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Trinh Hoang Nguyen disputerer for ph.d-graden med avhandlingen "Offshore Wind Data Integration", der han analyserer hvordan datastrømmer kan brukes til å fjernstyre offshore vindkraftanlegg bedre.
Artikkelen er mer enn ett år gammel, og kan inneholde utdatert informasjon.
I avhandlingen har Trinh Hoang Nguyen utviklet et rammeverk for integrert behandling av data fra offshore vindfarmer. Han foreslår også at det blir laget en felles forståelse av feltet, slik at det blir enklere å utveksle kunnskap og data.
Forskningen er delvis finansiert av NORCOWE - Norwegian Centre for Offshore Wind Energy, der UiA er en av deltakerinstitusjonene.
Trinh Hoang Nguyen har fulgt doktorgradsutdanningen ved Fakultet for teknologi og realfag, med spesialisering i IKT.
Using renewable energy to meet the future electricity consumption and to reduce environmental impact is a significant target of many countries around the world. Wind power is one of the most promising renewable energy technologies.
In particular, the development of offshore wind power is increasing rapidly due to large areas of wind resources. However, offshore wind is encountering big challenges such as effective use of wind power plants, reduced cost of installation as well as operation and maintenance (O&M).
Improved O&M is likely to reduce the hazard exposure of the employees, increase income, and support offshore activities more efficiently. In order to optimize the O&M, the importance of data exchange and knowledge sharing within the offshore wind industry must be realized. With more data available and accessible, it is possible to make better decisions, and thereby improve the recovery rates and reduce the operational costs.
This dissertation proposes a holistic way of improving remote operations for offshore wind farms by using data integration. Particularly, semantics and integration aspects of data integration are investigated. The research looks at both theoretical foundations and practical implementations.
As the outcome of the research, a framework for data integration of offshore wind farms has been developed. The framework consists of three main components: the semantic model, the data source handling, and the information provisioning.
In particular, an offshore wind ontology has been proposed to explore the semantics of wind data and enable knowledge sharing and data exchange. The ontology is aligned with semantic sensor network ontology to support management of metadata in smart grids. That is to say, the ontology-based approach has been proven to be useful in managing data and metadata in the offshore wind and in smart grids.
A quality-based approach is proposed to manage, select, and provide the most suitable data source for users based upon their quality requirements and an approach to formally describing derived data in ontologies is investigated.
Kandidaten: Trinh Hoang Nguyen was born in Vietnam, in 1985. He received the diploma in software engineering from Tomsk Polytechnic University, Russia in 2009. In 2010, he moved to Italy and worked as a research assistant at the University of Trento. From Dec 2010 to May 2014, he was a PhD student in ICT at University of Agder. He was a visiting scholar at Georgia Institute of Technology in Atlanta, USA in 2012 and Sapienza University of Rome, Italy in 2014. Since Aug 2014 he has joined POCS Caesar Association in Fornebu, Norway where he works as an IT Architect / Semantic Technology Specialist.
Prøveforelesning og disputas finner sted i Auditorium C2-040, Campus Grimstad. Dekan, professor Frank Reichert, leder disputasen.
Tid for prøveforelesning: Kl 10:00 fredag 28. november 2014
Oppgitt emne for prøveforelesning: "Data in public and private sectors: Comparison of issues, challenges, and risks"
Tid for disputas: Kl 12:00 fredag 28. november 2014
Tittel på avhandling: "OffshoreWind Data Integration".
Søk etter avhandlingen i AURA - Agder University Research Archive, som er et digitalt arkiv for vitenskapelige artikler, avhandlinger og masteroppgaver fra ansatte og studenter ved Universitetet i Agder. AURA blir jevnlig oppdatert.
Førsteopponent: Professor Dr. Asunción Gómez-Pérez, Departamento de Inteligencia Artificial; Universidad Politécnica de Madrid
Annenopponent: Jayantha Prasanna Liyanage, Center for Industrial Asset Management (CIAM), Faculty of Science and Technology, UiS
Bedømmelseskomitéen er ledet av professor Matthias Pätzold, UiA