الفهرس 
Title : Framework for planning of ev charging infrastructure: a data-driven approach
SummaryOnly 14 pages are availabe for public view
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Abstract
Electric vehicles charging infrastructure (EVCI) is a key enabler of e-mobility rollout. With the wide implementation of e-mobility; it is of due importance to investigate the lessons learnt from EVCI installation across cities and particularly the impact of cities’ characteristics on planning for EVCI. City characteristics (like area, population, road network topology, urban areas connectivity, congestion, ambient temperature, and prevalent degree of electrification) are related to EVCI installation. This research addresses a multi-dimensional serviceability analysis of EVCI in 25 cities across the globe targeting service coverage, service radius, service capacity, and standard evaluation metrics. City comparisons, market patterns, and worldwide trends have been deduced and geo-spatially analyzed. Other factors related to the e-mobility business market (such as: charging infrastructure incentives and market categories of consumers) have resulted in - along with cities’ characteristics - different levels of success across the studied cities. This research contributes a data-driven approach to unveil much of those complex patterns associated with planning for EVCI including 1) coverage index vs annual sales, 2) density distribution for the number of charging pools/1km2 covered cell, 3) structure of EVCI covered areas in relation to city urban fabric, 4) analogy of demand-driven density distribution of EVCI locations, 5) charging pools/million population in relation to the type of parking citizens have access to and drivers’ charging preferences 6) effect of road network topology on the service radius of EVCI 7) effect of prevalent degree of electrification and traffic conditions on the coverage index and service radius of EVCI, 8) effect of ambient temperature on the service radius of EVCI; while highlighting varying degrees of infrastructure investment by comparing the patterns of Oslo, Paris, Amsterdam, and Shenzhen. To that end, a framework for EVCI planning is established based on these lessons. The proposed framework is divided into a government-targeted-driven framework for cities with explicit targets of e-mobility implementation, and another international-best-practices-driven framework for cities paving their way out at early market stages. The employed planning tools are not only applicable for design approaches but also allow for serviceability assessment by 1) quantifying EV served demand approximately represented by EV sales, and 2) the demand-driven power-law distribution of EVCI locations. The main outputs of the proposed framework are: 1) EVCI candidate locations, 2) EVCI level/type (slow, fast), 3) EVCI capacity (number of chargers), and 4) Served EV demand. Operational recommendations including demand-responsive programs are also discussed. The proposed international-best-practices-driven framework is demonstrated in a case study; the New Administrative Capital of Egypt and a phased plan for installing EVCI from 2022 to 2027 is developed to provide multiple design alternatives for decision-makers.