arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2103.14820eess.SYcs.SY
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基于在线反馈的不平衡配电网线性化潮流模型

An Online Feedback-Based Linearized Power Flow Model for Unbalanced Distribution Networks

Rui Cheng, Zhaoyu Wang, Yifei Guo

摘要:

潮流模型的非线性、非凸性和相位耦合性给不平衡配电网的分析和优化带来了挑战。为了解决这一问题,本文提出了一种基于在线反馈的不平衡配电网的线性化潮流模型的Y形连接和三角形连接的负荷。基于在线反馈的线性化模型基于支路流模型的一阶泰勒展开,并且通过利用在前一时间步长处的瞬时测量电压和负载消耗经由在线反馈来更新模型参数。它的闭环性质可以渐近地缓解模型失配,从而使其具有良好的性能。此外,利用不平衡辐射状配电网的接线结构,我们提出了一个统一的矩阵向量紧凑形式的线性化潮流模型。最后,通过IEEE 123节点系统的数值算例验证了该模型的有效性和优越性。一个简单的最优潮流的情况下,也提供了说明在线反馈为基础的线性化模型的应用。

英文摘要:

The non-linearity and non-convexity of power flow models and the phase coupling challenge the analysis and optimization of unbalanced distribution networks. To tackle the challenges, this paper proposes an online feedback-based linearized power flow model for unbalanced distribution networks with both wye-connected and delta-connected loads. The online feedback-based linearized model is grounded on the first-order Taylor expansion of the branch flow model, and updates the model parameters via online feedback by leveraging the instantaneous measured voltages and load consumption at the previous time step. Its closed-loop nature can asymptotically mitigate the model mismatch, thus lending itself to a good performance. In addition, exploiting the connection structure of unbalanced radial distribution networks, we provide a unified matrix-vector compact form of the proposed linearized power flow model. Finally, the numerical tests on the IEEE 123-bus test system validate the effectiveness and superiority of the proposed model. A simple optimal power flow case is also provided to illustrate the application of the online feedback-based linearized model.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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