One of the key strategies for reducing greenhouse gas emissions in the maritime industry is the adoption of “cold ironing,” which relies on a continuous external power source. This paper introduces the novel concept of nuclear microreactor-driven cold ironing as the primary power source for large maritime ports. Additionally, it proposes an artificial intelligence (AI) system as the enabling mechanism for the efficient and safe integration of microreactors into cold ironing operations. The proposed system combines a learning Gaussian Process with fuzzy logic inference, enabling the development of various operational modes that enhance the microreactor's flexibility in meeting cold ironing demands and attain energy efficiency. The AI system is tested in a simulated case study, demonstrating that the microreactor achieves the desired operational flexibility. Furthermore, it highlights significant advantages, including reduced emissions and lower operational costs. Notably, it is also concluded that the combination of AI and microreactors also has the capacity to efficiently power the entire port facility.


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    Title :

    Artificial Intelligence System for Enabling Microreactor-Driven Cold Ironing in Maritime Ports


    Contributors:


    Publication date :

    2025-05-05


    Size :

    582649 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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