2016
DOI: 10.1109/tpwrs.2015.2393813
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Systematic Determination of Discrepancies Across Transient Stability Software Packages

Abstract: Several transient stability software packages are widely used for power grid planning and operations. Prior research and software documentations have shown that packages can vary in the implementations of dynamic models, and hence could potentially yield different results for the same system simulation. This paper presents a systematic methodology to determine the sources of the discrepancies seen in results obtained from different transient stability packages. This methodology can be applied to various types … Show more

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Cited by 9 publications
(4 citation statements)
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References 16 publications
(18 reference statements)
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“…In this case, in RTDS, a distributed parameter model was used to have a more realistic system representation, while in DIgSILENT PowerFactory was used in the lumped parameters PI-model, because DIgSILENT PowerFactory does not support the use of the model of distributed parameters when a three-phase short-circuit is applied at the middle of the transmission line. On the other hand, in the second case study, the PI-model was used in both software; also, it was observed that despite the models used to represent the synchronous machines and their controllers Automatic Voltage Regulator (AVR), governors, and excitation systems) the same in both software, their implementations were slightly different, and this yielded different results for the same system under simulation [33,34]; for that reason, the controllers were tuned in DIgSILENT PowerFactory to obtain a similar behavior as RTDS and to be able to compare the obtained results. These changes were made to evaluate the robustness of the methodology for the inertia estimation.…”
Section: Methodology Evaluationmentioning
confidence: 99%
“…In this case, in RTDS, a distributed parameter model was used to have a more realistic system representation, while in DIgSILENT PowerFactory was used in the lumped parameters PI-model, because DIgSILENT PowerFactory does not support the use of the model of distributed parameters when a three-phase short-circuit is applied at the middle of the transmission line. On the other hand, in the second case study, the PI-model was used in both software; also, it was observed that despite the models used to represent the synchronous machines and their controllers Automatic Voltage Regulator (AVR), governors, and excitation systems) the same in both software, their implementations were slightly different, and this yielded different results for the same system under simulation [33,34]; for that reason, the controllers were tuned in DIgSILENT PowerFactory to obtain a similar behavior as RTDS and to be able to compare the obtained results. These changes were made to evaluate the robustness of the methodology for the inertia estimation.…”
Section: Methodology Evaluationmentioning
confidence: 99%
“…The proposed methodology is able to consider other tuning methods and additional transient stability metrics. Comparison among simulation results by different software is of interest, as well [39]. We will report these studies in future work.…”
Section: Discussionmentioning
confidence: 97%
“…However, the model contains nonlinear differential-algebraic equations, which are complicated and takes a long time to calculate, which is difficult to meet the requirements of online calculation (Liu et al, 2020(Liu et al, , 2019Alsafasfeh et al, 2019c,b). Artificial intelligence algorithms can establish the mapping relationship between data input and output through learning, and the calculation speed is fast, so it is used for transient stability assessment and avoid complex time-domain equation solving (Alsafasfeh et al, 2019a;Shakerighadi et al, 2020;Kang et al, 2017;Bhui and Senroy, 2017;Shiwei et al, 2019;Yousefian et al, 2017;Li et al, 2018a;Shetye et al, 2016). Literature (Hu et al, 2019) uses data preprocessing algorithms such as feature variable selection, cluster analysis, and maximum entropy discrete method to reduce the data dimension and then applies the association classification method for temporary stability evaluation.…”
Section: Introductionmentioning
confidence: 99%