城市电力-天然气-交通综合网络的优化路由框架

IF 4.6 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Open Journal of Intelligent Transportation Systems Pub Date : 2024-03-27 DOI:10.1109/OJITS.2024.3380569
Mohammad Jadidbonab;Hussein Abdeltawab;Yasser Abdel-Rady I. Mohamed
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引用次数: 0

摘要

本文开发了一个基于风险规避的框架,用于优化电力、燃气和交通(PGT)综合网络的运营,并将其应用于埃德蒙顿市中心的一个典型 PGT 网络,埃德蒙顿是加拿大向电动汽车和可持续城市出行方式过渡的前沿。开发的非概率框架为决策者提供了各种安全选项,以避免最坏情况的发生,促进社会和环境效益。不同能源系统的整合使运营商能够在设施停运等危急情况下采取最优策略,将系统维持在安全运行范围内,而无需采用昂贵的变通方法。所提出的算法和集成结构可以选择最佳行驶路线,最大限度地减少气体排放影响,并找到充电选项,减少电动汽车用户的出行时间。它还能缓解分布式发电机断电和道路关闭带来的挑战。在不同案例研究和埃德蒙顿太阳能 PGT 网络上实施该框架的数值结果表明了其可行性和有效性。
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An Optimal Routing Framework for an Integrated Urban Power–Gas–Traffic Network
This paper develops a risk-averse-based framework for optimizing the operation of an integrated power, gas, and traffic (PGT) network with an application to a typical PGT network in downtown Edmonton, the forefront of Canada’s transition to electric vehicles and sustainable urban travel options. The developed non-probabilistic framework provides decision-makers with various secure options to avoid worst-case scenarios and promote social and environmental benefits. The integration of different energy systems allows operators to pursue optimal strategies in critical situations, such as facility outages, maintaining the system within a secure operational range without resorting to expensive workarounds. The proposed algorithm and integrated structure can select optimal travel routes to minimize gas-emission effects and locate charging options to reduce electric vehicle users’ travel time. It can mitigate challenges posed by distributed generator outages and roadway closures. The numerical results from implementing the framework on different case studies and the solar-based PGT network of Edmonton indicate its feasibility and effectiveness.
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