EMF Estimation of Over Head Transmission Line Using CS Algorithm with Aid of NFC

Abstract

In this paper, the cuckoo search (CS) algorithm-neuro fuzzy controller (NFC) technique is proposed for estimating the electric and magnetic field (EMF) of over head transmission line (OHTL). In the proposed method, the CS algorithm is used to optimize the conductor spacing (arrangements) and to minimize the EMF. From the optimized arrangement of the conductors, the EMF of the transmission lines is evaluated and formed as the datasets. Then the optimized data set values are applied to the input of the NFC. Subsequently, the coordinates are given to the input of the NFC which predicts their corresponding EMF data. The proposed method is implemented in the MATLAB working platform. For testing the performance of the proposed estimation methods, two overhead transmission line models with 110 kV and 400 kV respectively are considered. In order to verify the effectiveness of the proposed method this is compared with the CS algorithm-ANN controller.

Low-frequency exposure analysis using electric and magnetic field measurements and predictions in the proximity of power transmission lines in urban areas

“…In recent years, artificial neural network techniques have been effectively used to predict the electromagnetic fields in overhead power transmission lines [19][20][21][22]. This study will shed light on the comparison of traditional methods with artificial neural network methods to estimate the electric and magnetic fields around power transmission lines.…”

A New Intelligent Estimation Method Based on the Cascade-Forward Neural Network for the Electric and Magnetic Fields in the Vicinity of the High Voltage Overhead Transmission Lines

“…Moreover, it needs precise instruments and skilled operators to avoid inaccuracies which turns it into an expensive practice [19]. Another means of EMF evaluation is analytical equations which can estimate the EMF with some simplifications in the boundary conditions, limiting them to being merely useful for simple problems [20]. Moreover, EMF can be estimated using numerical finite element methods (FEM).…”

“…In [20], Sivakami et al suggested a model using a cuckoo search algorithm (CSA) and neuro-fuzzy controller (NFC). First, they used the cuckoo search algorithm as an optimizer to optimize the conductor spacing, which has a significant effect on the intensity of EMF to make an input dataset with minimum electric field intensity for the NFC.…”