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Adaptive Load Shedding Method Based on Power Imbalance Estimated by ANN

机译:基于ANN估计的功率不平衡的自适应载荷脱落法

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A new adaptive load shedding method based on the artificial neural network (ANN) and power flow tracing is proposed in this paper. The ANN is used to estimate the total active power imbalance according to the time interval of frequency drop of the equivalent inertial center from the rated value to the threshold. Load frequency regulation factor and the load priority are incorporated into the power flow tracing method to choose locations of load shedding and determine the amount of load shedding of each load. The new method is tested in the 8-machine 36-bus system. The test results demonstrate that the active power imbalance estimated by the ANN is more accurate. Besides, the new load shedding algorithm can give priority to shedding the load with smaller load frequency regulation factor and protect important loads from being shed.
机译:本文提出了一种基于人工神经网络(ANN)和功率流程跟踪的新的自适应载荷脱落法。该ANN用于根据等效惯性中心的频率下降的时间间隔从额定值到阈值来估计总有效功率不平衡。负载频率调节因子和负载优先级被整合到电流跟踪方法中,以选择负载脱落的位置,并确定每个负载的负载脱落量。该方法在8台机36总线系统中进行了测试。测试结果表明,ANN估计的主动功率不平衡更准确。此外,新的负载脱落算法可以优先于负载频率调节因子的负载缩小负载,并保护重要载荷免受棚屋。

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