A Data-Driven Framework for Electric Vehicle Charging Infrastructure Planning: Demand Estimation, Economic Feasibility, and Spatial Equity
電気自動車充電インフラ計画のためのデータ駆動型フレームワーク：需要推定、経済的実現可能性、空間的公平性 (AI 翻訳)
Mahmoud Shaat, Farhad Oroumchian, Zina Abohaia, M. Barachi
🤖 gxceed AI 要約
日本語
本研究は、アブダビにおける2050年までのEV充電インフラ需要を、2つのシナリオ（Progressive・Thriving）に基づいて推定するフレームワークを開発。Thrivingシナリオではより高い投資が必要だが、利用率と空間的公平性が向上し、長期的なリターンが高い。現在のコミュニティの17.6%しかインフラ基準を満たしておらず、系統拡大と公平な配備の必要性を強調。
English
This study develops a scenario-based framework to estimate EV charging infrastructure needs in Abu Dhabi through 2050, comparing two adoption pathways. The Thriving scenario, despite higher capital investment, yields better utilization, spatial equity (Gini=0.27), and long-term returns. Only 17.6% of communities meet readiness thresholds, highlighting the need for coordinated grid expansion and equitable deployment.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本でもEV普及と充電インフラ整備が進む中、本論文のシナリオベースの需要推定・経済性評価手法は、特に地域格差を考慮した計画に参考となる。空間的公平性をGini係数で定量化するアプローチは、日本の地方部への充電網設計にも応用可能。
In the global GX context
For global audiences, this paper offers a data-driven framework for EV charging infrastructure planning that balances economic efficiency and spatial equity in an emerging low-carbon city context. It contributes to the literature on sustainable transport infrastructure in the Middle East and supports the UAE's Net Zero 2050 target.
👥 読者別の含意
🔬研究者:Researchers can adopt the scenario-based modeling framework for spatial equity analysis in EV infrastructure planning.
🏢実務担当者:Practitioners can use the methodology to assess charging demand and economic feasibility for urban and rural deployment.
🏛政策担当者:Policymakers should note the importance of coordinated grid expansion and equitable deployment strategies highlighted by the low readiness baseline.
📄 Abstract（原文）
The accelerating global transition to electric mobility demands data-driven infrastructure planning that balances technical, economic, and spatial considerations. This study develops a scenario-based demand and economic modeling framework to estimate electric vehicle (EV) charging infrastructure needs across Abu Dhabi’s urban and rural regions through 2050. Two adoption pathways, Progressive and Thriving, were constructed to capture contrasting policy and technological trajectories consistent with the UAE’s Net Zero 2050 targets. The model integrates regional travel behavior, energy consumption (0.23–0.26 kWh/km), and differentiated charging patterns to project EV penetration, charging demand, and economic feasibility. Results indicate that EV stocks may reach 750,000 (Progressive) and 1.1 million (Thriving) by 2050. The Thriving scenario, while demanding greater capital investment (≈108 million AED), yields higher utilization, improved spatial equity (Gini = 0.27), and stronger long-term returns compared to the Progressive case. Only 17.6% of communities currently meet infrastructure readiness thresholds, emphasizing the need for coordinated grid expansion and equitable deployment strategies. Findings provide a quantitative basis for balancing economic efficiency, spatial equity, and policy ambition in the design of sustainable EV charging networks for emerging low-carbon cities.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/wevj17010042first seen 2026-05-15 17:53:52
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。