Artificial Intelligence in Marine Electrical and Power Management Systems

Introduction
Modern vessels have evolved into complex, floating microgrids. The integration of AI into Power Management Systems (PMS) is driven by the transition to hybrid and fully electric propulsion, where AI optimises the interplay between batteries, hydrogen fuel cells, and traditional engines. The focus is on “Smart Grid” stability to support energy-intensive systems such as luxury cruise amenities and advanced naval sensors.

In emerging economies, AI in electrical systems is a vital tool for grid resilience and operational continuity. In regions where shore-power (cold ironing) infrastructure is still developing, AI allows vessels to self-optimise power distribution, reducing fuel waste and preventing localised blackouts that can lead to costly port delays. This course examines how AI-enabled power systems can be scaled to support both high-tech green vessels and retrofitted ageing fleets

From a managerial perspective, electrical resilience is the backbone of shipboard safety. Delegates will explore how AI can automate “load shedding” during critical manoeuvres and how to protect these increasingly digital power networks from cyber-physical threats.

Learning Outcomes
1. Design AI-enabled power management strategies for complex marine electrical microgrids.
2. Optimise load management to reduce fuel consumption and peak-power stress.
3. Implement smart grid technologies for seamless shore-to-ship power integration.
4. Evaluate redundancy strategies to ensure power for critical AI-driven navigation.
5. Develop “Zero-Trust” security protocols for electrical control networks.
6. Formulate power-scaling strategies for vessels operating in varied climate extremes.

Learning Objectives
1. Analyse AI-enabled electrical power systems and their integration with shipboard IoT.
2. Optimise power distribution using predictive AI for fluctuating electrical loads.
3. Assess resilience and redundancy strategies for mission-critical ship systems.
4. Describe how AI optimises battery-charging cycles in hybrid-electric vessels.
5. Examine the role of AI in managing “Microgrids” onboard offshore platforms.
6. Calculate the efficiency gains from AI-driven automated load shedding.