Maritime Decarbonisation through MetaPort

Maritime transportation is the backbone of international trade and global connectivity. To address the environmental impact of this sector, the International Maritime Organisation (IMO) has established strict regulations to reduce greenhouse gas emissions.

Energy Efficiency Management (EEM) has emerged as a primary strategy for lowering ship fuel consumption, serving as a pillar for the industry's 2050 sustainability goals.

A critical innovation in this transition is the use of Onshore Power Supplies (OPS). OPS, or "cold ironing," allows vessels to turn off their diesel engines and plug into the local electrical grid while at berth. The synergy between EEM and OPS is essential for modernising maritime logistics.

The MetaPort project, carried out by the Department of Electrical Engineering, explores this interconnection through a two-phase technical approach. First, the project utilises Machine Learning models including Artificial Neural Networks (ANN) and Random Forest Regression (RFR), to predict energy consumption and estimate specific onboard power demands.

Second, the project introduces a novel optimisation methodology based on meta-heuristic algorithms to determine the most efficient energy distribution patterns for ships in port.

To ensure real-world accuracy, the research accounts for external variables such as weather conditions. Factors like wind speed and direction significantly influence the energy required to maintain ship systems during berthing.

By calculating the minimum energy consumption necessary for various operations, MetaPort provides stakeholders with actionable data for ship management.

These advancements directly support the decarbonisation of ports and contribute to a more efficient, environmentally responsible shipping industry.