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The paper proposes a new local method of controlling the on-load tap changer (OLTC) of a transformer to mitigate negative voltage phenomena in low-voltage (LV) networks with a high penetration of photovoltaic (PV) installations. The essence of the method is the use of the load compensation (LC) function with settings determined via artificial neural network (ANN) algorithms. The proposed method was compared with other selected local methods recommended in European regulations, in particular with those currently required by Polish distribution system operators (DSOs). Comparative studies were performed using the model of the 116-bus IEEE test network, taking into account the unbalance in the network and the voltage variation on the medium voltage (MV) side. [ABSTRACT FROM AUTHOR]

In this paper, a method for determining line drop compensator (LDC) parameters for step voltage regulators and on‐load tap changers is proposed to avoid voltage violations in distribution systems with voltage fluctuations due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators need to effectively solve voltage problems caused by the widespread installation of distributed energy resources with the existing voltage regulators to construct an efficient and rational infrastructure. Our focus was on improving the method for determining the LDC parameters for the existing voltage regulators based on LDC control. A mechanism to dynamically change the LDC parameters depending on the situations in the distribution system was developed by using a mixture of experts, one of the machine learning techniques, and real‐time voltage and power flow information from information technology switches. The power flow calculations were performed using a distribution system model constructed based on the topology, loads, and generation characteristics of an actual distribution system in the Hokuriku region. The effectiveness of the proposed method was evaluated in terms of its improved effect on PV and EV hosting capacity, as well as the impact on the frequency of tap operations of voltage regulators. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xi'an Jiaotong University is the property of Editorial Office of Journal of Xi'an Jiaotong University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introducing solar and wind power into distribution networks (DNs) is an important initiative to promote the cleanliness and low-carbonization operation of DNs. However, the source and load outputs are uncertain in DNs, which will lead to problems of inaccurate regulation and insufficient renewable energy utilization. Therefore, this study provides an efficient multi-timescale regulation strategy for DNs based on active and passive resources combined. First, the day-ahead regulation model is constructed to minimize the total operating cost in a day for DNs. It aims to determine the on-load tap changer (OLTC) and capacitor bank (CB) switching schemes and consider them as the constraints for intraday regulation by power flow unification. Then, an intraday source and load uncertainty model is considered, which aims to cope with the problems of inaccuracies in the day-ahead source and load prediction. Based on this, the objective function of the intraday regulation model is set. It aims to minimize the deviation from the total day-ahead cost and then ensure the optimal system economy and determine the intraday new energy and energy storage system (ESS) short-time action scheme. Finally, the example results show that the proposed scheme can achieve the maximum utilization of renewable energy and improve the low-carbon economic operation of the whole system. [ABSTRACT FROM AUTHOR]

This paper introduces a Fuzzy Logic Controller designed for an on-load tap changer within medium voltage distribution systems with bulk penetration of Distributed Energy Resources. As the on-load tap changer remains one of the most essential forms of voltage regulation in medium voltage distribution networks, improving its operation is a cost-effective response to the emerging voltage violations caused by intermittent generation during the early stages of the energy system transformation. Software-in-the-loop simulations were conducted to validate the effectiveness of the proposed algorithm compared to the conventional methods. A modified CIGRE Medium Voltage Distribution Network Benchmark in European Configuration was modelled while the controller code developed in Python 3.12 was running on a PC, both coupled in a real-time closed-loop environment. The analyses showed that the proposed algorithm managed to reduce overvoltage from 7.02% to 4.85% in the benchmark network, thus demonstrating that the algorithm is efficient and ready for on-field implementation. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

On-Load Tap-Changer (OLTC) is the only core equipment in the ultra-high voltage (UHV) converter transformer that moves frequently, and flexible connection structure (FCS) is the moveable actuating part of the vacuum interrupter drive mechanism of OLTC. Minimizing the transient stress during the movement of FCS is essential for prolonging its fatigue life, thus is pursued by optimizing the shape of the flexible sheet in this paper. Peak transient stress of FCS is defined as the optimization objective, and eight geometrical parameters controlling the shape of flexible sheet are defined as the optimization variables. A progressive three-stage shape optimization strategy is proposed by combing four techniques: Multi-body Dynamic (MBD), Finite Element Analysis (FEA), Correlation Coefficient Analysis (CCA) and Adaptive Single-objective Optimization (ASO). MBD analysis of the vacuum interrupter drive mechanism and FEA of the FCS are utilized for calculating the transient stress distribution. Spearman CCA is performed to quantitively determine the correlation and sensitivity between the optimization variables and the optimization objective. Shape optimization of FCS using ASO is carried out, and results show that the stress concentration is basically eliminated and the peak transient stress decrease by 34.35% after shape optimization. Further analysis of the FCS with multi-layered flexible sheet is conducted, again demonstrating the effectiveness of the shape optimization on minimizing transient stress.

The paper proposes a new local method of controlling the on-load tap changer (OLTC) of a transformer to mitigate negative voltage phenomena in low-voltage (LV) networks with a high penetration of photovoltaic (PV) installations. The essence of the method is the use of the load compensation (LC) function with settings determined via artificial neural network (ANN) algorithms. The proposed method was compared with other selected local methods recommended in European regulations, in particular with those currently required by Polish distribution system operators (DSOs). Comparative studies were performed using the model of the 116-bus IEEE test network, taking into account the unbalance in the network and the voltage variation on the medium voltage (MV) side.

Power transformers are an essential part of the power grid. They have a relatively low rate of failure, but removing the consequences is costly when it occurs. One of the elements of power transformers that are often the reason for shutting down the unit is the on-load tap changer (OLTC). Many methods have been developed to assess the technical condition of OLTCs. However, they require the transformer to be taken out of service for the duration of the diagnostics, or they do not enable precise diagnostics. Acoustic emission (AE) signals are widely used in industrial diagnostics. The generated signals are difficult to interpret for complex systems, so artificial intelligence tools are becoming more widely used to simplify the diagnostic process. This article presents the results of research on the possibility of creating an online OLTC diagnostics method based on AE signals. An extensive measurement database containing many frequently occurring OLTC defects was created for this research. A method of feature extraction from AE signals based on wavelet decomposition was developed. Several machine learning models were created to select the most effective one for classifying OLTC defects. The presented method achieved 96% efficiency in OLTC defect classification. [ABSTRACT FROM AUTHOR]

The introduction of a large number of photovoltaic systems to distribution systems has increased the complexity of the voltage profile. It is thus necessary to manage voltage at a higher system level. For this purpose, the voltage profile of the distribution system can be calculated using state estimation and the voltage can be controlled based on the estimated values. Many methods for estimating voltage profiles using state estimation have been developed. However, the estimation accuracy of voltage profiles required for proper voltage control has not been discussed. If the assumed required estimation accuracy is too high, then more meters than necessary will be installed, unnecessarily increasing costs. Conversely, if the assumed required estimation accuracy is too low, voltage control equipment will not operate properly, and voltage violations may occur. Thus, it is important to determine the required estimation accuracy of voltage profiles for proper voltage control. In this paper, the estimation error of the voltage profile is expressed using a probability density function, and the estimation accuracy of voltage profiles required for proper voltage control is examined. A numerical case study was performed on a distribution network model with 2160 consumers, and revealed the following. To prevent voltage violations, an estimation accuracy of voltage profile that is approximately 10 times lower than that of the estimation accuracy based on current measurement equipment data is sufficient. To minimize the number of tap operations, an estimation accuracy needs to be improved by 70% compared with the estimation accuracy based on current measurement equipment data. [ABSTRACT FROM AUTHOR]

Due to the non-deterministic and probabilistic qualities of renewable energy resources (RER), integrating these resources has posed a challenge for energy companies and government policy planners. Hybrid power systems require frequent voltage regulation to address the changes in renewable generation and facilitate voltage management. This leads to an increment in the operating time of the tap changer in the power transformer, thus resulting in accelerated degradation of the on-load tap changer (OLTC) device. The primary focus of this paper is to optimally manage the penetration level of renewable generation while maintaining the minimum time for proper operation of voltage regulation devices. Accordingly, the major contribution of this paper is to address the switching cycle issues of the on-load tap-changing transformer. Initially, a framework is proposed to optimize the location and size of renewable power generation using a multi-objective cuckoo search optimization algorithm. The main goal here is to reduce power losses and tap changer operations while improving the system voltage profile under different levels of renewable energy penetration. The optimization problem takes into consideration the fluctuating nature of wind speed and solar irradiance for sunny and cloudy days over 24 h. The framework has been applied to the IEEE 57-bus and 118-bus systems with different load levels. The performance of the proposed approach has been benchmarked by comparing it with the genetic optimization algorithm to identify the higher potential buses for renewable generation allocation. The cuckoo search algorithm (CSA) shows outstanding results in reducing the number of switching cycles to about (37 – 43) % whereas the genetic algorithm (GA) only (17 – 18). In this sense, the number of changes in tap position when using the CSA is 1956 for sunny days and 1763 for cloudy days compared to GA 2558 for sunny days and 2547 for cloudy days. The voltage profiles for both algorithms are maintained in the range of (1.06 and 0.94) per unit. The results affirm the effectiveness of the proposed approach in determining the optimal placement and size of RER with voltage profile improvement and reduction in the switching cycles of OLTC. [ABSTRACT FROM AUTHOR]

Introducing solar and wind power into distribution networks (DNs) is an important initiative to promote the cleanliness and low-carbonization operation of DNs. However, the source and load outputs are uncertain in DNs, which will lead to problems of inaccurate regulation and insufficient renewable energy utilization. Therefore, this study provides an efficient multi-timescale regulation strategy for DNs based on active and passive resources combined. First, the day-ahead regulation model is constructed to minimize the total operating cost in a day for DNs. It aims to determine the on-load tap changer (OLTC) and capacitor bank (CB) switching schemes and consider them as the constraints for intraday regulation by power flow unification. Then, an intraday source and load uncertainty model is considered, which aims to cope with the problems of inaccuracies in the day-ahead source and load prediction. Based on this, the objective function of the intraday regulation model is set. It aims to minimize the deviation from the total day-ahead cost and then ensure the optimal system economy and determine the intraday new energy and energy storage system (ESS) short-time action scheme. Finally, the example results show that the proposed scheme can achieve the maximum utilization of renewable energy and improve the low-carbon economic operation of the whole system.

This paper introduces a Fuzzy Logic Controller designed for an on-load tap changer within medium voltage distribution systems with bulk penetration of Distributed Energy Resources. As the on-load tap changer remains one of the most essential forms of voltage regulation in medium voltage distribution networks, improving its operation is a cost-effective response to the emerging voltage violations caused by intermittent generation during the early stages of the energy system transformation. Software-in-the-loop simulations were conducted to validate the effectiveness of the proposed algorithm compared to the conventional methods. A modified CIGRE Medium Voltage Distribution Network Benchmark in European Configuration was modelled while the controller code developed in Python 3.12 was running on a PC, both coupled in a real-time closed-loop environment. The analyses showed that the proposed algorithm managed to reduce overvoltage from 7.02% to 4.85% in the benchmark network, thus demonstrating that the algorithm is efficient and ready for on-field implementation.

This paper presents a novel fault diagnosis method for oil-immersed on-load tap changers (OLTC) to address the issue of limited diagnostic accuracy. The proposed method combines the analysis of mechanical vibration signals and high-frequency current signals from the contact pair, aiming to improve the precision of fault diagnosis. To begin with, an experimental platform was used to simulate the OLTC contact, enabling the collection of mechanical vibration signals and high-frequency current signals under different operational states. These signals underwent wavelet packet transform for denoising, followed by correlation analysis to investigate their interrelationships across various states. Features were then extracted and analyzed using ensemble empirical mode decomposition and the Hilbert–Huang transform. Subsequently, a support vector machine (SVM) was employed to analyze both the mechanical vibration signal and high-frequency current signal, facilitating the classification of the OLTC contact state. The results demonstrated that the joint analysis of electrical and mechanical signals provided a comprehensive representation of the actual contact state under different conditions. The SVM classification achieved an error below 10% in predicting the values of the two signal types, validating the efficiency and feasibility of the proposed fault diagnosis method for OLTC contacts. The findings presented in this paper offer valuable insights for on-site fault diagnosis of practical OLTCs. [ABSTRACT FROM AUTHOR]

This paper investigates voltage regulation in low voltage (LV) networks under different loading conditions of a supply network, with increased levels of distributed generation, and in particular with a diverse range of locational solar photovoltaic (PV) penetration. This topic has been researched extensively, with beneficial impacts expected up to a certain point when reverse power flows begin to negatively impact customers connected to the distribution system. In this paper, a voltage-based approach that utilizes novel voltage-based reliability indices is proposed to analyse the risk and reliability of the LV supply feeder, as well as its PV hosting capacity. The proposed indices are directly comparable to results from a probabilistic reliability assessment. The operation of the network is simulated for different PV scenarios to investigate the impacts of increased PV penetration, the location of PV on the feeder, and loading conditions of the MV supply network on the reliability results. It can be seen that all reliability indices improve with increased PV penetration levels when the supply network is heavily loaded and conversely deteriorate when the supply network is lightly loaded. Moreover, bus voltages improve when an on-load tap changer is fitted at the secondary trans-former which leads to better reliability performance as the occurrence and duration of low voltage violations are reduced in all PV scenarios. The approach in this paper is opposed to the conventional reliability assessment, which considers sustained interruptions to customers caused by failure of network components, and thus contributes to a comprehensive analysis of quality of service by considering transient events (i.e., voltage related) in the LV distribution network. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a coordination method for the voltage control devices based on optimal settings of the D-STATCOMs, on the load tap changer (OLTC) transformer and the distributed generations (DGs)-based renewable energy resources (RERs). The central controller is introduced to handle the active smart distribution network (SDN) problems to maintain the voltage profile within its permissible limits, minimize power losses in different operating conditions, and minimize the energy wastage from the distributed renewable energy resources. These problems are formulated as a multi-objective optimization problem. With increasing load demand and RERs in the distribution system, voltage coordination threatens real-time efficiency. In this research work, central controller-based Gorilla Troops optimization (GTO) algorithm is proposed to detect the optimum solutions for the voltage coordination problem. The load demand uncertainty and the stochastic nature of power generated from RERs (PV panels and wind turbines) are considered in the voltage coordination problem due to their significant effects on the operation and planning of the SDN. The proposed SDN has been represented based on the Internet of Things (IoT) communication protocol. It enhances the data and information transfer between the system-connected agents. A practical test system, NDEDC-24 bus radial distribution network from the North Delta Electrical Distribution Company and IEEE-33 node system are used to test and evaluate the proposed method. The results are compared with other well-known evolutionary methods. The proposed method obtains more accurate results than the other methods.

Nowadays, in low voltage electric distribution networks, the distribution network operators are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic prosumers. The intermittent nature of the prosumers, together with the degree of uncertainty of the requested and injected powers associated with all end-users from low voltage electric distribution networks, can cause voltage variations that violate the allowable limits. In this context, this paper developed an efficient and resilient expert system integrating rule-based reasoning applied to the on-load tap changer-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators—the penetration degree of the photovoltaic prosumers, the consumption evolution associated with the consumers, and the energy production of the photovoltaic systems—was performed to demonstrate the efficiency of the proposed expert system in a low voltage electric distribution network from a rural area belonging to a Romanian distribution network operator. The success rate of the expert system was 86.7% (65 out of 75 scenarios did not have voltage issues). All voltages were between the allowable limits in 100% of the time slots associated with the analysed period. For the other scenarios (representing 13.3%), voltages were inside the range [−10%, +10%] in at least 95% of the time slots. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The operating condition identification of on-load tap changer under actual service environment yields no desired effect. To solve this problem， the paper proposes an operating condition recognition method based on MSSST （multi-synchronous squeezing S transform） and RLCNN (reinforced lightweight convolution neural network) is proposed. In this method， the multi-synchronous squeezing S transform is firstly introduced into the field of power equipment condition monitoring and applied to analyze the vibration signal of on-load tap changer so that the two-dimensional time frequency characteristic of signal can be effectively depicted. In additional， the MobileNetv2 lightweight convolution neural network is fused with the Adaboost adaptive lifting mechanism， and a novel RLCNN model is proposed. Then the two-dimensional time frequency maps of vibration signal are regarded as the samples to train the model， which is used to judge the operating condition of on-load tap changer. Experimental results show that the method can accurately judge the different operating conditions of on-load tap changer. Compared with other identification methods， this method has a higher precision rate and better stability as well as practical engineering application value.

• A new comprehensive voltage stability index that characterized by minimal assumptions is formulated and suggested. • Develop a proposed index based on the most accurate transmission line model that can consider the impact of line length on voltage stability evaluation. • The new index takes into account the impact of off-load and on-load tap changer transformers that verified its accuracy by implementing some cases. Recently, voltage stability has become increasingly important because of the expansion and growing demands on power transmission networks. Several factors may contribute to the blackouts occurrence in power system, including severe voltage instability and insufficient power transfer capabilities. To avert voltage collapse in power grids, identifying the critical operating conditions with high precision is crucial. By representing a new index in this paper, the assessment of voltage stability within transmission networks can be undertaken. In contrast to other indices, the proposed index has least assumptions and can assess the voltage stability in power systems with significant precision. Afterward, the suggested index is broadened to encompass the influence of on-load tap changers (OLTC). In order to attain this, the OLTC model has been developed using a precise implementation of mathematical equations, enabling an accurate evaluation of the impact of tap changer variations on voltage stability. To ascertain the efficacy of the proposed index, an evaluation has been conducted on a two-bus as well as 9-and 30-bus transmission test systems under various operational scenarios. The simulation outcomes suggest the superior effectiveness of the suggested index compared to other well-established indices. These results illustrate its ability to accurately assess the impacts of OLTC. [ABSTRACT FROM AUTHOR]

The introduction of a large number of photovoltaic systems to distribution systems has increased the complexity of the voltage profile. It is thus necessary to manage voltage at a higher system level. For this purpose, the voltage profile of the distribution system can be calculated using state estimation and the voltage can be controlled based on the estimated values. Many methods for estimating voltage profiles using state estimation have been developed. However, the estimation accuracy of voltage profiles required for proper voltage control has not been discussed. If the assumed required estimation accuracy is too high, then more meters than necessary will be installed, unnecessarily increasing costs. Conversely, if the assumed required estimation accuracy is too low, voltage control equipment will not operate properly, and voltage violations may occur. Thus, it is important to determine the required estimation accuracy of voltage profiles for proper voltage control. In this paper, the estimation error of the voltage profile is expressed using a probability density function, and the estimation accuracy of voltage profiles required for proper voltage control is examined. A numerical case study was performed on a distribution network model with 2160 consumers, and revealed the following. To prevent voltage violations, an estimation accuracy of voltage profile that is approximately 10 times lower than that of the estimation accuracy based on current measurement equipment data is sufficient. To minimize the number of tap operations, an estimation accuracy needs to be improved by 70% compared with the estimation accuracy based on current measurement equipment data.

Power transformers are an essential part of the power grid. They have a relatively low rate of failure, but removing the consequences is costly when it occurs. One of the elements of power transformers that are often the reason for shutting down the unit is the on-load tap changer (OLTC). Many methods have been developed to assess the technical condition of OLTCs. However, they require the transformer to be taken out of service for the duration of the diagnostics, or they do not enable precise diagnostics. Acoustic emission (AE) signals are widely used in industrial diagnostics. The generated signals are difficult to interpret for complex systems, so artificial intelligence tools are becoming more widely used to simplify the diagnostic process. This article presents the results of research on the possibility of creating an online OLTC diagnostics method based on AE signals. An extensive measurement database containing many frequently occurring OLTC defects was created for this research. A method of feature extraction from AE signals based on wavelet decomposition was developed. Several machine learning models were created to select the most effective one for classifying OLTC defects. The presented method achieved 96% efficiency in OLTC defect classification.

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper analyzes the effect of sliding speed on the electrical conductivity and friction properties of the contact pair of an on-load tap changer (OLTC). Reciprocating current-carrying tribological tests were carried out on a rod–plate–copper–tin–copper contact galvanic couple at different sliding speeds in air and insulating oil media. The results show that as the sliding speed increases from 24 mm/s to 119 mm/s, the average contact resistance in air increases from 0.2 Ω to 0.276 Ω, and the average contact resistance in insulating oil also increases from 0.2 Ω to 0.267 Ω. At 119 mm/s, the maximum contact resistance in insulating oil reaches 0.3 Ω. The micro-topography images obtained by scanning electron microscopy show that with the increase in sliding speed, the wear mechanisms in the air are mainly abrasive wear and adhesive wear, and the wear mechanisms in oil are mainly layered wear and erosion craters; high sliding speed and arcing promote contact surface fatigue and crack generation. X-ray photoelectron spectroscopy was used to analyze the surface. The copper oxide in the air and the cuprous sulfide in the insulating oil cause the surface film resistance, and the total contact resistance increases accordingly. In addition, the test shows that 119 mm/s in air and 95 mm/s in insulating oil are the speed thresholds. Below these speed thresholds, the increase in contact resistance is mainly caused by mechanical wear. Above these thresholds, the increase in contact resistance is mainly caused by arc erosion and chemical oxidation processes. Non-mechanical factors exacerbate the deterioration of the contact surface and become the main factor for the increase in contact resistance. [ABSTRACT FROM AUTHOR]

Power quality and reliability are of great importance in the modern world, whether it be the power generated by the power utilities or the power consumed by the customer respectively. They need these supplies to be at its optimum value so that the cost is effective, and the safety of devices assured otherwise problems such as overvoltage, under-voltage, and voltage sags caused by disturbances in the power supply could be disastrous. On-load tap changers (OLTC) have therefore been used since the inception of electrical engineering. The main function of the OLTC is to change the turns of the transformer winding so that the voltage variations are limited without interrupting the secondary current.The major idea is that the electronic switches and other smart systems provide more controllability during the tap changing process, unlike mechanical switches.This paper presents an alternative design and implementation of a low-cost solid-state OLTC and employs a control strategy that is microcontroller-based, ensuring the desired flexibility and controllability required in programming the control algorithms.It eliminates the limitations of both mechanical and hybrid OLTCs (arcing, slow response time, losses) and is user-friendly (provides an effective communication medium). Voltage regulation is achieved by varying the turns of the transformer winding whiles it is energized, supplying load current and with the tap selection carried out on the primary side. Therefore, this approach provides a less expensive system but ensures the efficiency and reliability of voltage regulation.

This paper investigates voltage regulation in low voltage (LV) networks under different loading conditions of a supply network, with increased levels of distributed generation, and in particular with a diverse range of locational solar photovoltaic (PV) penetration. This topic has been researched extensively, with beneficial impacts expected up to a certain point when reverse power flows begin to negatively impact customers connected to the distribution system. In this paper, a voltage-based approach that utilizes novel voltage-based reliability indices is proposed to analyse the risk and reliability of the LV supply feeder, as well as its PV hosting capacity. The proposed indices are directly comparable to results from a probabilistic reliability assessment. The operation of the network is simulated for different PV scenarios to investigate the impacts of increased PV penetration, the location of PV on the feeder, and loading conditions of the MV supply network on the reliability results. It can be seen that all reliability indices improve with increased PV penetration levels when the supply network is heavily loaded and conversely deteriorate when the supply network is lightly loaded. Moreover, bus voltages improve when an on-load tap changer is fitted at the secondary trans-former which leads to better reliability performance as the occurrence and duration of low voltage violations are reduced in all PV scenarios. The approach in this paper is opposed to the conventional reliability assessment, which considers sustained interruptions to customers caused by failure of network components, and thus contributes to a comprehensive analysis of quality of service by considering transient events (i.e., voltage related) in the LV distribution network.

The increasing use of photovoltaics (PVs) in distribution systems owing to the low-carbon policy has given rise to the need for various technological changes. In particular, the operation of on-load tap changers (OLTCs) has attracted attention. In traditional distribution systems, the OLTC operates via a line-drop compensator (LDC), which focuses on the load to solve the low-voltage problem; however, the problem of over-voltage caused by PVs persists. Currently, a method for operating an OLTC using the measured voltage is being researched; however, solving the voltage problem for several feeders connected to a main transformer (MT) is not viable. Therefore, this study proposes an OLTC operation method to address the feeder with the largest voltage problem depending on the direction of power flow. The proposed method selects a point where the OLTC operates using the difference between the measured and reference voltages. Setting the reference voltage can solve the problem that occurs due to the direction of power flow. Finally, the effectiveness of the proposed method is verified via case studies. Based on the results, we can conclude that the proposed method effectively solves the voltage problem, and an increase in hosting capacity can be expected. [ABSTRACT FROM AUTHOR]

As aerospace, electrified railway, weapon equipment manufacturing, and other fields have leapt forward, the operating environment of current-carrying friction pairs is becoming increasingly severe, and research on the current-carrying friction and wear theory and its vital technologies are progressively in demand. This study summarizes the relevant research on the current-carrying friction and wear. In this study, the essential characteristics and classification of current-carrying friction and wear are summarized, the effect of working parameters on current-carrying friction and wear performance is clarified, and the generation mechanism, failure mechanism, and factors of current-carrying friction and wear are emphatically investigated. Moreover, the mechanism of arc generation and the effect of environmental conditions and surface facial masks on the friction and wear process are summarized. This paper also introduces the preparation technology of a conductive wear-resistant self-lubricating material, the main factors affecting the conductive wear-resistant property of the coating, and the action mechanism. The simulation and prediction results of the current-carrying friction and wear temperature field and the wear amount are presented. Finally, the problems in the current-carrying friction and wear research are classified, and future research directions in this field are proposed. The future's critical development and improvement directions are also proposed from the aspects of developing coating quality evaluation equipment, optimizing the coating quality, and studying the coating self-lubricating mechanisms. [ABSTRACT FROM AUTHOR]

In this study, a multi-objective optimization method is proposed to solve day-ahead voltage control problems in distribution systems. The main purpose is to determine the optimal schedule for on-load tap changer (OLTC) settings at the sub-station and switched capacitors (SC) based on day-ahead load forecasting. The optimization criteria presented in this study include: (1) minimizing the voltage deviations at the main transformer bus, and (2) minimizing the total power loss. In the proposed method, the Pareto front and Manhattan distance are combined as indices to assess and select the best solution. Multi-Pareto optimality is used to improve the performance of the proposed scheduling strategy. In this study, the network components were modeled by the DIgSILENT Power Factory 15.2, while the multi-objective optimization algorithm was implemented on the MATLAB 2016a software package. Additionally, the effects of different distributed generation (DG) grid-connected points and operation scenarios on voltage control scheduling were examined. The efficiency and performance of the proposed method were verified using an IEEE 33 BUS test system. Compared with the local voltage level (LVL) and reactive power device control (RPDC) methods, the proposed method delivered percentage reductions in (1) voltage deviations at all buses, (2) voltage variations, (3) total system power loss, and (4) difference in values of up to 160.93%, 31.16%, 10.35%, and 434.34%, respectively. [ABSTRACT FROM AUTHOR]

The placement of the photovoltaic generation system (PVGS) and operation of the on-load tap changer (OLTC) should have great impacts on the system loss and voltage quality, which are the main concerns of the distribution operator. Considering these multiple evaluation indices and other constraints, this paper proposed a substation-based optimal PVGS placement and OLTC operation model. The objective function that was used to evaluate the optimal PVGS placement and OLTC operation consists of a minimization of system loss and voltage quality. The model's constraints contain the voltage and line flow limits, voltage deviations, voltage unbalance, etc. Uncertainties of the load and irradiance are also included in the model. A nondominated sorting genetic algorithm II (NSGA II) is used to solve this multi-objective optimization problem. Comparisons of the substation-based and feeder-based planning are also studied in this paper. The test results demonstrate the substation-based planning could obtain a better solution. [ABSTRACT FROM AUTHOR]

The increasing adoption of distributed energy resources, such as rooftop photovoltaic (PV) systems and electric vehicles (EVs), can cause adverse impacts in distribution systems, including the growth in PV hosting capacity (PVHC) and the depreciation of on-load tap changers (OLTC) lifetime. To analyze the impacts of these technologies in the network over the day, the quasi-static time series (QSTS) can be used with a resolution capable of performing the start and end times of the EVs charging and PV generation profile to observe the role of the OLTC in the grid. This work investigates the QSTS PVHC from the integration of EVs residential charging and in a public charging station (PCS) considering an unbalanced medium voltage (MV) network with and without OLCT. For this, a set of random variables for EV behavior are used, such as home and PCS arrival and departure times. The model is developed in Python and OpenDSS in a Monte Carlo simulation. In addition, the results show that the PCSs along the grid can increase the QSTS PVHC in MV networks that do not have OLTC. However, when the distribution system presents OLTC, the number of tap changes increases significantly if many EVs use the PCS. This result can drive actions by the distribution network operator to consider the distance between PCSs and OLTCs. [ABSTRACT FROM AUTHOR]

The increasing Photovoltaic (PV) penetration in residential Low Voltage (LV) networks is likely to result in a voltage rise problem. One of the potential solutions to deal with this problem is to adopt a distribution transformer fitted with an On-Load Tap Changer (OLTC). The control of the OLTC in response to local measurements reduces the need for expensive communication channels and remote measuring devices. However, this requires developing an advanced decision-making algorithm to estimate the existence of voltage issues and define the best set point of the OLTC. This paper presents a decentralized data-driven control approach to operate the OLTC using local measurements at a distribution transformer (i.e., active power and voltage at the secondary side of the transformer). To do so, Monte Carlo simulations are utilized offline to produce a comprehensive dataset of power flows throughout the distribution transformer and customers' voltages for different PV penetrations. By the application of the curve-fitting technique to the resulting dataset, models to estimate the maximum and the minimum customers' voltages are defined and embedded into the control logic to manage the OLTC in real time. The application of the approach to a real UK LV feeder shows its effectiveness in improving PV hosting capacity without the need for remote monitoring elements. [ABSTRACT FROM AUTHOR]

Nowadays, in low voltage electric distribution networks, the distribution network operators are encountering a high number of connected small-scale distributed generation units, mainly photovoltaic prosumers. The intermittent nature of the prosumers, together with the degree of uncertainty of the requested and injected powers associated with all end-users from low voltage electric distribution networks, can cause voltage variations that violate the allowable limits. In this context, this paper developed an efficient and resilient expert system integrating rule-based reasoning applied to the on-load tap changer-fitted transformer to improve the efficiency of the voltage control in the PV-rich LV EDNs. An in-depth analysis based on 75 scenarios, resulting from the combinations of three indicators—the penetration degree of the photovoltaic prosumers, the consumption evolution associated with the consumers, and the energy production of the photovoltaic systems—was performed to demonstrate the efficiency of the proposed expert system in a low voltage electric distribution network from a rural area belonging to a Romanian distribution network operator. The success rate of the expert system was 86.7% (65 out of 75 scenarios did not have voltage issues). All voltages were between the allowable limits in 100% of the time slots associated with the analysed period. For the other scenarios (representing 13.3%), voltages were inside the range [−10%, +10%] in at least 95% of the time slots.

[Display omitted] • MBD and FEA are combined to calculate the transient stress distribution. • CCA and ASO are combined to obtain the optimal shape. • Stress concentration is eliminated and the peak stress decrease by 34.35%. • The FCS with multi-layered flexible sheet is further analyzed. On-Load Tap-Changer (OLTC) is the only core equipment in the ultra-high voltage (UHV) converter transformer that moves frequently, and flexible connection structure (FCS) is the moveable actuating part of the vacuum interrupter drive mechanism of OLTC. Minimizing the transient stress during the movement of FCS is essential for prolonging its fatigue life, thus is pursued by optimizing the shape of the flexible sheet in this paper. Peak transient stress of FCS is defined as the optimization objective, and eight geometrical parameters controlling the shape of flexible sheet are defined as the optimization variables. A progressive three-stage shape optimization strategy is proposed by combing four techniques: Multi-body Dynamic (MBD), Finite Element Analysis (FEA), Correlation Coefficient Analysis (CCA) and Adaptive Single-objective Optimization (ASO). MBD analysis of the vacuum interrupter drive mechanism and FEA of the FCS are utilized for calculating the transient stress distribution. Spearman CCA is performed to quantitively determine the correlation and sensitivity between the optimization variables and the optimization objective. Shape optimization of FCS using ASO is carried out, and results show that the stress concentration is basically eliminated and the peak transient stress decrease by 34.35% after shape optimization. Further analysis of the FCS with multi-layered flexible sheet is conducted, again demonstrating the effectiveness of the shape optimization on minimizing transient stress. [ABSTRACT FROM AUTHOR]

Silver sulphide corrosion is a recently identified failure mechanism of transformer onload tap changers (OLTC). The corrosive sulphur in transformer oil reacts with the silver coated components of OLTC tap selector and forms silver sulphide films. During OLTC operation, the silver sulphide flakes can be detached from the tap selector and mix with the transformer oil. The silver sulphide is a semi conductive material. As a result, the dielectric strength in the transformer oil around the OLTC silver coated contacts or elsewhere in the transformer, wherever the semi conductive particles travel, will be reduced. Eventually, due to either high electric field stress or aged oil with a low dielectric strength, oil breakdown can occur between adjacent contacts. This can cause a catastrophic failure of the OLTC and quite often the tapping winding as well. Since such failures affect the transformer reliability, utilities are interested in methods of detecting and mitigating silver sulphide corrosion on OLTCs. This paper presents a risk assessment criterion to identify the degree of significance of silver sulphide corrosion in transformers using existing diagnostic techniques. [ABSTRACT FROM AUTHOR]

The on-load tap changer is critical for voltage regulation, however, its voltage regulation philosophy is suitable for one-directional power flow power systems. Since distributed generators introduce bidirectional power flow, the conventional operation of the on-load tap changer will be highly impacted, resulting in high voltage magnitudes that exceed acceptable limits, frequent voltage magnitude fluctuations, and the increase in overall reactive power supply when distributed generators start absorbing/injecting reactive power. Therefore, an adaptive control system is proposed on this paper that alters the existing voltage regulation philosophy of the on-load tap changer and also coordinate the voltage regulation capabilities of distributed generators with those of the on-load tap changer for optimal overall voltage regulation and the reduction of reactive power that flows through the power system, enhancing the power factor thereof. The proposed control system will change the centralized, and single-variable busbar voltage monitoring technique of the conventional philosophy with a decentralized, and multi-variable strategy that controls voltage based on the average voltage of the entire distribution network. The control system will calculate the on-load tap changer and distributed generators setpoints based on the overall average network voltage, average voltage deviation from nominal voltage, generators points of connection voltage and the total reactive power that flows through the power transformer. The control system was tested on a 22kV network modelled in MATLAB SIMULINK and the results attained revealed that the proposed multi-stage control system can successfully control voltage and simultaneously improve power factor.

The South African power distribution network is characterized by long power distribution lines with low short circuit capacity, and when distributed generation is introduced to these lines, voltage magnitudes are severely impacted. The existing voltage regulation methods of the on-load tap changer and step voltage regulator cannot successfully regulate voltage in long distribution lines with distributed generation since their control philosophy was designed for networks without distributed generation. Therefore, a dynamic system is proposed in this paper that coordinates the on-load tap changer, step voltage regulator, distributed generators, and the battery energy storage system to control voltage in long distribution lines with distributed generation. Their coordination will be based on response time and robustness. Unlike the conventional method, the proposed novel system will calculate a reference voltage that the on-load tap changer and the step voltage regulator must follow, based on the real time average voltage of the section of the network they each regulate. The system will also control the charging and discharging of a battery energy storage system based on the point of connection voltage and the average voltage of the feeder which it is connected to. Reactive power from distributed generators will also be used to enhance voltage regulation and refine the network power factor. When voltage magnitudes cannot be successfully brought within acceptable range, the proposed scheme will decrease the active power produced by distributed generators. The proposed system is examined on a South African 22kV network built in Matlab/Simulink.

The on-load tap changer (OLTC) is one of the key components of converter transformer. The energy generated during tap switching process of the OLTC will cause thermal expansion and surging of the insulating oil in the chamber, resulting in the mis-operation of protective relay and threatening the safe and stable operation of the power system as well. Therefore, taking the typical dual-transition resistance-type OLTC as an example, a numerical modeling method of OLTC oil flow surging based on the realizable k-ε model is proposed, and the fluid simulation model is established based on the FLUENT software. The quantitative relationship between the OLTC transition resistance value and the oil velocity and oil pressure at the top of the oil chamber is analyzed, that is, the smaller the transition resistance, the greater the oil flow velocity and oil pressure during switching. In addition, an equivalent experimental platform is built to carry out the static action characteristic experiment of OLTC oil flow relay, the corresponding relationship between the change range of oil pressure at the top of the chamber, and the oil velocity under typical value (1.5 m/s, 2.0 m/s, and 2.5 m/s) are revealed. Based on which, the optimization suggestions on the protection relay threshold configuration of OLTC oil velocity and oil pressure are put forward.

With the proliferation of electric vehicles (EVs), the supporting facilities and infrastructure become new components in conjunction with conventional electrical appliances. These novel appliances, e.g., charging piles and energy storage devices, bring new features as well as challenges to the existing power grid. To enhance the accuracy of mechanical fault identification for on-load tap changers (OLTCs) in smart grid with EVs, a feature selection method for OLTC mechanical fault identification is proposed in this paper. This method relies on the multi-feature fusion and the joint application of the K-nearest neighbors algorithm (KNN) and the improved whale optimization algorithm (IWOA). By multi-feature fusion, the high-dimensional set of time-domain and frequency-domain characteristics as well as energy and composite multi-scale permutation entropy can be constructed. As a result, the maximum correlation minimum redundancy (mRMR) principle can be used to screen the sensitive feature subsets. Finally, IWOA is used to optimize the sensitive feature subsets, and KNN is used to classify the different types of optimal feature subsets. The experimental results show that the proposed method is at least 8% more accurate than the existing methods. The high-accuracy nature of the proposed method can accelerate the promotion of EVs and the establishment of intelligent transportation environments. [ABSTRACT FROM AUTHOR]

The low voltage (LV) network's constraints are prone to violations with the introduction of distributed energy resources at the customer vicinity. This study assesses the technical aspects of the realistic Finnish distribution network with varying photovoltaic (PV) penetration and quantifies the hosting capacities (HCs) of different regions. Moreover, to maximize the network's HC, having the overvoltage issue, different voltage control strategies are employed comprising on-load tap changer (OLTC), reactive power control (RPC) of inverters, network reinforcement (NR), and hybrid approaches. HC relative to different country-specific over-voltage limits are defined and the best voltage control technique is assessed, utilizing the stochastic approach of Monte Carlo simulations to model the uncertainty in the LV network's probabilistic variables. Moreover, combined medium voltage (MV)/LV network simulations are conducted to compare with the LV only simulations results. Technically, NR is the best approach to maximize the HC of a particular region but economically it is not proven a feasible one. The results presented that the OLTC employment will maximize the PV penetration if the overvoltage limit derived from EN 50160 is implemented and doubles the HC in the stricter-voltage-limits' scenarios, which can be maximized by the RPC inclusion in cohesion with OLTC. Moreover, RPC only strategy can be employed in the cases of low PV penetration scenarios, when OLTC will be proven the more expensive option. As the voltage violation limit becomes stricter, the hybrid approach of OLTC and RPC will be the best strategy.

The on-load tap changer (OLTC) switching arc will affect the life of the contact, so it is necessary to test its working condition. Based on DQ coordinate transformation, fundamental wave component extraction, and wavelet algorithm, proposed an OLTC arc detection method based on energy conservation theory in this paper. Used the fundamental wave component extraction algorithm extracted the transformer excitation parameters, and established the OLTC equivalent circuit by combining the Habedank arc model. Compared the differences between the follow effect and frequency calculation of simulated and measured waveforms, which were caused by the five orthogonal transformation algorithms, including Transport-Delay, Hilbert Transformation, Inverse Park Transformation, SOGI and Improved SOGI. The DQ coordinate transformation based on the Transport-Delay orthogonal converter is determined to calculate the active power of each part of the circuit. According to the principle of energy conservation, obtained the data of arcing loss under nine simulated conditions. Based on the simulation circuit, built the OLTC prototype and dSPACE hardware in loop simulation platform, and measured three load conditions. The sampling signal was filtered by the wavelet algorithm. Considering the measurement and calculation errors, the simulation and measured results show that the actual arcing power has a consistent change with the calculated value between different working conditions, and the maximum difference between simulation results and measured results is thirty times and ten times. It can distinguish the difference of arcing energy of diverter switch under different working conditions and has the measurability. Meanwhile, it verifies the effectiveness of this study, hoping to provide a theoretical basis for developing OLTC on-line contact detection system.