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

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

Applied Energy, 2018, vol. 230, issue C, 62-77

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.

Keywords: All-electric ships; Energy management; Model predictive control (MPC); Real-time optimization; Hybrid energy storage (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (11)

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DOI: 10.1016/j.apenergy.2018.08.079

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