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This chapter focuses on long-term energy management strategies for shipboard energy storage systems (ESSs), aiming to enhance fuel economy and energy efficiency across entire voyages. Two core strategies are proposed: a hierarchical robust scheduling strategy and a distributed energy dispatching strategy. The hierarchical strategy optimizes hybrid ESS (HESS) sizing via mixed-integer quadratic programming (MIQCP) and implements a three-layer power allocation scheme (daily/hourly/minutely) to smooth power fluctuations. The distributed strategy addresses performance inconsistencies among distributed lithium-ion batteries (LiBs) by integrating state coupling models, minimizing fuel consumption, and mitigating instantaneous load fluctuations through wavelet packet decomposition. Validated with real-world propulsion data, the strategies reduce fuel consumption by up to 20.8%, stabilize DC bus voltage (fluctuation range 1478.5–1515.4V), and ensure LiBs operate within safe state-of-health (SOH) and state-of-charge (SOC) ranges. These results confirm the strategies’ effectiveness in improving the economy, stability, and reliability of shipboard microgrids under uncertain navigation conditions.

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Long-Term Energy Management Strategy: Validation and Analysis

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  • 发表日期：

    2026年

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  • Yingbing Luo,
  • Sidun Fang

摘要

This chapter focuses on long-term energy management strategies for shipboard energy storage systems (ESSs), aiming to enhance fuel economy and energy efficiency across entire voyages. Two core strategies are proposed: a hierarchical robust scheduling strategy and a distributed energy dispatching strategy. The hierarchical strategy optimizes hybrid ESS (HESS) sizing via mixed-integer quadratic programming (MIQCP) and implements a three-layer power allocation scheme (daily/hourly/minutely) to smooth power fluctuations. The distributed strategy addresses performance inconsistencies among distributed lithium-ion batteries (LiBs) by integrating state coupling models, minimizing fuel consumption, and mitigating instantaneous load fluctuations through wavelet packet decomposition. Validated with real-world propulsion data, the strategies reduce fuel consumption by up to 20.8%, stabilize DC bus voltage (fluctuation range 1478.5–1515.4V), and ensure LiBs operate within safe state-of-health (SOH) and state-of-charge (SOC) ranges. These results confirm the strategies’ effectiveness in improving the economy, stability, and reliability of shipboard microgrids under uncertain navigation conditions.