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. 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.
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Published on 01/01/2020
Volume 2020, 2020
Licence: CC BY-NC-SA license
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