An Artificial Neural Network Developed in MATLAB-Simulink for Reconstruction a Distorted Secondary Current Waveform. Part 1

Recently, there has been an increased interest in the use of artificial neural networks in various branches of the electric power industry including relay protection. Аrtificial neural networks are one of the fastest growing areas in artificial intelligence technology. Recently, there has been an increased interest in the use of аrtificial neural networks in the electric power engineering, including relay protection. Existing microprocessor-based relay protection devices use a traditional digital signal processing of the monitored signals which is reduced to a multiplying the values of successive samples of the monitored current and voltage signals by predetermined coefficients in order to calculate their RMS values. In this case, the calculated RMS values often do not reflect the real processes occurring in the protected electrical equipment due to, for example, current transformer saturation because of the DC component presence in the fault current. When the current transformer is saturated, its secondary current waveform has a characteristic non-periodic distorted form, which is significantly differs from its primary (true) waveform, which causes underestimation of the calculated RMS value of the secondary current compared to its true value. In its turn, this causes to a trip time delay or even to a relay protection devices operation failure. The use of аrtificial neural networks in conjunction with a traditional digital signal processing provides a different approach to the functioning of both the measuring and logical parts of the microprocessor-based relay protection devices, which significantly increases the speed and reliability of such relay protection devices in comparison with their traditional implementation. A possible application of the аrtificial neural networks for the relay protection purposes is the fault occurrence detection and its type identification, current transformer secondary current waveform distortion restoration due to its saturation up to its true value, detection the distorted and undistorted sections of the current transformer secondary current waveform during its saturation, primary power equipment abnormal operating modes detection, for example, power transformer magnetizing current inrush. The article describes in detail the stages of the practical implementation of the аrtificial neural networks in the MATLAB-Simulink environment by the example of its use to restore the distorted current transformer secondary current waveform due to saturation.

Numerical Investigation for The Valorization of Waste from HMD Cell Using Electrodialysis

The Hydromagnetic desalination (HMD) system is a continuous process with several advantages, including a high water recovery ratio, and can be favored economically by producing several industrial byproducts instead of discharging the highly concentrated brine to the environment. In the current work, the ions concentration in the Electrodialysis (ED) technique is simulated using COMSOL Multiphysics V.5.2 software. The ED cell simulated in this paper contains two selective membranes (anion and cation) with a width of 0.25 mm each. The salt is to be taken away in the middle domain. The cell operation has been simulated to separate the sodium and chlorine ions from the HMD brine waste solution at 40 or 55ºC temperatures at different voltages and concentrations. In this two-dimensional model, the Nernst-Plank equation has been used to describe ion flux and charge transport in the electrolyte solution. Secondary current distribution theory and the electroneutrality condition have been used in the mathematical model. Finally, Donnan equations have been used to provide the exact fulfillment of boundary conditions for constant voltage mode. The simulation shows that the highest efficiency is obtained at high temperatures and voltage with the lowest feed concentration. Finally, the results have been validated using experimental data from the literature, and a satisfying agreement has been found.

Change in Transverse Slope of Water Surface at River Bend: A Numerical Study

Generation of secondary current in a meandering river flow due to the centrifugal force acting on the bend is three dimensional (3D) in nature. But in case of practical problems like alluvial geomorphic processes, 3D models are not proved to be efficient. Hence, two dimensional (2D) models are generally adopted for such problems. This study offers a presentation of numerical simulation results for turbulent flows around bends of a meandering channel for different meander angles. 2D models were built by the use of iRIC Nays2DH solver for flow simulation of 45˚, 90˚, 135˚, 180˚ meandering bends with varying widths of 0.15m, 0.25m, 0.75m, 1.00m, 1.25m and 1.50m considering constant Froude number with constant meandering length (ML/W) and constant radius of curvature (R/W). Zero equation model was used as turbulence closure with finite differential advections as upwind scheme. The flow behavior has been studied at the apex and cross over portions of bends. From the simulation, the velocity at outer bank was found to be lower than that of the inner bank while the water surface elevation was found to be higher than that of the inner bank. Increase in transverse slope of water surface at bend was observed for increasing meander angles, Froude numbers and decreasing channel widths. Journal of Engineering Science 12(2), 2021, 93-101

Range Automatic Adjusted Current Transformer Primary Winning

The article discusses the issue of introducing a correction factor for protection and control devices, as the value of the secondary current in a certain range of the auto-adjustable current transformer does not correspond to the value of the secondary current in another range determined by the difference of magnetic driving forces generated by the components of the primary current. Alternatively, an algorithm has been developed to account for the measurement error in this condition in an automatic system that controls the operating mode of the current transformer. It was also found that the output data should be transmitted taking into account the correction factor in order to ensure the proper operation of the protection and measuring devices when the current transformer is switched to another measuring range in the measuring range.

A Hybrid Intelligent Method for Compensation of Current Transformers Saturation Based on PSO-SVR

The Current Transformers (CT) saturation may cause the protective relays mal-operation either non-recognition of internal fault or undesirable trip under external fault conditions. Therefore, compensation of CT saturation is very important for correct performance of protective schemes. Compensation of CT saturation by combination of signal processing methods and intelligent algorithms is a suitable solution to solve the problem. It decreases the probability of mal-operation and increases the reliability of the power system. In this paper, Support Vector Regression (SVR) method is employed to compensate the distorted secondary current due to CT saturation. In SVR method, despite the other methods such as MLPand ANFIS, instead of minimizing the model error, the operational risk error is considered as target function. In this method, by using Kernel tricks, a smart RBF neural network is obtained, so that all operational procedures will be optimized automatically. In this paper, an intelligent method based on Particle Swarm Optimization (PSO) algorithm is presented to determine the optimal values of SVR parameters. Due to the stability and robustness of this method in presence of noise and sudden changes in current, this method has a high accuracy. In addition, a sample power system is simulated using PSCAD software. Afterwards, current signals are extracted and fed to PSO-SVR algorithm, which is implemented in MATLAB environment. The obtained results show the preference of the proposed method in aspect of estimation accuracy as compared to some presented methods in the field of CT saturation detection and correction.

An explicit expression for velocity profile in presence of secondary current and sediment in an open channel turbulent flow

The present study revisits the determination of vertical distribution of streamwise velocity in an open channel turbulent flow considering the effect of secondary current in the presence of sediment together with a concentration dependent settling velocity and von Karman constant κ s. The work mainly modifies a previous study that introduced a lot of assumptions to obtain an analytical solution of the velocity distribution. The present study overcomes those assumptions in the model and though not fully analytical, attempts to present a semi-analytical solution that is explicit and in the form of a convergent series. Homotopy analysis method is used for this purpose and it is validated with numerical solution as well as with available laboratory data from the literature. How the secondary current and concentration dependent κ s influence the velocity profile, is also discussed.

Effects of Secondary Currents on Turbulence Characteristics of Supercritical Open Channel Flows at Low Aspect Ratios

In this paper, we present secondary current effects on the turbulence characteristics of supercritical narrow open channel flows over a smooth fixed bed. The main hydraulic parameters are low channel width to flow depth ratios varying between 1 and 2, and Froude numbers (F) ranging from 2 to 4. Detailed profiling of instantaneous streamwise and vertical flow velocities was conducted in a laboratory flume using a 2D laser Doppler anemometry. The cross-sectional distributions of mean flow velocities, turbulence intensities, Reynolds, and bed shear stresses were obtained from the measurements. The mean streamwise and vertical flow velocity distributions reveal that four pairs of secondary current cells are formed: a pair of well-developed free-surface vortices near the water surface, a pair of bottom vortices near the bed, and two pairs of mid-vortices between the free-surface and bottom vortices. These secondary currents cause bulging of the contour lines of the streamwise velocities with respect to the water surface and the bottom corner bisectors resulting in an undulated pattern of the mean velocity distribution across the cross-section. Furthermore, they cause the velocity dip phenomenon, i.e., the maximum flow velocity occurs well below the surface, and redistribute the Reynolds and bed shear stresses in transverse direction. The results demonstrate that decreasing the aspect ratio increases the strength of the secondary currents causing a significant change in flow patterns with larger free-surface vortices compared to the bottom vortices. Compared to the aspect ratio effect, the Froude number only slightly impacts the flow characteristics as a result of flow non-uniformity. For all investigated aspect ratios and Froude numbers, bed shear stresses are concentrated at the flume center, and on average 5 to 10% higher than their mean values. The modified wake-log-law holds both in the inner and outer regions, matching well with the experimental data for all test conditions. The present findings are discussed with literature data, and their impact on engineering applications is demonstrated.