Management and coordination charging of smart park and V2G strategy based on Monte Carlo algorithm

M. Aryanezhad, E. Ostadaghaee, M. Joorabian
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引用次数: 22

Abstract

Charging of plug-in-hybrid-electric vehicles (PHEVs) may adversely affect electric grid reliability because a large amount of additional electrical energy is required to charge the PHEVs. In this paper, a comprehensive method to evaluate the system reliability concerning the stochastic modeling of PHEVs, renewable resources, availability of devices, etc. is proposed. This method, which consists of managed charging and vehicle-to-grid (V2G) scenarios, can be practically implemented in smart grids because the bidirectional-power-conversion technologies and two-way of both the power and data are applicable. The results showed that the smart grid's adequacy was jeopardized by using the PHEVs without any managed charging schedule. The sensitivity analyses results illustrated that by using the management scenarios, not only did the PHEVs not compromise the system reliability, but also in the V2G scenario acted as storage systems and improved the well-being criteria and adequacy indices.
基于蒙特卡罗算法的智慧公园管理与协调收费及V2G策略
插电式混合动力汽车(phev)的充电可能会对电网的可靠性产生不利影响,因为phev充电需要大量额外的电能。本文提出了一种综合考虑插电式混合动力汽车随机建模、可再生资源、设备可用性等因素的系统可靠性评估方法。该方法由管理充电和车辆到电网(V2G)场景组成,由于双向功率转换技术和功率和数据的双向适用,可以在智能电网中实际实施。结果表明,在没有管理充电计划的情况下使用插电式混合动力车会影响智能电网的充分性。灵敏度分析结果表明,在V2G管理场景下,插电式混合动力车不仅不影响系统可靠性,而且在V2G场景下起到了存储系统的作用,提高了健康标准和充分性指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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