Evaluation of the Emission Impact of Cold-Ironing Power Systems, Using a Bi-Directional Power Flow Control Strategy

Carlos A. Reusser and Joel R. Pérez
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Carlos A. Reusser: School of Electrical Engineering, Pontificia Universidad Catolica de Valparaiso, Valparaíso 2340025, Chile
Joel R. Pérez: Mechanical Engineering Department, University College London, London WC1E 6BT, UK

Sustainability, 2020, vol. 13, issue 1, 1-16

Abstract: Even though cold ironing is not a new technology applied to reduce the impact of emissions from ships at berth, commonly used arrangements for shore-side power substations only allow a unidirectional power flow, from port to ship side. Although these applications have a positive contribution to port community health and global reduction of greenhouse gases (GHG), especially when the energy is supplied from renewable sources, emissions during loading/unloading operations are directly related to the operating profiles of auxiliary engines of a ship. The present work evaluates a ship’s emission impact when applying cold-ironing technology using a bi-directional power flow control strategy while at berth, thus optimizing the auxiliary engine operating profile and enabling regeneration into the port installations. The methodology applied considers the establishment of the operational profile of the ship, the adaptation and use of carbon intensity indicators (CII) used by the International Maritime Organization (IMO) to evaluate the impact of shipping, and the strategy considering the capacities of the ship to obtain and provide electric power from and to the port when at berth. Results show that the strategy can be applied to any ship with a high demand for electric power while at berth, and that the adaptation and use of different CIIs allows operational profiles of electric power generation on board to be optimized and to reduce emission generation, which affects port community health.

Keywords: cold ironing; emissions impact; electric power generation; back-to-back power converter; optimization algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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