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doctoral thesis
Real-world data-driven decision support system for electric vehicle charging infrastructure development.
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:190341
Pevec, Dario
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Telecommunications

Institutional repository: FER Repository

Cite this document

Pevec, D. (2020). Real-world data-driven decision support system for electric vehicle charging infrastructure development. (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:190341

Pevec, Dario. "Real-world data-driven decision support system for electric vehicle charging infrastructure development.." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:190341

Pevec, Dario. "Real-world data-driven decision support system for electric vehicle charging infrastructure development.." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:190341

Pevec, D. (2020). 'Real-world data-driven decision support system for electric vehicle charging infrastructure development.', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 23 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:190341

Pevec D. Real-world data-driven decision support system for electric vehicle charging infrastructure development. [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 November 23] Available at: https://urn.nsk.hr/urn:nbn:hr:168:190341

D. Pevec, "Real-world data-driven decision support system for electric vehicle charging infrastructure development.", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:190341

Metadata
TitleReal-world data-driven decision support system for electric vehicle charging infrastructure development.
Title (croatian)Sustav za potporu odlučivanju o razvitku infrastrukture punionica za električna vozila zasnovan na podacima iz stvarnog svijeta.
AuthorDario Pevec
MentorVedran Podobnik (mentor)
Committee memberVedran Podobnik (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Telecommunications)
Zagreb
Defense date and country2020, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Information Systems
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Trends show that the popularity of electric vehicles (EVs) has increased significantly in recent years, bringing about changes not only in the transport industry but also in the economy and society. There are many obstacles for EVs to reach their full market potential, among which the underdevelopment of the charging station infrastructure is clearly highlighted. The main objective of this PhD thesis is to provide a data-driven approach for an intelligent management of the infrastructure of EV charging stations using data science methods in the interdisciplinary field of sustainable transport, business and energy informatics. This dissertation answers three research questions: (i) "Where should a provider of EV charging station infrastructure install / remove / relocate a charging station?", (ii) "How can the infrastructure management approach be determined in view of the development of the existing infrastructure?" and (iii) "How can the range anxiety in the use of electric vehicles be defined and measured?" using practical methods. The scientific contributions of the dissertation are: a model and computing system based on real-world data intended for the management of charging station infrastructure for electric vehicles, and a techno-economic framework that allows a technological action plan and the analysis of what-if scenarios for the development of charging stations for electric vehicles.
Abstract (croatian)
Trendovi pokazuju kako se popularnost električnih vozila (EV) značajno povećala unazad par godina, uzrokovajući pritom promjene ne samo u transportnoj industriji već u poslovanju i društvu također. Postoje mnoge prepreke kako bi EV-ovi dosegli svoj potpuni tržišni potencijal među kojima se značajno ističe nerazvijenost infrastrukture punionica. Glavni cilj ove doktorske disertacije jest koristeći metode znanosti o podacima nad interdisciplinarnim područjem održivog transporta, ekonomije i energetske informatike, pružiti pristup temeljen na podacima za pametno upravljanje strukturom punionica EV-ova. Ova doktorska disertacija odgovara na tri istraživačka pitanja: (i) "Gdje pružatelj infrastrukture punionica za EV-ove treba postaviti/maknuti/premjestiti punionicu?", (ii) "Kako odrediti pristup upravljanja infrastrukturom s obzirom na razvijenost postojeće infrastructure?" te (iii) “Kako definirati I izmjeriti anksioznost dometa prilikom korištenja električnih vozila?” koristeći metodologije bazirane na podacima iz stvarnoga svijeta. Znanstveni doprinosi disertacije su: model i računalni sustav zasnovan na podacima namijenjen upravljanju infrastrukturom punionica za električna vozila te tehnološko-ekonomski radni okvir koji omogućuje tehnološki akcijski plan i analizu što-ako scenarija za razvoj infrastrukture punionica električnih vozila.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:168:190341
Promotion2020
Study programmeTitle: Computer Science
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti (Doktor znanosti)
Type of resourceText
Extent159 str.
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2020-11-19 11:02:35