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

机译:鱼类加工行业智能能量集群与能源价值链的分析与仿真

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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 COsub2/sub 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.
机译:爱尔兰海鲜机构报告说,15%的全球能源通过与鱼类工业中的制冷和空调有关的作业消耗,这强调了与清洁可再生能源和采用智能能源管理解决方案集成的重要性。虽然鱼类加工行业具有持续的制冷,空调和制冰工艺的能源成本高,但有一个真正需要分析和模型在鱼港的能源使用,以了解CO 2 排放的环境影响探索集成可再生能源的可能性。在本文中,我们对南威尔士州米尔福德避风港鱼加工港进行能源建模和优化。我们解释了如何在鱼行业端口级别开发模拟能力,并提出基于模拟的优化策略,以确定设备的优化计划。结果表明,可以使用与总能源需求相关的优化设备调度以及广泛的优化约束使用的优化设备调度来减少能耗。

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