Abstract
This paper presents an artificial intelligence application to measure switching overvoltages caused by shunt reactor energization by applying analytical rules. In a small power system that appears in an early stage of a black start of a power system, an overvoltage could be caused by core saturation on the energization of a reactor with residual flux. A radial basis function (RBF) neural network has been used to estimate the overvoltages due to reactor energization. Equivalent circuit parameters of network have been used as artificial neural network (ANN) inputs; thus, RBF neural network is applicable to every studied system. The developed ANN is trained with the worst case of the switching angle and remanent flux and tested for typical cases. The simulated results for a partial of 39‐bus New England test system show that the proposed technique can measure the peak values and duration of switching overvoltages with good accuracy.
Highlights
This paper presents an artificial intelligence application to measure switching overvoltages caused by shunt reactor energization by applying analytical rules
In high-voltage HV power systems usually power is transmitted through long high-voltage transmission lines
For the absorption of the surplus reactive power, HV shunt reactors are connected to the receiving end of the transmission lines
Summary
In high-voltage HV power systems usually power is transmitted through long high-voltage transmission lines. For the absorption of the surplus reactive power, HV shunt reactors are connected to the receiving end of the transmission lines. Switching of those shunt reactors produce transients that need to be carefully studied and, if required, limited 1–7. Transient overvoltages are a consequence of switching operations on long transmission lines, or the switching of capacitive devices, and may result in arrester failures. A tool such as the one proposed in this paper that can give the maximum switching overvoltage and its duration will be helpful to the operator during system restoration. Results of the studies are presented for a partial of 39-bus New England test system to illustrate the proposed approach
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