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Model predictive energy management in hybrid ferry grids
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| Published in: | Energy reports 6(2020), 2 vom: Feb., Seite 550-557 |
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| Authors and Corporations: | , , |
| Title: | Model predictive energy management in hybrid ferry grids/ Navid Vafamand, Jalil Boudjadar, Mohammad Hassan Khooban |
| Type of Resource: | E-Book Component Part |
| Language: | English |
| published: |
2020
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| Series: |
: Energy reports, 6(2020), 2 vom: Feb., Seite 550-557
, volume:6 |
| Subjects: | |
| Source: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
| Abstract: | 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. |
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| ISSN: |
2352-4847
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| DOI: | 10.1016/j.egyr.2019.11.118 |
| Access: | Open Access |