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Regression analysis of temporary over voltages during power system restoration

机译:电力系统恢复过程中临时过电压的回归分析

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Power system restoration is the process of re-energization of power system elements after a partial or a complete blackout situation. The decision regarding the energization of network lines is complex and time consuming in nature. To reduce the above complexity in power system restoration, the present research work develops a decision (s) regarding the re-energization of transmission lines. Initially the complex network is divided into Islands to enhance the speed and efficiency in the restoration process. Data Envelopment Analysis (DEA) approach is applied to test the bus system for finding out the most weighted corridor in order to prioritize those for energization from a complete black out situation. Further, Temporary Over Voltages (TOV) that are occurring during transformer energization in low load condition is estimated using MATLAB/Simulink and Artificial Neural Networks (ANNs). Regression analysis on these TOVs is done in evaluating the performance of forecasting tool. The proposed methods are applied to a complex network to demonstrate the performance. It is found that the proposed techniques are better and efficient alternative approaches in Isolating, Selection of Transmission corridors and determining the over voltages respectively rather than any other techniques and helps the power system planners to have a faster strategy for power system restoration.
机译:电力系统恢复是在部分或完全停电后,电力系统元素重新通电的过程。实际上,有关为网络线路通电的决定是复杂且耗时的。为了减少电力系统恢复中的上述复杂性,本研究工作制定了有关传输线重新通电的决策。最初,将复杂的网络划分为多个岛,以提高恢复过程的速度和效率。数据包络分析(DEA)方法用于测试总线系统以找出权重最大的走廊,以便从完全的停电情况中优先进行激励。此外,使用MATLAB / Simulink和人工神经网络(ANN)可以估算低负荷条件下变压器通电过程中出现的临时过电压(TOV)。这些TOV的回归分析是在评估预测工具的性能时进行的。所提出的方法被应用于复杂的网络以证明其性能。发现所提出的技术是隔离,选择输电通道和确定过电压的更好且有效的替代方法,而不是任何其他技术,并且可以帮助电力系统规划人员制定更快的电力系统恢复策略。

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