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New modular Electrical architecture and digital platforM to Optimise large battery systems on SHIPs

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

D1.2: Lessons learnt from ZEWT projects and from other sectors (opens in new window)

Analysis of European projects that develop and demonstrate deployable technological solutions of several applications such as the waterborne transport, mobility and stationary. This analysis will focus on the assessment of similar faced obstacles, lessons learnt from decisions and roadmaps in the projects in order to take advantage of strengths related to the waterborne sector to reach these goals.Refer to task T1.2

D1.1: Experiences learnt from BESS commercial exploitation and improvement requirements (opens in new window)

The deliverable presents the experiences learnt from the fuel savings and emission reductions data gathered from more than 500 BESS installations on various commercial vessels across Europe. The 500 kWh BESS retrofitted onto a hybrid electric vessel and the 4.5 MWh BESS installation on a new hybrid electric vessel are used to quantitively identify the improvement requirements for installations and operations. The further requirements needed of BESS to deal with both increasing importance of safety and further CO2 emission reductions will be identified.

D9.3: DEC plan and report (opens in new window)

‘plan for dissemination and exploitation including communication activities’ . This report will be periodically updated in alignment with the project's progress.

D2.1: Report on specifications and infrastructure definition for the digital tool platform (opens in new window)

From the requirements (D1.5), this deliverable define the specification, architecture and test plan of the digital platform considering :- a wide variety of marine data (technical and non-technical) should be analysed and pre-processed for integration in the digital tool.- Artificial Intelligence applications employed and tested for big datasets analysis - links and cyber-secured communications between the cloud infrastructure and the third-party software used by shipowners and vessel operators.Refer to task T2.1

Publications

Lessons learned from the commercial exploitation of marine battery energy storage systems (opens in new window)

Author(s): Wei He a, Lars O. Valøen b, Kjetil V. Olsen c, Kåre M. Kjeka c, Bjørn M. Fredriksen c, Mathieu Petiteau d, Amine Touat d, Helge Såtendal a, Aaron Howie a, David Howey e, Rambabu Kandepu b, Carsten F. Hammershøj
Published in: Journal of Energy Storage, 2024, ISSN 2352-152X
Publisher: Journal of Energy Storage
DOI: 10.1016/j.est.2024.111440

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