Tian‐yu Zhang, En‐jian Yao, Yang Yang, Hong‐Ming Yang, Dong‐bo Guo, David Z. W. Wang
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引用次数: 0
Abstract
This study presents a novel multistage expressway fast charging station (EFCS) planning problem coordinated with the dynamic regional power structure (PS) transformation. Under the prerequisite of the EFCS network's sustainable operation, network accessibility, and orderly construction, a three‐step planning method oriented to the enhancement of energy saving and emission reduction (ESER) benefits and rationalization of facility utilization is developed: (i) EV‐expanded network, (ii) multiagent‐based dynamic traffic assignment (MA‐DTA), and (iii) deployment refinement. Embedding the MA‐DTA and customized refinement strategy into the iterative planning structure enables the integration of operations and planning of the EFCS network. A numerical experiment and an empirical study in the Shandong Peninsula urban agglomeration are conducted. It demonstrates that the method can find a high‐quality solution within acceptable computation time and is applicable to realistic large‐scale EFCS planning. The planning method can effectively play the role of economy and facility in inducing EV users' charging demands, thus enhancing the overall ESER benefits. The integration of operation and planning is proven effective in reasonably matching the supply and demand of facility service and charging loads in a full‐time period. Further, the multistage EFCS planning schemes during 2025–2045 are explored, and some insightful policy implications are revealed.
期刊介绍：
Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms.
Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.
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