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Ports are increasingly becoming urban cyber-physical systems in which maritime operations, terminal activities, buildings, electricity networks, renewable generation and environmental pressures interact. Energy Management Systems (EMS) can coordinate energy production and consumption, while Digital Twins (DTs) can connect real-time data, simulation and decision support. Yet port digitalisation and port decarbonisation are still frequently treated as separate domains. This paper develops a Digital-Twin-enabled energy-management framework for urban ports and applies it to three Italian port-city systems: Genoa, Livorno and Naples. The study combines official energy-environmental plans, port emission inventories, operational information and infrastructure data to examine three dimensions of urban intelligence: data integration, energy-system coordination and implementation capacity. The comparison reveals a strong dominance of maritime activities in port-related emissions, accounting for approximately 80.1% in the Western Ligurian Port System, 87.85% in Livorno and 97.0% in Naples. Shore-side electricity nevertheless produces markedly different estimated environmental returns: carbon-abatement intensity ranges from 0.330 tCO2eq/MWh in Naples to 0.400 tCO2eq/MWh in Genoa Pra’ and 0.783 tCO2eq/MWh in Livorno. Planned intervention portfolios correspond to estimated emission reductions of approximately 9.0%, 14.3% and 10.2%, respectively. A sensitivity test for the Central Tyrrhenian case shows that implementation constraints can reduce the estimated portfolio effect from approximately 10.2% to 5.3%. Comparison with Rotterdam, Antwerp-Bruges, Valencia, Hamburg and Sines shows that international practice is moving from isolated smart assets toward integrated platforms linking sensing, simulation, energy optimisation and operational decisions. The paper therefore proposes a transferable architecture for Digital-Twin-enabled Port Energy Management and argues that urban intelligence emerges not from technology deployment alone, but from the capacity to connect information, prediction, physical intervention and verifiable environmental outcomes.
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Irina Di Ruocco (2026) studied this question.
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