Alcala, Jose Matas & Carreño, Jorge El Mariachet, 2022. "A distributed real-time power management scheme for shipboard zonal multi-microgrid system," Applied Energy, Elsevier, vol. 317(C).
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