Primjena GIS-a u određivanju optimalnih lokacija punjača za električna vozila

master's thesis

• Title (english): The Application of GIS in Determining Optimal Locations for Electric Vehicle Chargers
• Author: Josip Bolješić
• Mentor: Mario Miler (mentor); MBZ: 296874
• Mentor: Dino Dobrinić (komentor); MBZ: 358296
• Committee member: Damir Medak (predsjednik povjerenstva)
• Committee member: Mario Miler (član povjerenstva)
• Committee member: Luka Rumora (član povjerenstva)
• Granter: University of Zagreb; Faculty of Geodesy; (Institute of Geomatics); (Chair of Geoinformatics); Zagreb
• Defense date and country: 2024-06-21, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Geodesy; Geomatics

Abstract

Električna vozila su vozila koja koriste električnu energiju umjesto fosilnih goriva za pogon, čime smanjuju emisije štetnih plinova i doprinose održivijem životnom stilu. Pad cijena električnih vozila i napredak u tehnologiji baterija doprinijeli su njihovoj sve većoj popularnosti. Nova generacija ovakvih vozila nudi vozačima veću autonomiju i brže vrijeme punjenja, što dodatno potiče njihovu upotrebu. Cilj ovog projekta je generirati nove optimalne lokacije za punionice električnih vozila (EV) koristeći Python 3.8.10 i QGIS 3.16.14. Projekt će se temeljiti na kodu koji je napisao Obed Sims, a može se pronaći na sljedećem linku: https://towardsdatascience.com/where-should-we-be-placing. Korištenjem Pythona i alata QGIS-a, projekt ima za cilj analizirati različite faktore kao što su gustoća prometa, potražnja za punjenjem i dostupnost potencijalnih lokacija poput parkirališta. Ti faktori će se uzeti u obzir pri identifikaciji optimalnih lokacija za nove punionice korištenjem MILP metode programirane u Pythonu. Generirane lokacije će maksimizirati iskoristivost punionica i pružiti korist lokalnoj zajednici. Gradovi poput Zagreba prepoznaju važnost razvoja infrastrukture punionica kako bi podržali rast električne mobilnosti. Ulaganja u mrežu brzih punionica duž glavnih prometnih koridora i na strateškim lokacijama unutar grada pomažu u smanjenju prepreka za vlasnike električnih vozila i potiču prijelaz na održivije oblike prijevoza.

Abstract (english)

Electric vehicles are vehicles that use electric power instead of fossil fuels for propulsion, thereby reducing harmful emissions and contributing to a more sustainable lifestyle. The decrease in the cost of electric vehicles and advancements in battery technology have contributed to their increasing popularity. The new generation of these vehicles offers drivers greater autonomy and faster charging times, further promoting their usage. The aim of this project is to generate new optimal locations for electric vehicle charging stations (EV) using Python 3.8.10 and QGIS 3.16.14. The project is based on the code written by Obed Sims, which can be found at the following link: https://towardsdatascience.com/where-should-we-be-placing. By utilizing Python and the QGIS tools, the project aims to analyze various factors such as traffic density, charging demand and availability of potential locations as parking lots. These factors will be considered in identifying optimal locations for new charging stations by using MILP method programmed in Python. The generated locations will maximize the utilization of charging stations and provide benefits to the local community. Cities like Zagreb recognize the importance of developing charging infrastructure to support the growth of electric mobility. Investments in a network of fast charging stations along major traffic corridors and strategic locations within the city help reduce barriers for electric vehicle owners and encourage a transition to more sustainable forms of transportation.

• Keywords: električna vozila; punionica; Python 3.8.19; QGIS 3.16.14; MILP metoda
• Keywords (english): electric vehicles; charger; Python 3.8.19; QGIS 3.16.14; MILP method
• Language: croatian
• URN:NBN: urn:nbn:hr:256:142549
• Study programme: Title: Geodesy and Geoinformatics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka geodezije i geoinformatike (magistar/magistra inženjer/inženjerka geodezije i geoinformatike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-06-20 14:41:51