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A distributed real-time power management scheme for shipboard zonal multi-microgrid system

Author

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  • Xie, Peilin
  • Tan, Sen
  • Bazmohammadi, Najmeh
  • Guerrero, Josep. M.
  • Vasquez, Juan. C.
  • Alcala, Jose Matas
  • Carreño, Jorge El Mariachet

Abstract

The increasing demands of reducing fuel consumption for marine transportation have motivated the use of high fuel efficiency power plants and the development of power management systems (PMS). Current studies on shipboard PMS are mostly categorized as centralized, which are easy to be implemented and able to converge to the global optimum solutions. However, centralized techniques may suffer from the high computational burden and single-point failures. Considering the future trends of marine vessels toward zonal electrical distribution (ZED), distributed PMS are becoming an alternative choice. To achieve the ship high fuel-efficiency operation under high fluctuated propulsion loads, a real-time distributed PMS is developed in this paper that can acquire as good fuel economy as centralized PMS, but with faster computing speed. With a combination of filter-based, rule-based, and optimization-based approaches in a highly computationally efficient manner, the distributed PMS is constructed based on three layers that guarantees not only high fuel efficiency, but also sufficient energy reservation in different sailing modes and even in faulty conditions. Convergence tests and multiple case studies are conducted to prove the effectiveness of the proposed PMS in terms of fast convergence speed, improved fuel efficiency, and enhanced resilience.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:317:y:2022:i:c:s0306261922004639
    DOI: 10.1016/j.apenergy.2022.119072
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    1. Jiankai Gao & Yang Li & Bin Wang & Haibo Wu, 2023. "Multi-Microgrid Collaborative Optimization Scheduling Using an Improved Multi-Agent Soft Actor-Critic Algorithm," Energies, MDPI, vol. 16(7), pages 1-21, April.

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