Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Analysis and simulation of smart energy clusters and energy value chain for fish processing industries

Alzahrani, Ateyah, Petri, Ioan ORCID: and Rezgui, Yacine ORCID: 2020. Analysis and simulation of smart energy clusters and energy value chain for fish processing industries. Presented at: 6th International Conference on Energy and Environment Research, ICEER 2019, Aveiro, Portugal, 22-25 July 2019. Published in: Sa Caetano, Nidia, Borrego, Carlos, Nunes, Maria Isabel and Felgueiras, Manuel Carlos eds. The 6th International Conference on Energy and Environment Research - Energy and environment: challenges towards circular economy. Energy Reports. , vol.6 (1) (6 (1)) Elsevier, pp. 534-540. 10.1016/j.egyr.2019.09.022

[thumbnail of untitled.pdf]
PDF - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (908kB) | Preview


The Irish Seafood agency reports that 15% of global energy is consumed by operations related to refrigeration and air conditioning in the fish industry which stresses the importance of integration with clean renewables and adoption of smart energy management solutions. While fish processing industries have high energy costs with continuous refrigeration, air conditioning and ice making processes, there is a real need to analyse and model energy use in fish ports to understand environmental impacts in terms of CO2 emissions while exploring the potential for integrating renewable energy sources. In this paper, we conduct energy modelling and optimization for the Milford Haven fish processing port in South Wales. We explain how a simulation capability can be developed at the fish industry port level and propose a simulation-based optimization strategy to determine optimized schedules for appliances. The results show that energy consumption can be reduced with the use of optimized appliance schedules developed in relation to the total energy demand as well as a wide range of optimization constraints.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 2352-4847
Date of First Compliant Deposit: 20 April 2020
Date of Acceptance: 12 September 2019
Last Modified: 26 Oct 2022 07:46

Citation Data

Cited 8 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics