Modelling of Active Distribution Networks for Power System Restoration Studies

Lammert, Gustav; Klingmann, Alexander; Hachmann, Christian; Lafferte, Darío; Becker, Holger; Paschedag, Tina; Heckmann, Wolfram; Braun, Martin

doi:10.1016/j.ifacol.2018.11.762

Cited by 8 publications

(5 citation statements)

References 4 publications

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“…The inverter coupled generation is modeled according to [31,32], implementing the active power frequency, i.e., P( f ) and reconnection behaviour of the pertinent German grid code [33] for high-voltage connected inverter coupled generation. With respect to the reconnection gradient and P( f )-characteristics, this is equivalent to the behaviour of generation connected at lower voltage levels [34,35].…”

Section: Renewable Generation Modelmentioning

confidence: 99%

“…The CLPU of the load is considered as described above for a range of parameters as described in Section 6.2. The resulting power values are multiplied by a voltage and frequency dependency as follows according to [31,36]. These dependencies represent a combination of loads with very different voltage and frequency dependencies such as power electronically coupled loads, resistive loads, directly coupled asynchronous machines, etc.…”

Section: Load Modelmentioning

confidence: 99%

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Cold Load Pickup Model Adequacy for Power System Restoration Studies

2022

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When a grid section is re-energized after an interruption, the load behaviour can be significantly different from normal operation. In this manuscript, the impact of the phenomenon—known as cold load pickup—is investigated by evaluating 31 time series measured after network outages in Austria and Germany. Its impact on power system restoration and the adequacy of the most common type of simplified model for such investigations is assessed by the time domain simulation of a restoration setting involving the parallel operation of conventional and renewable generation. Parameter distributions are provided for the exponential decay and the delayed exponential decay model with the aim of facilitating meaningful consideration of the phenomenon in time domain simulations of power system restoration. The benefits and limitations of these models are assessed by comparison of time domain simulation results using either the normalized raw data, an exponential decay model or a step-wise active power chance to reflect load behaviour. It is shown that using an exponential decay model leads to higher fidelity of simulation results with respect to the resulting steady-state active power sharing among generators than just applying a step-wise power change in the simulation.

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Section: Renewable Generation Modelmentioning

confidence: 99%

Section: Load Modelmentioning

confidence: 99%

Cold Load Pickup Model Adequacy for Power System Restoration Studies

2022

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“…From this standpoint, in [15] a model which considers both the CLPU effect and the DG plants disconnection as a function of the frequency is described. The contribution is valuable, but several aspects are neglected, such as the involving of DG in Primary Frequency Regulation (PFR) service and the possibility of having a mix of different load categories supplied by a DN.…”

Section: A Literature Reviewmentioning

confidence: 99%

A Novel Dynamic Load Modeling for Power Systems Restoration: An Experimental Validation on Active Distribution Networks

et al. 2022

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In this paper, a novel approach to assess the power demand of distribution networks during a restoration process following an outage is presented. The possibility of correctly estimating such power demand represents a very important support in the choice and management of reliable restoration paths which significantly contributes to increase the resilience of the power system. In fact, due to the ever-growing penetration of renewable energy sources in the worldwide networks, electrical systems are often pushed to operate closer to their design limits and so, in particular conditions, black outs can be more frequent compared to the past. In this context, the aim of this work is to develop a general expression which can consider and represent all the key elements which affect the active and reactive power demand of distribution grids during the restoration process. The proposed method considers also the relationship between distributed generation and frequency behaviour in the power demand estimation. This aspect is generally neglected in literature although it has a significative impact. The effectiveness of the present approach is experimentally demonstrated on field. More specifically, the developed tool is applied to estimate the power demand of two real distribution networks and the tool results are compared with on-field recordings. This comparison demonstrates that the proposed approach represents a promising tool which, together with the restoration tests, could be an important ally in the design and management of the restoration plan of electrical networks.INDEX TERMS Load modelling, Cold load pick up, Black start, power system restoration, modelling of distributed generation.

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“…However, if shortterm dynamics are of concern, it is also reasonable to model the inrush currents of transformers and/or the starting transients from induction motors explicitly. Furthermore, if there is a relevant penetration of distributed generation, its reconnection behaviour should be modelled explicitly [26,27].…”

Section: Modelling Of Clpumentioning

confidence: 99%

“…A load feeder of 20 MW nominal active power and a fixed cos φ of 0.9, corresponding to a nominal apparent power of 20 MW/0.9 = 22.2 MVA, was added to bus 1, which is connected at the 20 kV level, via a transformer equipped with an automatic tap changer, to a 130 kV subtransmission bus in the central area of the power system. The load model used is described in [26] and implements the exponential CLPU curve described in Section 2 along with voltage and frequency dependency of α = 0.62 and k p f = 1(%/Hz) of active and β = 0.96 and k q f = 1(%/Hz) of reactive power, respectively. The initial overshoot a of the CLPU is set to 100%.…”

Section: Test Systemmentioning

confidence: 99%