MAGPIE Energy matching tool

Ports are complex, energy-intensive ecosystems where multiple stakeholders must coordinate operations while responding to ambitious decarbonisation targets. At the same time, they face rising operational energy costs, growing CO2 emissions, limited visibility over local flexibility and missed opportunities to use energy resources more efficiently. The Energy Matching Tool (EMT), developed within MAGPIE, is an open-source decision-support solution that helps ports and port actors plan short-term energy operations over the next 24–48 hours. By coordinating local generation, demand flexibility and storage, it supports more efficient energy use, lower operational costs and improved integration of low-carbon energy sources. The tool provides users with practical operational recommendations and KPI-based results, helping them compare baseline and optimized scenarios in a transparent way.

The EMT is applicable to ports with a diverse mix of energy assets, including renewable generation, storage systems and flexible demand. It can model building climatization, smart reefers, onshore power supply, e-truck charging, swap battery containers, industrial loads and other modular or shiftable loads. For each use case, the model should be adapted to reflect the specific asset flexibility, operating rules, data availability and stakeholder constraints. The tool can support single operators as well as aggregators or port energy communities, particularly where coordinated energy use can create shared operational and economic benefits. Examples of port contexts where it can be applied Container terminals: high applicability due to cranes, reefers, e-trucks, onshore power supply and the potential for large-scale renewable integration. Ferry terminals: applicable where vessel charging, shore power or fleet electrification create controllable electricity demand. Industrial ports: applicable where flexible industrial loads, hydrogen production or shared energy infrastructure can be coordinated to improve energy efficiency and reduce operational costs. In general, the greater the level of energy demand, local production and operational flexibility, the greater the opportunity to unlock value through coordinated planning.

Implementation requires access to representative energy data, asset characteristics, tariffs, operational constraints and, where relevant, grid topology. The tool can initially be used locally for experiments and demonstrations, using prepared input files and example notebooks from the MAGPIE repository.

A practical implementation starts with selecting the port area or community to analyse, identifying relevant assets and collecting the required input data. A first baseline simulation should be run to validate profiles and constraints. Flexible simulation scenarios can then be tested to understand the potential of having controllable assets such as smart reefers, OPS, e-truck charging, storage or industrial loads. For multi-player settings, the market layer can be added to test internal energy exchange and compare benefits for the community and each player. As stakeholders gain confidence in the digital solution, implementation can evolve from simulation-based assessment to real operational use, first through pilot applications and later across broader port use cases.

The core stakeholders are the port authority, terminal operators, industrial consumers, renewable energy producers, distribution/grid operators, technology providers. Port authorities can coordinate strategy and data governance; operators and industrial users provide operational constraints and validate recommendations; energy producers and aggregators enable local supply and trading; technology providers support deployment and maintenance; research partners support modelling, validation and future improvements.