Digitalization for Port Decarbonization: Decarbonization of key energy processes at the Port of Tyne
| العنوان: | Digitalization for Port Decarbonization: Decarbonization of key energy processes at the Port of Tyne |
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| المؤلفون: | Ilias Sarantakos, Annabel Bowkett, Adib Allahham, Timur Sayfutdinov, Alan Murphy, Kayvan Pazouki, John Mangan, Guanlan Liu, Enrong Chang, Eleni Bougioukou, Haris Patsios |
| المصدر: | IEEE Electrification Magazine. 11:61-72 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Energy Engineering and Power Technology, Electrical and Electronic Engineering |
| الوصف: | This article presents findings of the Clean Tyne Project. This project was part of the Clean Maritime Demonstration, funded by the UK’s Department for Transport and delivered in partnership with Innovate UK. Announced in March 2020, and part of the Prime Minister’s Ten Point Plan to position the UK at the forefront of green shipbuilding and maritime technology, the Clean Maritime Demonstration Competition was a £20m investment from government alongside a further £10m from industry to reduce emissions from the maritime sector. The contribution of Newcastle University in the project was to provide quantifiable evidence around the benefits of digitalization, by means of a real-time supervisory and data acquisition platform, in the reduction of carbon emissions, as well as operating and infrastructural costs, at the Port of Tyne.The main aim of this article is to report and discuss the key outputs originating from the modelling performed by Newcastle University around specific operational scenarios at the port. These are intended to highlight the value of intelligent coordination of key energy processes and reduced uncertainty of associated data, both enabled by digitalization. For this purpose, we have designed and modelled current and future operational scenarios, in which Emission Reduction Technologies (ERTs)1 and infrastructure are introduced, alongside increased capability for coordination of energy assets and data availability. In our analysis we consider a centralized decision-making process where energy costs and carbon emissions are minimized subject to available infrastructure and data.Our results can be divided into three categories: impact of emission reduction technologies, impact of coordination, and impact of uncertainty on investment deferral. Under certain credible modelling and data assumptions, and considering energy operational costs and emissions, our findings are that: ERTs can yield significant emissions reductions of up to 93% in year 2040 compared to a present scenario, even if imported power is not 100% zero-carbon; energy costs related with key operations can be reduced up to 45% in year 2050 compared to a scenario where assets are not coordinated; and finally, confidence in data can yield significant reductions in infrastructural investment costs for key energy assets such as energy storage; we have noted that reduction of uncertainty through data availability (due to digitalization) led to a £3.35 Mreduction of CapEx for a particular case considering energy storage installed at the Port of Tyne. We now continue by showing how we modelled port operational scenarios. We then perform a quantitative analysis of cost and carbon emission savings that can be achieved by intelligent coordination of key processes, as well as savings in the form of deferral of network reinforcement and investment in new assets and technologies due to reduced uncertainty around historical data. We subsequently present our results, key findings, and conclude this article, including some suggestions for future work. |
| وصف الملف: | text |
| تدمد: | 2325-5889 2325-5897 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::daa99abc11f57d711781056261718a7d https://doi.org/10.1109/mele.2022.3233114 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....daa99abc11f57d711781056261718a7d |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 23255889 23255897 |
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