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首页> 外文期刊>IEEE Transactions on Industry Applications >Approach to Enhance the Robustness on PMU-Based Power System Dynamic Equivalent Modeling
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Approach to Enhance the Robustness on PMU-Based Power System Dynamic Equivalent Modeling

机译:基于PMU的电力系统动态等效建模的鲁棒性增强方法

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摘要

Due to the maturity of wide area measurement technology, phasor measurement unit (PMU)-based dynamic equivalent modeling method (PDM) has been wildly used in large-scale power system modeling. However, traditional "event-based" PDM equivalent model may face serious robustness issues, such as although derived equivalent models show the good ability on reproduction of the system behaviors under recorded events where they derived from, they may not work well for other possible disturbances. In this article, to improve the robustness of equivalent model, a novel method on dynamic equivalent modeling of power system is proposed. Based on the result of coherency identification, generators inside the equivalent system can be aggregated into different coherent subgroups and represented by multimachine equivalent model. Key parameter selection, which can shrink the scale of identified parameters, is designed to avoid multiple solutions of the equivalent model. Moreover, a multiobjective parameter identification algorithm is developed to fully consider the PMU measurements in different system events. In addition, hybrid dynamic simulation is performed so that each equivalent submodel can be identified separately. Finally, the effectiveness of the proposed method is verified in an actual power grids in China.
机译:由于广域测量技术的成熟,基于相量测量单元(PMU)的动态等效建模方法(PDM)已广泛用于大规模电力系统建模中。但是,传统的“基于事件”的PDM等效模型可能会遇到严重的鲁棒性问题,例如,尽管派生的等效模型显示出在记录事件源自的系统行为下具有良好的系统行为再现能力,但它们可能无法很好地应对其他可能的干扰。为了提高等效模型的鲁棒性,提出了一种新的电力系统动态等效建模方法。根据相干性识别的结果,等效系统内部的生成器可以聚合为不同的相干子组,并由多机等效模型表示。关键参数选择可以缩小已识别参数的规模,旨在避免等效模型的多个解决方案。此外,开发了一种多目标参数识别算法,以充分考虑不同系统事件中的PMU测量。另外,执行混合动态仿真,以便可以分别识别每个等效子模型。最后,在中国实际电网中验证了该方法的有效性。

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