OSSB and Hybrid Methods to Prevent Cable Faults for Harmonic Containing Networks (original) (raw)
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MSSB to Prevent Cable Termination Faults for Long High Voltage Underground Cable Lines
Elektronika ir Elektrotechnika
Cable termination fault is one of the most important problems for high voltage underground cable lines (HVUCL). Harmonic current (HC) and the sheath current (SC) are causes of cable termination faults of HVUCL. The sheath voltage (SV) of cable increases due to SC and HC also. So, the electroshock risk for human occurs. In this study, cable termination faults are examined for long HVUCL that is connected to electric network with high harmonic distortion rate. In literature, solid bonding (SB) and sectional solid bonding (SSB) methods are used to reduce harmonic distortion rate and SC effect in HVUCL. However, when SB and SSB methods are used for bonding of long HVUCL, harmonic distortion limit and touch voltage limit are exceeded. Therefore, the modified SSB (MSSB) method is developed for bonding of long HVUCL. SV of HVUCL should be known to use MSSB for bonding of long HVUCL. Then SV of HVUCL is forecasted by using artificial neural network and hybrid artificial neural networks (HAN...
Journal of Engineering Research, 2022
The insulation fault is a major problem in high voltage cable lines. The major factors in the insulation faults are harmonic currents and the metal sheath voltage (MV) that occur on the metal sheath of cable. MV and harmonic distortion should be minimized to prevent insulation faults. Thus, sectional solid bonding with different grounding resistance (SSBr) method is developed as a new bonding method for minimizations of harmonic current and MV. Also, SSBr should be optimized by optimized according to minimum MV and harmonic distortion rate of high voltage cable. Inertia weighted particle swarm optimization (iPSO), particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution algorithm (DEA) are used for optimization of SSBr, and three groups the prediction methods are used separately as objective function of the optimization methods to determine minimum MV and harmonic distortion. These groups are neural networks, hybrid neural networks and regression methods....
The optimized bonding method for long high voltage cable lines under the unbalanced cases
Neural Computing and Applications, 2019
In the unbalanced loading (UL) and phase to ground fault (PGF) cases, zero sequence current (ZC) flows on neutral point of power transformer, and the sheath current (SC) and the sheath voltage (SV) increase due to ZC. Thus, overvoltage (OV) and high harmonic distortion (HD) occur in cable termination (CT). OV causes high and imbalanced electric field, and high HD causes increasing of insulation temperature in CT, so CT faults occur. In the literature, bonding methods are used to prevent SC and SV effects, but these methods are not sufficient to prevent ZC effects, so the modified sectional solid bonding (MSSB) is suggested to prevent ZC effects. The aims of this study are minimizations of SV and HD on CT to prevent CT faults, so MSSB parameters are optimized by optimization method. In optimization algorithms of MSSB, the forecasting methods (FM) and optimization methods (OM) are used to optimize MSSB parameters. The best FM is selected according to training and forecasting errors, and the selected FM is used as an objective function of OM. Training and forecasting errors of hybrid ANN are less than the other methods, so hybrid ANN methods are used as FM. When bonding methods that are in literature are simulated under UL and PGF cases, SV and HD values exceed the limits. When the optimized MSSB method is used, HD and SV do not exceed the limits. Therefore, the optimized MSSB is suggested to prevent CT faults for the unbalanced cases.
Artificial intelligence based high voltage cable bonding to prevent cable termination faults
Electric Power Systems Research, 2020
Cable termination fault (CTF) is a major problem for high voltage cable lines (HVCL). Increasing of the sheath voltage (SV), zero sequence current (ZC) and current harmonic distortion (THDI) on metallic sheath (MS) of HVC are major factors for CTF. MS is grounded according to IEEE 575-1988 standard to reduce SV. However, these methods are not sufficient to prevent CTF based on ZC and THDI. The aims of this paper are minimization of SV, ZC and THDI to prevent CTF based on ZC and THDI. Thus, LSSB method is developed as a new bonding method. Also, LSSB parameters should be optimized to make the most economical and practical bonding. GA, DEA, PSO and iPSO are used optimization methods for optimization of LSSB. SV and THDI should be known for optimization of LSSB, so the forecasting methods (FM) are used as fitness function of optimization methods in LSSB optimization. The regression and hybrid artificial neural network methods are compared to determine the most suitable FM. When the optimized LSSB is used for bonding of long HVCL, SV reduces approximately 90%, ZC reduces approximately 93%, and THDI reduces approximately 70%. Thus CTF risk is minimized by using the optimized LSSB in HVCL.
High‐voltage cable bonding to prevent cable termination faults based on zero‐sequence current
International Transactions on Electrical Energy Systems, 2019
Zero-sequence current (ZC) occurs due to harmonics and unbalanced loading current. ZC increases the sheath voltage (SV) and cable temperature, so cable faults occur on cable terminations in high-voltage underground cable lines (HVUCL). In literature, bonding methods are used to prevent ZC effects, but these methods are not adequate to prevent ZC effects for long HVUCL under high harmonic distortion because ZC is not considered when these methods are designed. In this study, the modified sectional solid bonding (MSSB) is suggested for long HVUCL that works under high harmonic distortion rate and unbalanced loading conditions. Namely, ZC is considered when MSSB is designed. MSSB parameters should be determined before HVUCL is installed for the most economical and practical bonding. SV of HVUCL should be known to determine MSSB parameters, so SV of HVUCL is forecasted by using adaptive network-based fuzzy inference system (ANFIS), artificial neural networks (ANN), and hybrid ANN. Training and forecasting errors of hybrid ANN are less than ANFIS and ANN methods, so hybrid ANN methods are suggested to forecast SV of HVUCL. Also, MSSB parameters should be optimized, so optimization methods are used for optimization of MSSB. When MSSB method is used for bonding of long HVUCL, harmonic distortion rate and SV in cable terminations are not exceeded the determined limits to prevent cable faults.
The sheath current effects are major problems for electrical network and facilities. The sheath voltage is increased by the sheath current. Thus the sheath voltage exceeds touch voltage, and electroshock risks and cable faults occur. Also, cable temperature is increased by the sheath current, so cable ampacity reduces. In literature, single-point bonding, solid bonding and cross bonding are used to reduce sheath voltage and current. However, if the unbalanced phase current is high, the sheath voltage is not dropped under touch voltage by using these bonding methods. Therefore, sectional solid bonding method is developed to solve this problem in this study. When sectional solid bonding is used to reduce the sheath voltage and current, the sheath voltage drops under touch voltage although unbalanced phase current is high. Also, optimum parameters for sectional solid bonding are determined by differential evolution algorithm.
GSA-ANN and DEA-ANN Methods to Prevent Underground Cable Line Faults
International Journal of Computer and Electrical Engineering
Cable faults is an important issue for underground cable lines, and the sheath current is a major factor for cable faults. The sheath current occurs on metallic sheath of high voltage underground cable. Thus, metallic sheath of underground cable is grounded to prevent the sheath current faults. If the sheath current which will generate on metallic sheath, the most suitable grounding method can be selected to prevent the sheath current effects. In this study, artificial neural network (ANN) is used to determine the sheath current of underground cable line, and many simulation studies of the sheath current are made to obtain training data of ANN. Simulation studies of sheath current of different underground cable lines are made in PSCAD/EMTDC. Also optimization methods are used to update weights of ANN. Gravitational search algorithm (GSA) and differential evolution algorithm (DEA) are used to optimize weights of ANN. It is seen that training and forecasting errors of hybrid methods are lower than classic ANN.
2017
Power is increasingly supplied to city centres with 110 kV cable lines. This is a convenient way to supply power, and practically the only one possible in areas of dense urban development. A high-voltage cable contains a coaxial metallic sheath, in which in normal operation and in fault conditions (during short-circuits) significant line-to-earth voltages can be induced, which threatens electric shock and/or damage to the cable’s outer non-conductive sheath. These voltages depend on the earthing/bonding of the cable’s sheaths, and on the cable configuration. These voltages induce currents, which, in turn, cause additional power losses in the cable. The article presents multivariate analysis of the voltages induced in a selected cable line in steadystate condition. Single-point bonding of sheaths has been discussed, as well as their both-ends bonding, transposition, and transposition of cores (conductors). For each case, the losses of active power in this line have been calculated. D...
Hybrid GSA-ANN Methods to Forecast Sheath Current of High Voltage Underground Cable Lines
Journal of Computers
Electrical safety is major issue for electric networks, so high voltage underground cable lines have been used instead of overhead line recently in city center and neighborhood. However, sheath current generates on metallic sheath of high voltage underground cable, and sheath current causes major cable faults and electroshock. Single point bonding, solid bonding and cross bonding are used to reduce sheath current and voltage. If sheath current is determined before high voltage underground cable line is installed, the most suitable method can be used to reduce sheath current and voltage. Hence, cable faults and electroshock can be prevented. There are many factors in formation of sheath current. Thus, formulation of sheath current is very complex and difficult. In this case forecasting methods can be used to determine sheath current, and artificial neural network (ANN) is a powerful method for forecasting studies. In this study, Gravitational Search Algorithm (GSA) and artificial neural network (ANN) is used to reduce training error, and hybrid GSA-ANN method is obtained. It is seen at the end of this study that errors of hybrid GSA-ANN method are less than errors of classic ANN.
Single-core underground power cables with two-points bonding induce currents in their metallic sheaths. The sheath induced currents are undesirable and generate power losses and reduce the cable ampacity. This paper has shown that the values of the sheath losses in some cases could be greater than conductor losses, depending on various factors. Such these factors are type of cable layouts, cable parameters, cable spacing, sheath resistance, phase rotation, conductor current and cable armoring. In this paper the above factors have been investigated. The calculations are carried out depending mainly on IEC 60287 by a proposed computer program using MATLAB.