Battery Energy Storage Systems (BESS) are increasingly recognised as a viable solution for fuel consumption reduction and resilience enhancement of Naval Ship Power Systems (NSPS). However, the effectiveness of battery systems is influenced by operational profiles, power system configuration, reliability requirements, battery sizing, and the Energy Management Strategy (EMS). This paper presents a multi-layered, multi-objective optimisation framework for BESS power and capacity configuration selection and sizing in NSPS, leveraging operational data and Dynamic Programming to evaluate design trade-offs. The method identifies Pareto-optimal configurations balancing fuel consumption, battery degradation, and system reliability. The framework is validated using onboard load measurements and evaluates BESS parameter sizing over a given design space in different scenarios, comparing benefits in fuel efficiency, BESS utilisation, and system reliability. Findings suggest that adopting a Minimum Generator Operation (MGO) strategy with a BESS may decrease generator operating hours by up to 33 %, while optimised load sharing yields up to a 2 % reduction in fuel consumption during manoeuvring. The study highlights Pareto-optimal solutions based on selected Performance Functions (PF) and introduces the concept of assisted multi-objective design of shipboard battery systems.
Multi-objective optimisation-based approach for shipboard energy-efficient battery energy storage sizing leveraging operational data
Belvisi, Daniele;Figari, Massimo
2025-01-01
Abstract
Battery Energy Storage Systems (BESS) are increasingly recognised as a viable solution for fuel consumption reduction and resilience enhancement of Naval Ship Power Systems (NSPS). However, the effectiveness of battery systems is influenced by operational profiles, power system configuration, reliability requirements, battery sizing, and the Energy Management Strategy (EMS). This paper presents a multi-layered, multi-objective optimisation framework for BESS power and capacity configuration selection and sizing in NSPS, leveraging operational data and Dynamic Programming to evaluate design trade-offs. The method identifies Pareto-optimal configurations balancing fuel consumption, battery degradation, and system reliability. The framework is validated using onboard load measurements and evaluates BESS parameter sizing over a given design space in different scenarios, comparing benefits in fuel efficiency, BESS utilisation, and system reliability. Findings suggest that adopting a Minimum Generator Operation (MGO) strategy with a BESS may decrease generator operating hours by up to 33 %, while optimised load sharing yields up to a 2 % reduction in fuel consumption during manoeuvring. The study highlights Pareto-optimal solutions based on selected Performance Functions (PF) and introduces the concept of assisted multi-objective design of shipboard battery systems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



