基于agent的电动汽车充电调度

Armin Ghasem Azar, R. Jacobsen
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引用次数: 5

摘要

电动汽车技术旨在减轻能源挑战对当前交通基础设施的负面影响。然而,整合大量这样的车辆会给电网带来显著的额外负荷,并可能使其过载。针对电动汽车充电调度问题,提出了一种分层事件驱动的多智能体系统框架。家庭代理与变电站代理协商时间旅行模式,以决定电动汽车何时应该充电。提出了一种可扩展的负荷调度算法,可以在不使用任何预测方法的情况下实时调度电动汽车的充电过程。它的目标是允许尽可能多的电动汽车运行,同时随着时间的推移,将它们的总充电能耗保持在与电价相关的连续阈值以下。仿真结果表明,该框架受益于充电的灵活性,降低了充电成本,并削去了电网的峰值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agent-based charging scheduling of electric vehicles
The electric vehicle technology intends to mitigate negative impacts of the energy challenge on the current transportation infrastructure. However, integrating a large number of such vehicles imposes a significant additional load to the grid and may overload it. This paper proposes a hierarchical event-driven multi-agent system framework for coordinated charging scheduling of electric vehicles. Household agents negotiate temporal travel patterns with substation agents to decide when electric vehicles should charge their batteries. A scalable load scheduling algorithm is proposed to schedule charging process of electric vehicles in real-time regardless of using any forecasting method. It aims to permit as many electric vehicles as possible to operate while keeping their aggregated charging energy consumption below continuous electricity-price-dependent thresholds over time. Simulations confirm that the framework benefits from charging flexibilities, reduces the charging cost, and shaves the grid's peak.
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