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Modelling and implementing smart micro-grids for fish-processing industry

Alzahrani, Ateyah, Petri, Ioan ORCID: https://orcid.org/0000-0002-1625-8247 and Rezgui, Yacine ORCID: https://orcid.org/0000-0002-5711-8400 2019. Modelling and implementing smart micro-grids for fish-processing industry. Presented at: 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), Valbonne Sophia-Antipolis, France, 17-19 June 2019. Proceedings 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE, -. 10.1109/ICE.2019.8792575

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Abstract

Fish processing industries involve the usage of energy-intensive equipment, such as refrigerators, air conditioners and ice making machines leading to high energy costs and, indirectly, to an increase of the carbon emissions. As most fish industries sites are old, there is a strong need to make them more sustainable and achieve economic competitiveness in the energy market. Micro-grids have been utilised as efficient solutions in energy-intensive industries greatly balancing energy consumption and production at different scales. Smart micro-grids can also reduce carbon emissions by using renewable energy resources and applying smart energy management techniques.In this paper, we propose a smart micro-grid system for fish-processing industries with a validation use-case at Milford Haven Port in South Wales, UK. The system has been modelled using EnergyPlus and Matlab with the infinite grid, renewable energy resource, battery and charge/discharge controllers utilized for optimising energy consumption and production and for reducing carbon emissions. The preliminary results show that local power demand can meet the local power generation with the implementation of smart energy management techniques to support decision making for fish-processing industries.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Engineering
Publisher: IEEE
Date of First Compliant Deposit: 20 August 2019
Date of Acceptance: 11 April 2019
Last Modified: 06 May 2023 01:34
URI: https://orca.cardiff.ac.uk/id/eprint/125028

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Cited 6 times in Scopus. View in Scopus. Powered By Scopus® Data

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