Transient selectivity for enhancing autonomous fault management in unearthed distribution networks with DFIG-based distributed generations

Elkalashy, Nagy I.; Kawady, Tamer A.; Ashmawy, Mohamed G.; Lehtonen, Matti

doi:10.1016/j.epsr.2016.05.017

Cited by 6 publications

(1 citation statement)

References 29 publications

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“…A general diagram of a DFIG is shown in Fig. 1 [7]. It can be seen that the DFIM has the mechanical power input in the rotor shaft and the stator is connected to a step-up transformer to transmit the generated power to the electrical network.…”

Section: General Description Of the D G Modelmentioning

confidence: 99%

The Detailed Doubly Fed Induction Wind Generator for Electromagnetic Transients Calculations and its Initialization in ATP

Venerdini

Mombello

2021

Preprint

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The Alternative Transients Program (ATP) is one of the most used electromagnetic transient programs due to its powerful modeling capability and versatility. However, it has limitations as regards the automatic initialization of power electronics devices and control systems. To overcome this drawback, a simple methodology is presented in this paper to initialize a detailed model of a doubly fed induction wind generator implemented in ATP. The methodology is based on the automatic initialization of this device and it is divided into two stages. The first one consists of offline calculations to obtain initial steady-state values of certain model variables and, in the second one, these results are used as ATP model parameters. The simulation is started by means of auxiliary switches also included in the model. To validate the methodology, the transient and steady-state behavior of 4 case studies was evaluated. The analysis of these results shows that the steady-state values calculated by ATP for t = 0 are the desired ones and the oscillograms present a steady-state condition. The proposed methodology makes it possible to accurately initialize a detailed DFIG-type generator model in ATP, without the need to sacrifice simulation time to wait for variables to reach a steady state.

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Section: General Description Of the D G Modelmentioning

confidence: 99%