Metal Oxide Surge Arresters Research Articles

Development of Quality Inspection System for Insulation Monitoring Device of Metal-Oxide Surge Arrester

Metal-oxide surge arrester (MOA) is one of the important equipment in electrical utility company, its security and stability is critical to the safe operation of electrical equipment, and the insulation monitoring device is vital for getting the running status of metal-oxide surge arrester. Technical parameters requirements of this kind of device is discusses in this paper , and furthermore, relying on the condition monitoring technology laboratory for transmission and transformation equipment of the State Grid Corporation of China, a complete set of quality evaluation system is established, of which the following functions were realized, the total current and resistive current measurement error test, communication function test, environmental adaptability test, insulation performance test, electromagnetic compatibility performance test, mechanical performance test, enclosure protection performance test etc. With the system, a powerful technical support can be provided for the quality evaluation of the device, as well as the safe and reliable operation of the arrester.

Optimal Surge Arrester Parameter Estimation Using a PSO-Based Multiobjective Approach

In this paper, an improved self-adaptive particle swarm optimization (ISAPSO) algorithm is developed for estimating the best set of surge arrester model parameters. The purpose is to minimize the relative error between the calculated and manufacturer's measured residual voltage peak values for lightning, switching, and steep-front impulses. An objective function, which generalizes the model parameters for all impulse current types with different peak levels, is proposed. This objective function is the summation of three subfunctions that in each of them one type of impulse current with different current peak levels is considered. An efficient multiobjective approach is also applied along with the presented ISAPSO method. The proposed algorithm finds different sets of Pareto-optimal nondominated solutions for the objective functions. A fuzzy clustering technique is used to restrain the size of the repository within the desired limit. The proposed method is applied for a 150-kV TRIDELTA metal-oxide surge arrester in order to demonstrate its accuracy and effectiveness.

Simulation and analysis of metal-oxide surge block arrester dynamic characteristics

Metal-oxide surge arresters play an important role in protecting power system equipment doing lightning surges and switching surges. Especially, overhead transmission lines are often struck by lightning. This often results in line faults. These can be reduced effectively by installing lightning arresters. Recently, some simulation programs such as EMTP/ATP have been developed to estimate the benefits of the installation of lightning arresters. For those simulation programs, the arrester model is usually a non-linear resistor. As seen in many discussions from papers and theories, the ZnO arrester, which is the most popular, has the dynamic behavior of frequency dependence. In other words, the residual voltage of the arrester depends on the frequency of surge. The higher the frequency of surges, the higher the residual voltage of the arrester. In this article, the simulation results of four different frequency-dependent models examined by EMTP/ATP show relative maximum error lower than 9%, as well as the residual voltage of arrester being increased by 14% when the front time of surge is reduced from 8 to 1 µs. With these results, this article offers suggestions to use frequency-dependent arrester models for all corrective arrester simulations to enhance the accuracy of simulation programs.

Reliability of directly-molded polymer surge arresters: Degradation by immersion test versus electrical performance

This technical report describes an experimental analysis of metal–oxide surge arresters applied to power distribution network. This analysis is performed from periodical measurements of leakage current of the samples and hydrophobicity of the external polymeric housing correlated to the aging/degradation process by saline water immersion at 90°C for 3months, in order to simulate 20years of field application. Based on this evaluation, the useful life and time degradation of polymer arresters are analyzed from the progressive variation of their electrical characteristics as a function of the immersion time.

Evaluation of MOSA condition using leakage current method

This paper covers the evaluation of metal-oxide surge arrester (MOSA) condition using the method based on the analysis of leakage current at the operating voltage of the network. A comparison is made between the following variants of this method: (1) the method based on harmonic analysis of the total leakage current; (2) the method based on the third order harmonic of the resistive leakage current; (3) the method of power loss; (4) the capacitive current compensation method; and (5) the method based on direct measurement of the amplitude of the resistive leakage current. For these methods the appropriate indicators are introduced for evaluating the MOSA condition. The application of these methods is analyzed depending on fluctuation and the presence of higher harmonics of the MOSA operating voltage. Calculations were conducted using the program MATLAB on a simplified equivalent circuit of a MOSA with a non-linear element modeled using the degree function. Based on the calculation results, a gradation was made for the applicability of individual indicators for evaluating the MOSA condition which indicates a special advantage for using the fundamental harmonic of the resistive component of leakage current and the fundamental harmonic of power loss.

A More Uniform Electric Field Distribution on Surge Arresters through the Optimal Design of Spacer and Fiber Glass Layer

In this study, the optimal design of spacers and fiber glass layer of a metal oxide surge arrester is presented in order to achieve a more uniform electric field distribution, inside and outside the arrester. This is done by using intelligent algorithms and numerical analysis, i.e., Finite Element Method (FEM). The introduced method can be used in order to determine the optimal dimensions of spacers and fiber glass layer so that the electric field distribution is optimized and the lifetime of highly stressed ZnO blocks in the vicinity of HV electrode is increased. In order to verify the results, Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms are used.

Preventing Transformer Energizing Resonant Overvoltages Using Surge Arrester Temperature Rise Index and Controlled Closing Method

Resonant overvoltages caused by transformer energization in relatively weak systems, especially during power system restoration, are investigated in this paper. These transient overvoltages may result in failures, especially for surge arresters. A theoretical analysis is performed to obtain the transformer inrush current harmonics and the transmission-line lengths for which the harmonic resonance is likely to occur. The temperature rise of surge arresters is proposed as an index to diagnose a harmonic resonance case. An appropriate electrothermal model for metal-oxide surge arresters is developed using the thermal model and proposed combined electrical model. Comprehensive transient simulation studies are performed to find out the harmonic resonance cases using the proposed index. Obtained simulation results are in good agreement with the analytical results. To reduce such harmonic resonance cases, controlled closing of the transformer can be utilized. In this paper, the proper instants for transformer energization are proposed in such a way that the overvoltage is reduced to acceptable values.

MOSA Monitoring Technique Based on Analysis of Total Leakage Current

Currently, the majority of metal-oxide surge arrester (MOSA) monitoring techniques are based on total leakage current decomposition of their capacitive and resistive components. However, these techniques are subject to some financial, technical, and practical limitations, which can hamper their usage on the field. In this paper, a new monitoring technique for the zinc-oxide surge arrester is proposed. The technique is based on the feature extraction of measured total current signals and on the analysis of these characteristics by artificial neural networks. The measured total currents were obtained from station class surge arresters submitted to their maximum continuous operating voltage. In the lab tests, six different kinds of failures were simulated on the tested MOSA with the purpose of evaluating the capacity of the technique to distinguish different operating conditions of surge arresters. Hit ratios greater than 98% were obtained in the identification of the operating conditions. The results show the viability of the technique on MOSA monitoring procedures.

Monte Carlo analysis of wind farm surge arresters risk of failure due to lightning surges

This paper presents a Monte Carlo procedure intended for the assessment of the metal-oxide (MO) surge arresters risk of failure in onshore wind farms. It focuses on the energy withstand (absorption) capability of the MO surge arresters in relation to lightning surges and in terms of their risk of failure assessment. Presented methodology accounts for the fact that the lightning itself is stochastic in nature and that the MO surge arrester energy capability is a statistical quantity. The well-known backsurge phenomenon is employed as a means for studying the MO surge arresters energy stresses due to lightning surge transients (in onshore wind farms), where the associated transient (i.e. high-frequency) models of particular wind farm components feature prominently. Necessary numerical simulations are carried-out with the well-known EMTP-ATP software package. This procedure could be seen as beneficial in selection of the optimal MO surge arrester energy withstand capability for wind farm projects situated in areas marked with high keraunic levels and/or having high soil resistivity.

Simulation Study of the MOA Resistive Leakage Current Detection Method

On-line monitoring of the insulating state of metal oxide surge arresters (MOA) is monitoring its resistive leakage current. This paper analyses the common detection methods of resistive current, pointed out the problems. According to the relationship among the grid voltage and the flow through the leakage current of MOA, the resistive and capacitive current, put forward a new resistive leakage current detection method, and established a mathematical model. Using this mathematical model, new detection method can be verified by simulation. Confirmed that the new method can effectively reduce the impact of the power grid of the third harmonic voltage and phase coupling capacitor, this create a precise measurement for MOA resistance current online testing.

A Current Orthogonality Method to Extract Resistive Leakage Current of MOSA

A new resistive current extraction method based on orthogonality between the capacitive current and the resistive current (COM) is presented. Orthogonality of the resistive and capacitive current of metal-oxide surge arrester (MOSA) in the low current region is proven. The resistive and capacitive current of MOSA can be obtained accurately, regardless of the harmonic voltage. Several algorithms include the point-on-wave method, the capacitive current compensation method, the harmonic analysis method, and the proposed method are used to extract the resistive current based on simulated voltage and leakage current signal, and to study the influence of MOSA model parameters, capacitance, integral harmonics, and noninteger harmonics of voltage signal, the signal frequency deviation, and the offset in sampling time between current and voltage channels on calculation accuracy. The result indicates that the proposed method has no error if the voltage and current are noiseless, but gives rise to a small error even if the signals have noise. The proposed method is more accurate than other methods. The real voltage and leakage current signals of a 10-kV MOSA are acquired by experiment, and the result indicates that the proposed method is effective and the most stable.

Comparison of metal oxide surge arrester models in overvoltage studies

Comparison of metal oxide surge arrester models in overvoltage studies

Comparison of metal oxide surge arrester models in overvoltage studies

During switching or lightning overvoltages, surge arresters play an important role in limiting voltage levels and protecting substation equipment, by conducting the excess of current in the system, which would otherwise damage the equipment. This paper aimed to conduct a technical comparison of the models developed to represent the frequency dependent characteristic of metal oxide surge arresters. The scope of this paper also included outlining a methodology to choose which one would be more appropriate. The major contribution of this article is the validation of the models in a typical 500 kV substation insulation coordination study.

Evaluation of lightning performance of transmission lines protected by metal oxide surge arresters using artificial intelligence techniques

Lightning and switching overvoltages are the main causes for faults in electrical networks. In the last decades, several different conventional methodologies have been used for the adjustment of the lightning performance of high voltage transmission lines, which are protected against lightning using overhead ground wires and surge arresters. The current paper proposes a new developed Artificial Neural Network (ANN), based on the Q-learning algorithm, in order to estimate the lightning failure rate of lines of the Hellenic system. The results obtained by the ANN model exhibit a satisfactory correlation in comparison with the real recorded data or the simulations results taken from a conventional method.

Low Current Transformer Utilizing Co-Based Amorphous Alloys

Metal oxide surge arresters have been widely used for protection of power system networks against overvoltages caused by atmospheric discharges or malfunction of devices connected to the network. During its operation, a surge arrester structure is degradated, which can be observed as an increase of a surge arrester leakage current. This paper presents an implementation of a new, high-permeability, Co64Fe4Ni1Si15B14 amorphous alloy as a current transformer for monitoring of a leakage current in low voltage surge arresters. The characteristics of the current transformer for different loads have been measured in the system using very sensitive current-voltage converter. Experimental results confirmed that low current transformer utilizing Co64Fe4Ni1Si15B14 amorphous alloy in annealed state gives a possibility to measure a leakage current about several μA with operating frequency 50 Hz. Moreover, the results indicate that the leakage current waveforms have a different shape than a pure sine wave voltage applied to the surge arrester enabling an evaluation of the device nonlinearity as a measure of its degradation by means of a resistive component of the leakage current.

Ferroresonance of Power Transformers Considering Non-linear Core Losses and Metal Oxide Surge Arrester Effects

In this article, a simple case of ferroresonance in a three-phase transformer is used to study the effect of a metal oxide surge arrester on the control of chaotic ferroresonance and duration of chaotic transient in a power transformer including non-linear core losses. The time-domain simulations are derived using MATLAB (The MathWorks, Natick, Massachusetts, USA) for a three-phase 50-MVA, 635.1-kV power transformers while one of its phases is opened. The magnetization characteristic of the power transformer is modeled by a single-value two-term polynomial. The non-linear core losses are modeled by a third-order power series in terms of voltage, and the core losses non-linearities are considered as well. The simulation results show that connecting the metal oxide surge arrester to the transformer exhibits a great suppressing effect on occurred ferroresonance over-voltage.

Effect of Metal Oxide Surge Arrester on Ferroresonance inVoltage Transformer Including Nonlinear Core Losses

This paper studies the effect of Metal Oxide Surge Arrester (MOSA) on ferroresonance overvoltage transformer (VT) considering nonlinear core losses effect. It is expected that MOSA generally cause ferroresonance 'dropout'. Time-domain study has been done to study this effect. Simulation has been done on a voltage transformer rated 100VA, 275 kV. The magnetization characteristic of the transformer is modelled by a single-value two-term polynomial with order seven. The core loss is modelled by nonlinear resistance. The simulation results reveal that connecting the MOSA in parallel to the VT exhibits a great controlling effect on ferroresonance overvoltages. Phase plane, voltage waveforms, along with bifurcation diagrams are also derived. Significant effect on the onset of chaos, the range of parameter values that may lead to chaos along with ferroresonance overvoltages has been obtained and presented.

Characteristics and possibilities of software tool for metal-oxide surge arresters selection

This paper presents a procedure for the selection of metal-oxide surge arresters based on the instructions given in the Siemens and ABB catalogues, respecting their differences and the characteristics and possibilities of the software tool. The software tool was developed during the preparation of a Master's thesis titled, 'Automation of Metal-Oxide Surge Arresters Selection'. An example is presented of the selection of metal-oxide surge arresters using the developed software tool.

A novel parameter estimation method for metal oxide surge arrester models

Accurate modelling and exact determination of Metal Oxide (MO) surge arrester parameters are very important for arrester allocation, insulation coordination studies and systems reliability calculations. In this paper, a new technique, which is the combination of Adaptive Particle Swarm Optimization (APSO) and Ant Colony Optimization (ACO) algorithms and linking the MATLAB and EMTP, is proposed to estimate the parameters of MO surge arrester models. The proposed algorithm is named Modified Adaptive Particle Swarm Optimization (MAPSO). In the proposed algorithm, to overcome the drawback of the PSO algorithm (convergence to local optima), the inertia weight is tuned by using fuzzy rules and the cognitive and the social parameters are self-adaptively adjusted. Also, to improve the global search capability and prevent the convergence to local minima, ACO algorithm is combined to the proposed APSO algorithm. The transient models of MO surge arrester have been simulated by using ATP-EMTP. The results of simulations have been applied to the program, which is based on MAPSO algorithm and can determine the fitness and parameters of different models. The validity and the accuracy of estimated parameters of surge arrester models are assessed by comparing the predicted residual voltage with experimental results.

Comparison of the parameter estimation methods of surge arresters using modified particle swarm optimization algorithm

SUMMARYThe measurements show that the residual voltage of the metal oxide surge arrester (MOSA) has a dynamic characteristic. The accurate modeling and simulation of this dynamic characteristic is very important for arrester allocation, systems reliability, and insulation coordination studies. Several models with acceptable accuracy have been suggested to describe this behavior. It should be noted that the determination of nonlinear elements of MOSAs is very important for all models. In this article, a comparison among the different methods of the determination of the surge arrester voltage–current characteristics is represented. A new method, which is the combination of particle swarm optimization (PSO) and ant colony optimization methods, is proposed to estimate the parameters of MOSA models. In the proposed algorithm, to overcome the drawback of the PSO algorithm (convergence to local optima), to improve the global search capability, and to prevent the convergence to local minima, ant colony optimization algorithm is combined to PSO algorithm. The proposed method is called modified PSO. The transient models of MOSA have been simulated by using ATP‐EMTP. The results of simulations have been applied to the program, which is based on the modified PSO method and can determine the fitness and parameters of different models. The validity and the accuracy of the estimated parameters are assessed by comparing the predicted residual voltage with the experimental results. Copyright © 2011 John Wiley & Sons, Ltd.