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Multi-Objective Optimal Dispatching for Heterogeneous Multienergy Ship Microgrid
School of Electrical Engineering, Yanshan University, Qinhuangdao, China.
School of Electrical Engineering, Yanshan University, Qinhuangdao, China,.
School of Electrical Engineering, Yanshan University, Qinhuangdao, China.
School of Electrical Engineering, Yanshan University, Qinhuangdao, China.
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2023 (English)In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 6576-6581Conference paper, Published paper (Refereed)
Abstract [en]

With the growth of energy and transportation demand, the integrated energy dispatching of ship power grid has become the focus of researchers. The optimization technique is used to reduce the total energy consumption and pollutant emissions of ships, optimizing the ship power generation planning. The purpose is to achieve environmental protection and energy saving while ensuring the continuous and reliable power supply of ships. However, heterogeneous ship microgrid poses new challenges to integrated energy dispatch. This paper proposes an integrated energy scheduling scheme that integrates photovoltaic, wind power, diesel engine, gas turbine, and battery for a heterogeneous multienergy ship microgrid. Under the system constraints, a multi-objective optimal scheduling model including operating costs and pollutant emissions is established, then the gravity search algorithm is applied to solve such an issue. The simulation results show that the scheme can effectively reduce the cost of energy consumption and pollutant emissions of ships, improving the economy, reliability and energy conservation, which verify the advantages of the proposed scheme.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023. p. 6576-6581
Series
Proceedings of the IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-343746DOI: 10.1109/CDC49753.2023.10384251ISI: 001166433805062Scopus ID: 2-s2.0-85184808261OAI: oai:DiVA.org:kth-343746DiVA, id: diva2:1839941
Conference
62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, Dec 13 2023 - Dec 15 2023
Note

Part of ISBN 9798350301243

QC 20240222

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-03-26Bibliographically approved

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Xu, Qianwen

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • de-DE
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Output format
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