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Novel Fault Models for Electronically Coupled Distributed Energy Resources and Their Laboratory Validation

机译:电子耦合分布能源资源的新型故障模型及其实验室验证

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摘要

In this paper, novel models for electronically coupled distributed energy resources (ECDERs) for online fault calculations of large-scale systems are proposed. ECDERs have different fault responses than traditional synchronous and induction (AC) machines, and generally accepted models for these emerging DERs do not exist. The deployment of ECDERs is constantly increasing worldwide and there is an urgent need for developing appropriate models for fault calculations. In order to have fast calculations, applicable to large-scale systems, the dynamic behavior of traditional AC machines have been approximated in three steady state time-periods (sub-transient, transient, and steady-state). Accordingly, the online fault calculations of large-scale systems have been conducted for these three periods. To simulate the ECDERs' dynamic behavior, and develop models that are compliant with traditional fault calculations, fault models of ECDERs in the sub-transient, transient, and steady-state periods are proposed, with a short peak current period included in the proposed models during the sub-transient period. To validate the proposed models, they are integrated into recently developed online fault calculations, and tested on various large-scale systems. Results from computer simulations are compared with results obtained using state-of-the-art laboratory equipment, as well as with relevant reports on fault current contributions of ECDERs. The results match very well, further validating the proposed models.
机译:在本文中,提出了用于大规模系统的在线故障计算的电子耦合分布能源(eCDERS)的新型模型。 eCDERS比传统的同步和感应(AC)机器具有不同的故障响应,并且通常不存在这些新兴DER的接受模型。 ECDERS的部署在全球范围内不断增加,并且迫切需要开发适当的故障计算模型。为了具有快速的计算,适用于大规模系统,传统交流机的动态行为在三个稳态时间周期(子瞬态,瞬态和稳态)中近似。因此,已经在这三个时期进行了大规模系统的在线故障计算。为了模拟eCDERS的动态行为,并开发符合传统故障计算的模型,提出了子瞬态,瞬态和稳态期间的eCDERS的故障模型,其中包括拟议模型中的短峰值当前周期在子瞬态期间。为了验证所提出的模型,它们将集成到最近开发的在线故障计算,并在各种大规模系统上进行测试。将计算机模拟的结果与使用最先进的实验室设备获得的结果进行了比较,以及关于越过者故障当前贡献的相关报告。结果非常好,进一步验证了所提出的模型。

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