Bridging the gap between energy optimisation and marine power safety

A structured framework that integrates safety-informed operational decisions into real-world energy optimisation could bridge the gap between theoretical models and practical engineering constraints

Marine and offshore units rely on complex electrical power systems that must balance safety, reliability, and operational efficiency. While modern research has progressed in modelling energy optimisation and hybrid systems, many times it is observed that blackouts proceed during or close to manoeuvring periods of the vessel due to late reaction of Power Management System (PMS) which works on predefined limitations.

It has been observed that a critical gap remains between theoretical energy optimisation strategies and the operational safety decisions made by engineers in the field. In practice, energy-efficient configurations are frequently overridden by operating engineers due to system protection limitations or safety concerns. There is a mismatch between optimised theoretical performance and actual system behaviour because existing models do not account for human interventions that deviate from automated PMS logic. This research leverages field experience in electrical commissioning and operator behaviour to integrate safety decision-making into energy optimisation frameworks.

Current research typically optimises energy usage under controlled assumptions and treats safety, reliability as secondary concerns. These models often assume that human decisions and protection systems will align perfectly with mathematical predictions. In contrast, real-world operations involve:

• Safety-driven overrides of optimised states

• Human adjustments in protection coordination

• Critical trade-offs between operational efficiency and blackout avoidance.

There is a fundamental need for a framework that explicitly embeds human operational behaviour and real-world constraints into the existing energy models. The aim of this article is to propose a structured framework that integrates safety-informed operational decisions into real-world energy optimisation, bridging the gap between theoretical models and practical engineering constraints. The specific objectives include:

1. Characterising safety-oriented decisions based on field cases and offshore experience.

2. Identifying conflict scenarios where optimal energy strategies clash with safety priorities.

3. Developing an integrated framework that embeds safety decision behaviour into optimisation models.

4. Proposing risk-aware optimisation techniques that balance efficiency with safety constraints.

5. Validating the approach using simulations and real-world case studies.

A three-layer approach

Using field data from offshore commissioning and recorded decisions affecting system safety, the methodology involves three layered management. The top layer (operational safety decisions) triggers manual overrides and emergency interventions.

The intermediate layer (reliability constraints) monitors load limits, spinning reserve margins, and stability while the base layer (energy optimisation) performs standard generator scheduling and load sharing.

During high-risk conditions, (such as manoeuvring in port), the safety and reliability layers have the authority to override optimisation objectives. During real-time marine operations, a sudden load demand (from bridge control) during manoeuvring can outpace the PMS response time with starting of reserve generator, potentially resulting in a blackout. Consequently, manual intervention is necessary to maintain vessel safety and prevent the development of uncontrollable conditions.

This study identifies the gap between theoretical models and actual practice in marine power systems. By employing a hierarchical structure where safety and reliability govern optimisation, a more realistic representation of system operation is achieved. This methodology supports the development of next-generation, resilient Power Management Systems and provides a foundation for future research in real-time risk-informed control.

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Main image: Tugboat assisting container cargo ship to harbour. Credit: Shutterstock.