混在車両下における低炭素志向のマクロ・メソ連成動的最適交通電力潮流
Low Carbon Oriented Macro-Meso Coupled Dynamic Optimal Traffic Power Flow under Mixed Vehicles (原題)
Mofei Zhou, Haoyuan Yan, Tianyang Zhao, Gengfeng Li, Zhaohong Bie
🤖 gxceed AI 要約
日本語
EVと内燃機関車が混在する都市連系交通電力システム（UCTPS）の低炭素運用を最適化するため、動的最適交通電力潮流（DOTPF）問題を定式化した。混在車両向けの時空間ネットワークと待ち行列機構を組み込み、経路問題と動的交通配分、炭素制約付き最適電力潮流を統合する。IEEE30母線とSioux Falls網の検証で、EV普及率の上昇は炭素削減に寄与するが、過度な普及は電力系統の混雑を悪化させ削減効果を減じることが示された。
English
This study formulates a Dynamic Optimal Traffic-Power Flow (DOTPF) problem to optimize low-carbon operation of urban coupled transportation-power systems with mixed EV and combustion fleets. It integrates a time-space network with queuing, heterogeneous vehicle routing, dynamic traffic assignment, and carbon-constrained optimal power flow. Simulations show rising EV penetration cuts carbon but excessive penetration worsens grid congestion, weakening reductions.
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
EV普及と系統混雑のトレードオフを定量化した点は、日本のEV普及政策・系統運用計画や自治体の脱炭素交通戦略に示唆を与える。炭素価格を内生化した枠組みはカーボンプライシング議論とも接続する。
In the global GX context
The paper links transport electrification with power-system carbon constraints, relevant to global EV transition and grid-integration debates. Its carbon-pricing-embedded optimization offers a modeling template for coupled sector decarbonization under ISSB-era transition planning.
👥 読者別の含意
🔬研究者:交通・電力連系の最適化モデリングと炭素制約の統合手法に関心のある研究者に有用。
🏢実務担当者:EV fleet導入や充電インフラ計画、系統混雑リスクを検討する企業の脱炭素戦略に示唆。
🏛政策担当者:EV普及率と系統容量のバランス、炭素価格設計を検討する政策担当者に参考となる。
📄 Abstract（原文）
ABSTRACT To optimize the integrated low-carbon operation of Urban Coupled Transportation Power Systems (UCTPS) accommodating mixed Electric Vehicle (EV) and Internal Combustion Vehicle (ICV) fleets, we investigate critical factors governing traffic-power flow interactions—including congestion conditions, carbon emission constraints, EV penetration levels, and carbon emission pricing. A Dynamic Optimal Traffic-Power Flow (DOTPF) problem is formulated for heterogeneous fleets using novel Time-Space Network (TSN) framework explicitly designed for mixed fleets, which incorporates integrated queuing mechanisms. This framework rigorously models sequential state transitions of both EV and ICV fleets, capturing their distinct behavioral dynamics. The formulation integrates a vehicle routing problem for heterogeneous fleets into a Dynamic Traffic Assignment Problem (DTAP), and a dynamic security-constrained Optimal Power Flow (OPF) model with carbon emission objectives is developed, coordinating thermal unit commitment and energy storage dispatch to reduce carbon emissions and generation costs. The multi-objective DOTPF is reformulated as a multi-objective convex mixed-integer quadratic programming model. Simulation studies on a coupled IEEE 30-bus power network and Sioux Falls transportation network validate the framework’s efficacy. Results show that increasing the penetration level of EVs can achieve carbon reduction in the UCTPS, however, an excessively high EV penetration level may exacerbate line congestion in the power system, thereby rendering the carbon reduction effect less significant.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.spes.2026.07.002first seen 2026-09-24 04:42:05
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