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Partial Discharge (PD) measurement is one of the best solutions for condition assessment of Gas Insulated Switchgears (GISs). For having Condition-based maintenance of GIS, online PD monitoring is of great importance. For this aim, Ultra High Frequency (UHF) PD sensors should be installed inside the GIS during the installation. However, in most installed GISs in industries, the internal UHF PD sensors are not installed. In this paper, a new method for online defect type recognition according to external UHF PD sensors and based on the time-frequency representation of PD signal is proposed. In this case, four artificial defect types named protrusion on the main conductor, protrusion on the enclosure, free moving metal particle, and metal particle on spacer are implanted inside the 132 kV L-Shaped structure of one phase in enclosure GIS. The signal energy at each level of the decomposed signal by Discrete Wavelet Transform (DWT) is applied for features of each defect type. The trends of signal energy variations at each frequency range of signal are applied for discriminating between each defect type. The Deep Feed Forward Network (DFFN) classifier is applied for PD pattern recognition. The results show the benefits and simplicity of the proposed method for PD signal classification, independent from the position of the PD sensor, especially in the case of online PD monitoring of GIS. [ABSTRACT FROM AUTHOR]

Change in customers' consumption patterns due to the introduction of new electricity consuming technologies into human consumption practices has impacted the existing optimal loading profile of the grid facilities. Although some MV/LV distribution transformers (DTs) are operating under a light load profile, this does not guarantee that they are in a healthy condition, since necessary maintenance procedures are required. On the other hand, many unplanned overloading conditions occur on the other DTs and causes accelerated failures which contributes to very high operational costs. This paper presents the outcome of a study on how the planned DTs relocation can save asset managers against their huge DTs replacement costs developed due to the highly overloaded DTs failures in a utility, and how it will improve the overall reliability of the DTs. A mixed-integer linear programming (MILP) solution is proposed to formulate the introduced economic relocation-based asset management (AM) framework while minimizing total cost (TC) of the network. The results show that incorporating relocation techniques into the AM formulation ends in reduction of the distribution network TC and a decrease in asset failure rates if compared with application of traditional techniques. [ABSTRACT FROM AUTHOR]

Application of the network equivalent concept for external system representation in electromagnetic transient studies is well known. However, the challenge in application of an equivalent model, approximated by rational functions, is to guarantee passivity of the corresponding model. Therefore, there is a need to enforce passivity of the equivalent model. In this paper, the passivity enforcement problem is first formulated as a quadratic programming (QP) problem, and then solved based on an efficient implementation, using an infeasible-interior-point primal-dual method. An application of this method for passivity enforcement of a six-port admittance model (with large passivity violations) demonstrates its effectiveness and computational efficiency. Index Terms--Convex quadratic optimization problem, infeasible-interior-point primal-dual method, network equivalent, passivity enforcement.

The fast and very fast transient overvoltages can endanger the insulation of transformer windings. Therefore, it is necessary to develop models, to study these transients. This paper compares the two well-known multiconductor transmission line (MTL) and lumped parameter detailed (RLC ladder network) models. The high-voltage (HV) winding of a 220/35-kV, 50-MVA transformer has been modeled using these models. The simulation results of the MTL and the RLC ladder network models have been compared with the measurements results in the frequency domain, by application of the Pearson's correlation coefficients. It is shown that the RLC Ladder Network model should be used for fast transient overvoltage (FTO) studies, i.e. frequency range of 10 kHz < f < 1 MHz and the MTL model with frequency dependent loss factor, demonstrates a better agreement with the measurement results for very fast transient overvoltage (VFTO) studies, i.e., in the frequency range of 1 MHz [less than or equal to] f [less than or equal to] 5 MHz. Index Terms--Loss factor, modeling, multiconductor transmission line, power transformer, very fast transient.

Understanding the potential and electric field distribution in the insulation system of a transformer during transients is vital to its construction. Therefore, we have developed a method for electric field analysis inside a power transformer. The method consists of the following steps. 1) A lumped parameter equivalent model is constructed by dividing transformer windings into several blocks. 2) The electric circuit parameters of this model are calculated. 3) Employing the results of the transformer transient model analysis as boundary conditions, a 2-D asymmetrical electric field finite-element analysis is performed to determine electric fields through the windings. The method has been examined employing power frequency and impulse voltages. We have also demonstrated successful application of the method to a transformer and have verified the computed results by comparison with measured results. Index Terms--Electric field, finite-element analysis, insulation design, power transformer.

Online monitoring of high voltage (HV) cross linked polyethylene (XLPE) cables is a major requirement and interest of utilities for reliable operation of underground cables. Although XLPE cables have a relatively reliable insulation system, however since its insulating material is less resistant to partial discharges (PD), the failure risk increases significantly after occurrence of any partial discharge. Therefore sensitive sensors and a reliable detection system are required for an effective cable life management. Due to attenuation effects of semi-conducting layers of XLPE cables on high frequency components of partial discharge signal, the detection process is easily distorted with application of conventional sensors such as high frequency current transformers (CTs). In this paper a new sensitive internal sensor of partial discharge signal, the semiconducting layer, is introduced which is available normally in the H.V. XLPE cables and access can be easily provided at the terminals and also at some specific distances from the terminals, i.e. every one hundred meters, if the manufacturer was asked for. Two 11 kV, XLPE cable setups are employed for study of high frequency signals and partial discharge signals propagation in the XLPE cable and its semiconducting layers. The J Marti's frequency dependent cable model is employed for simulation of partial discharge signal propagation in the core conductor and semiconducting layers of single phase XLPE cables. Index Terms--Attenuation, cable model, signal detection, partial discharges, semiconducting layers, simulation, internal sensor.

Partial Discharge (PD) measurement is one of the main methods for condition monitoring of Gas Insulated Switchgears (GIS). Internal Ultra High Frequency (UHF) sensors can be applied for capturing PD propagated electromagnetic signals within the GIS. PD sensor placement inside the GIS is one of the main challenges for designing an online PD measuring system. For this aim, the impacts of different GIS components on propagated PD electromagnetic waves should be studied. In this paper, different PD sensor position angles (with respect to PD sensor) are used to investigate their sensitivity to measuring PD electromagnetic waves. Two distinguishable parameters from the calculated PD electromagnetic waves, the first rated electric field and the signal's power over the two frequency ranges (0.3-2 GHz and 0.3-3 GHz) are used to analyze and quantify the calculation results. The impacts of different enclosure diameters, different types of spacers, and various disconnector contact gap distances (under different voltage levels) on this wave propagation are studied. Additionally, the two standard GIS busbar profiles, named L-shape and T-shape, are discussed in this paper. The results show that the attenuation degree of the measured PD EM waves is strongly influenced by the busbar dimensions and the configuration of its components. The GIS busbar designer can employ these results to select the proper PD sensors and their installation locations. [ABSTRACT FROM AUTHOR]

An EHV transformer's insulation structure must be designed to withstand the internal stresses generated during transients. Computer models are employed for predetermination of these stresses. This paper develops a detailed transformer model and solution method which represents the nonlinear, saturable characteristic of the magnetic core during transients. The resulting set of stiff nonlinear differential algebraic equations (DAE's) are solved by application of Gear's method. Part 1 describes the transformer model and the necessary set of equations based on linearization of the iron core's saturable magnetic characteristic at each time interval. Part 2 presents data verifying the methodology.

An EHV transformer's insulation structure must be designed to withstand the internal electrical stresses generated during system transients. Computer models are employed for predetermination of these stresses. Part 1 of this paper developed a detailed transformer model and solution method representing the nonlinear, saturable characteristic of the core during transients. The resulting set of stiff nonlinear differential algebraic equations (DAE's) are solved by application of Gear's method. Part 2 presents the verification of this methodology. This is accomplished by comparing the computed and measured response of a 765/345/34.5kV 500MVA autotransformer during energization and transient excitation.

An EHV transformer's insulation system must be designed to withstand stresses generated during transient events. Computer models are employed for pre-determination of these stresses. The lack of accurate and consistent computer models for use by both utilities and manufacturers, is felt to contribute to the relatively high failure rate of EHV transformers. This paper develops a detailed nonlinear transformer model and a solution method that improves the accuracy with which the effect of the nonlinear characteristic of the magnetic core during transients can be predicted. This model is based on linearization of the core's saturable characteristic during solution time intervals. This paper describes a nonlinear, single phase, detailed transformer model and its verification against measured data.

The short‐term expansion planning of the private utilities, as well as the emerging technologies such as photovoltaic panels (PVs), plug‐in hybrid electric vehicles (PHEVs), cryptocurrency mining, and storage elements spread, make the long‐term load estimation of distribution transformers (DTs) noticeably imprecise. In response, the number of overload and underload transformers is growing in recent years. The utilities normally analyse the loading of their DTs annually to determine the DTs, which should be replaced. It is a common practice for utilities to relocate these DTs to reduce the investment needed to purchase new transformers. Therefore, the utility needs a systematic algorithm to determine the optimal schedule to relocate/replace the DTs with minimum required time and cost. This paper introduces a two‐stage procedure to obtain the optimal schedule to replace DTs. In the proposed algorithm, the maximum permitted number of work‐hours per day for field workers is considered, which converts the problem to a daily‐task based optimisation problem. Also, an useful life investigation of the in‐service DTs is considered in the relocation problem. A real case study in Qom province, Iran, has been studied to prove the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The general method for identifying the partial discharge type in a power transformer is based on their fingerprints in the form of phase‐resolved discharge patterns. In the case of multiple defects, traditional clustering methods can be applied for separation of active sources. However, such an approach is impractical for online real‐time monitoring due to the very large data size. In this paper a new method using stream clustering is introduced. The method separates the active sources by processing the signal once it is captured, then only a synopsis of the discharge data is stored. Two stream clustering algorithms: Density Grids and DenStream are employed. Through measurements obtained from laboratory experimental setups (corona, surface discharge, transformer defect model) performance of the proposed algorithms are evaluated. It is shown that stream clustering method is able to separate the constituent components involved in the stream of a multi‐source discharge signal without the need to store a large amount of information. The performance of the Density Grids method depends on a limited number of features that it can accommodate. In comparison, the DenStream method can capture more features which enable better separation of active sources at the expense of longer processing time. [ABSTRACT FROM AUTHOR]