Identification of Inrush Current Using a GSA-BP Network

Abstract

Ensuring a stable and efficient transformer operation is a very crucial task nowadays, especially with the integration of modern and sensitive electrical equipment and appliances down the line. However, transformer maloperation still cannot be completely avoided, particularly with the existence of inrush current that possess similar characteristics as the fault currents when a fault occurred. Thus, this paper proposes an enhanced method for inrush current identification based on a backpropagation (BP) network, optimized using genetic and simulated annealing algorithms. The proposed method has the ability to find the global optimal solution while avoiding local optima, with increased solution accuracy and low calculation complexity. Through extensive simulations, it was found that the inrush and fault currents have differences in their harmonic contents, which can be exploited for the identification of those currents using the proposed identification method. The proposed genetic simulated annealing–BP (GSA-BP) algorithm make use of 200 current samples to improve the detection accuracy of the inrush current from 80% to 97.5%. Comparative studies performed against the existing identification methods show that the GSA-BP network has superior efficiency and accuracy while being practical for real-life application to improve the transformer protection system.

Deep Learning-Based Algorithm for Internal Fault Detection of Power Transformers during Inrush Current at Distribution Substations

“…Despite the improvement made, a high sampling rate is required, and it may be susceptible to noise. A process to identify an inrush current based on the enhanced GSA-BP approach was proposed in [25] to discriminate inrush currents from fault currents in transformers.…”

Wavelet scattering and multiclass support vector machine (WS_MSVM) for effective fault classification in transformers: a real-time experimental approach

“…• The percentage of SHR is utilized to avoid the trip signal issued by the relay for magnetizing inrush events whenever the circuit breaker is switched to energize the transformer or the magnitude increases due to sympathetic inrush current (SIC) when a parallel connected transformer is switched. However, the magnitude of SIC depends on various factors like the size of the parallel connected transformer and its strength in the system [16].…”

“…• Prediction: To make predictions on new data, the algorithm traverses the tree from the root node to a leaf node, following the decision rules learned during training. The predicted class label or regression value at the leaf node is then assigned to the input sample Also, some available literature [16,18] discusses the classification of inrush current, but have lower efficiencies of less than 96% and thus have not been compared in this paper. The details of the proposed algorithm WS_MSVM are discussed in the next section.…”

Field Programmable Gate Array-Based Smart Switch to Avoid Inrush Current in PV Installations

“…In [ 35 , 36 , 37 ], several methodologies are proposed to identify inrush currents in protection schemes and distinguish them from fault currents.…”