Recent estimates indicate that roughly 80% of worldwide freight is carried at sea. With shipping and cargo handling responsible for at least 2.5% of annual carbon emissions, the maritime sector poses fertile ground for carbon reductions. This paper focuses on the use of Digital Twins for analyzing and optimizing energy consumption related to cargo handling in a seaport. Specifically, the paper focuses upon data-driven modelling and ‘what-if’ analysis to quantify the potential of energy regeneration capture in a seaport electrified gantry crane used for cargo handling. The crane, located in Middlesbrough, UK was modelled using real-time sensor and control system data on electricity consumption, position, velocity, and driver commands. Mean average modelling errors of less than 1% were obtained. The dynamic model was deployed for exploration of regeneration capture from lifting operations using a simulated Active Front End (AFE) of power electronics and batteries. Using calibrated simulations, data from a cargo handling system and historical annual consumption data, the paper provides estimates of the potential energy savings for three existing electrified cranes of approximately 420 MWh per year. Using conservative estimates of 40% reclamation of energy for all hoist lifting operations, obtained via a simplified static model, further potentially significant savings are suggested to be possible through the retrofitting of additional diesel cranes.
|Title of host publication||2022 26th International Conference on Circuits, Systems, Communications and Computers (CSCC)|
|Publication status||Published - 12 Oct 2022|
|Event||26th International Conference on Circuits, Systems, Communications and Computers - Crete, Chania, Greece|
Duration: 19 Jul 2022 → 22 Jul 2022
|Conference||26th International Conference on Circuits, Systems, Communications and Computers|
|Abbreviated title||CSCC 2022|
|Period||19/07/22 → 22/07/22|