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Model predictive energy management in hybrid ferry grids
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| Veröffentlicht in: | Energy reports 6(2020), 2 vom: Feb., Seite 550-557 |
|---|---|
| Personen und Körperschaften: | , , |
| Titel: | Model predictive energy management in hybrid ferry grids/ Navid Vafamand, Jalil Boudjadar, Mohammad Hassan Khooban |
| Format: | E-Book-Kapitel |
| Sprache: | Englisch |
| veröffentlicht: |
2020
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| Gesamtaufnahme: |
: Energy reports, 6(2020), 2 vom: Feb., Seite 550-557
, volume:6 |
| Schlagwörter: | |
| Quelle: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
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| 520 | |a 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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| author | Vafamand, Navid, Boudjadar, Jalil, Khooban, Mohammad Hassan |
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| contents | 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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| spelling | Vafamand, Navid VerfasserIn aut, Model predictive energy management in hybrid ferry grids Navid Vafamand, Jalil Boudjadar, Mohammad Hassan Khooban, 2020, Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2, 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., DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/, Aufsatz in Zeitschrift DE-206, Kongressbeitrag DE-206, Boudjadar, Jalil VerfasserIn aut, Khooban, Mohammad Hassan VerfasserIn aut, Enthalten in Energy reports Amsterdam [u.a.] : Elsevier, 2015 6(2020), 2 vom: Feb., Seite 550-557 Online-Ressource (DE-627)820689033 (DE-600)2814795-9 (DE-576)427950821 2352-4847 nnns, volume:6 year:2020 number:2 month:02 pages:550-557, https://www.sciencedirect.com/science/article/pii/S2352484719309965/pdfft?md5=da95a5c35c573ecf9628095e36cc18f7&pid=1-s2.0-S2352484719309965-main.pdf Verlag kostenfrei, https://doi.org/10.1016/j.egyr.2019.11.118 Resolving-System kostenfrei, http://hdl.handle.net/10419/243931 Resolving-System kostenfrei, https://doi.org/10.1016/j.egyr.2019.11.118 LFER, https://www.sciencedirect.com/science/article/pii/S2352484719309965/pdfft?md5=da95a5c35c573ecf9628095e36cc18f7&pid=1-s2.0-S2352484719309965-main.pdf LFER, LFER 2020-04-07T00:00:00Z |
| spellingShingle | Vafamand, Navid, Boudjadar, Jalil, Khooban, Mohammad Hassan, Model predictive energy management in hybrid ferry grids, 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., Aufsatz in Zeitschrift, Kongressbeitrag |
| title | Model predictive energy management in hybrid ferry grids |
| title_auth | Model predictive energy management in hybrid ferry grids |
| title_full | Model predictive energy management in hybrid ferry grids Navid Vafamand, Jalil Boudjadar, Mohammad Hassan Khooban |
| title_fullStr | Model predictive energy management in hybrid ferry grids Navid Vafamand, Jalil Boudjadar, Mohammad Hassan Khooban |
| title_full_unstemmed | Model predictive energy management in hybrid ferry grids Navid Vafamand, Jalil Boudjadar, Mohammad Hassan Khooban |
| title_in_hierarchy | Model predictive energy management in hybrid ferry grids / Navid Vafamand, Jalil Boudjadar, Mohammad Hassan Khooban, |
| title_short | Model predictive energy management in hybrid ferry grids |
| title_sort | model predictive energy management in hybrid ferry grids |
| topic | Aufsatz in Zeitschrift, Kongressbeitrag |
| topic_facet | Aufsatz in Zeitschrift, Kongressbeitrag |
| url | https://www.sciencedirect.com/science/article/pii/S2352484719309965/pdfft?md5=da95a5c35c573ecf9628095e36cc18f7&pid=1-s2.0-S2352484719309965-main.pdf, https://doi.org/10.1016/j.egyr.2019.11.118, http://hdl.handle.net/10419/243931 |