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Vehicle Smart Grid Allocation using Multi-Agent Systems sensitive to Irrational Behavior and Unstable Power Supply

机译:车辆智能电网分配使用对非理性行为和不稳定电源敏感的多种子体系统

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As the number of electric vehicles increases, the access to public charging points along an electric grid can become congested. This study proposes a multi-agent solution to solve the task of electric vehicle allocation on smart grid chargers sensitive to the vehicle's base, destination and battery profile for charging convenience. In particular, we assess robustness against irrational vehicle behavior and unstable power supply. The proposal follows a design science research methodology. We consider an unstable power source and agents with emotional behaviours, such as irrational preconception of stations and individual perceptions experience. Different environments are simulated with an automatic topology engine extraction grounded on real world urban scenarios. This tool may be helpful to aid planning by simulating station distribution in a parameterizable way. The simulation results allow for a preview of the architecture performance at a system wide level considering several scenarios with distinct characteristics. The smart grid consistently manages energy delivery, leaving no cars uncharged.
机译:随着电动车辆的数量增加,沿电网的公共充电点的访问可能变得拥挤。本研究提出了一种多种子体解决方案,以解决对车辆基地,目的地和电池轮廓敏感的智能电网充电器上的电动车辆分配任务,以便为便利性充电。特别是,我们评估对非理性车辆行为和不稳定电源的鲁棒性。该提案遵循设计科学研究方法。我们考虑一个不稳定的电源和具有情感行为的代理,例如非理性的站点,以及个人观念体验。通过在现实世界城市场景的自动拓扑引擎提取基础上模拟不同的环境。通过以可参数化方式模拟站分布,该工具可以有助于帮助规划。模拟结果允许在系统广泛级别预览架构性能,考虑有几种具有不同特性的场景。智能电网一直管理能量交付,留下没有速度的汽车。

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