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Implementation of Temporal Parallelization for Rapid Quasi-Static Time-Series (QSTS) Simulations

机译:快速准静态时间序列(QSTS)模拟的时间并行化的实现

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Quasi-static time-series (QSTS) analysis of distribution systems can provide critical information about the potential impacts of high penetrations of distributed and renewable resources, like solar photovoltaic systems. However, running high-resolution yearlong QSTS simulations of large distribution feeders can be prohibitively burdensome due to long computation times. Temporal parallelization of QSTS simulations is one possible solution to overcome this obstacle. QSTS simulations can be divided into multiple sections, e.g. into four equal parts of the year, and solved simultaneously with parallel computing. The challenge is that each time the simulation is divided, error is introduced. This paper presents various initialization methods for reducing the error associated with temporal parallelization of QSTS simulations and characterizes performance across multiple distribution circuits and several different computers with varying architectures.
机译:配电系统的准静态时间序列(QSTS)分析可以提供有关分布式和可再生资源(如太阳能光伏系统)高渗透率潜在影响的重要信息。但是,由于计算时间长,因此对大型配电馈线进行为期一年的高分辨率QSTS仿真可能会非常繁重。 QSTS仿真的时间并行化是克服这一障碍的一种可能解决方案。 QSTS模拟可以分为多个部分,例如分成一年中的四个相等部分,并与并行计算同时解决。挑战在于,每当模拟被分割时,都会引入误差。本文提出了各种初始化方法,以减少与QSTS仿真的时间并行化相关的误差,并描述跨多个配电电路和具有不同体系结构的几台不同计算机的性能。

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