Abstract This paper proposes a stochastic framework to augment the integration of variable renewable energy sources (VRESs) in power system scheduling. In this way, the fast-response capability of gas-fired generator units (GFGUs) and vehicle-to-grid (V2G) capability of electric vehicles (EVs) can play important roles in large-scale integration of VRESs. However, the growth of GFGUs utilization can increase the grade of interdependency between power and natural gas systems. In this condition, the power system tends to demand more reliability and flexibility from the natural gas system, which creates new challenges in power system scheduling. The likely significant growth of EVs can solve this challenge and reduce the correlation between power and natural gas systems, bringing new opportunities for power system scheduling. However, a considerable literature in the field of operation of GFGUs and EVs has only focused on using the hourly discrete time model (HDTM). Undoubtedly, the major limitation of HDTM is its inability to handle the fast sub-hourly dispatch of GFGUs and energy storage capability of EVs. Accordingly, in this paper, this limitation has been solved by the operation of both energy systems with a continuous time model (CTM). The reliability test system with a ten-node gas transmission system has been analysed to show the effectiveness of the proposed problem.

中文翻译：

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基于连续时间模型方法的电力和天然气系统的合作，包括电动汽车和可变的可再生能源

摘要 本文提出了一个随机框架来增加电力系统调度中可变可再生能源（VRES）的整合。这样，燃气发电机组 (GFGU) 的快速响应能力和电动汽车 (EV) 的车辆到电网 (V2G) 能力可以在 VRES 的大规模集成中发挥重要作用。然而，GFGU 利用率的增长可以提高电力和天然气系统之间的相互依赖程度。在这种情况下，电力系统往往要求天然气系统具有更高的可靠性和灵活性，这给电力系统调度带来了新的挑战。电动汽车的显着增长可以解决这一挑战并减少电力和天然气系统之间的相关性，为电力系统调度带来新的机会。然而，GFGU 和 EV 运行领域的大量文献仅关注使用每小时离散时间模型 (HDTM)。毫无疑问，HDTM 的主要局限在于无法处理 GFGU 的快速亚小时调度和电动汽车的储能能力。因此，在本文中，通过使用连续时间模型 (CTM) 运行两个能源系统，这一限制已得到解决。已经对具有十节点输气系统的可靠性测试系统进行了分析，以显示所提出问题的有效性。通过使用连续时间模型 (CTM) 运行两个能源系统，这一限制已得到解决。已经对具有十节点输气系统的可靠性测试系统进行了分析，以显示所提出问题的有效性。通过使用连续时间模型 (CTM) 运行两个能源系统，这一限制已得到解决。已经对具有十节点输气系统的可靠性测试系统进行了分析，以显示所提出问题的有效性。