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首页> 外文期刊>Energy Reports >The 6th International Conference on Power and Energy Systems Engineering (CPESE 2019), September 20–23, 2019, Okinawa, Japan Model predictive energy management in hybrid ferry grids
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The 6th International Conference on Power and Energy Systems Engineering (CPESE 2019), September 20–23, 2019, Okinawa, Japan Model predictive energy management in hybrid ferry grids

机译:第六届国际电力和能源系统会议(CPESE 2019),2019年9月20日至23日,日本冲绳模型在混合渡轮网格中的预测能源管理

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摘要

High performance and cost-effective ferry boats are of capital interest for customers and marine industry companies. On the other hand, the traditional ferry boats, operated by diesel generators, spatter the atmosphere with CO2 emissions and detrimental particles. Hence, electric propulsion in marine applications, especially in ferry vessel systems, has gained a lot of attention during the last decade as a promising technology to decrease fuel consumption and emissions. However, one of the main issues in the electric ferries (E-Ferry) is to keep the voltage and frequency within an acceptable range according to the large dynamic load fluctuations. In order to solve this issue, this paper presents a model predictive energy management based on a modified black hole algorithm (BHA) for the hybrid E-Ferry systems. Finally, to study the efficiency of our proposal, we run a real-time simulation using the d-Space simulator and compare the effect of the prediction horizon on the system performance.
机译:高性能和经济高效的渡船对客户和海洋工业公司具有资本利益。另一方面,由柴油发电机运营的传统渡船,用二氧化碳排放和有害颗粒飞溅大气。因此,在船舶应用中的电动推进,特别是在渡轮船系统中,在过去的十年中,在过去的十年中获得了很多关注,以降低燃料消耗和排放的有希望的技术。然而,电渡轮(E-FERRY)中的主要问题之一是根据大动态负载波动保持可接受范围内的电压和频率。为了解决这个问题,本文提出了一种基于用于混合电子渡轮系统的改进的黑洞算法(BHA)的模型预测能量管理。最后,要研究我们提案的效率,我们使用D-Space Simulator进行实时仿真,并比较预测地平线对系统性能的影响。

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