Distribution Transformers Research Articles

A review of health index-based condition assessment techniques for power and distribution transformers

In this paper, the most significant diagnostic parameters of transformers and the corresponding asset management strategies adopted by the leading power utilities of various countries are discussed. The analytical techniques used include Monte Carlo simulations (MCSs), fuzzy inference systems, neuro-fuzzy systems, regression analysis, multi-criterion analysis (MCA) and so on. These techniques incorporate information related to transformer design and fabrication, operation history and maintenance, visual inspection and various diagnostic tests and measurements. The health assessment methodologies for power and distribution transformers may require improvement. Cost-effective techniques involving few critical parameters have to be used for distribution transformers. Suitable communication technologies need to be deployed for remote monitoring and assessment. Appropriate interfacing software can be developed for analysis. There are many issues and operating conditions associated with Indian transmission and distribution systems, which call for the adaptation of the discussed techniques for their effective use.

Grid-Forming Control of Three-Phase and Single-Phase Converters Across Unbalanced Transmission and Distribution Systems

In this work, we investigate grid-forming control for power systems containing three-phase and single-phase converters connected to unbalanced distribution and transmission networks, investigate self-balancing between single-phase converters, and propose a novel balancing feedback for grid-forming control that explicitly allows to trade-off unbalances in voltage and power. We develop a quasi-steady-state power network model that allows to analyze the interactions between three-phase and single-phase power converters across transmission, distribution, and standard transformer interconnections. We first investigate conditions under which this general network admits a well-posed kron-reduced quasi-steady-state network model. Our main contribution leverages this reduced-order model to develop analytical conditions for stability of the overall network with grid-forming three-phase and single-phase converters connected through standard transformer interconnections. Specifically, we provide conditions on the network topology under which (i) single-phase converters autonomously self-synchronize to a phase-balanced operating point and (ii) single-phase converters phase-balance through synchronization with three-phase converters. Moreover, we establish that the conditions can be relaxed if a phase-balancing feedback control is used. Finally, case studies combining detailed models of transmission systems (i.e., IEEE 9-bus) and distribution systems (i.e., IEEE 13-bus) are used to illustrate the results for (i) a power system containing a mix of transmission and distribution connected converters and, (ii) a power system solely using distribution-connected converters at the grid edge.

Analisis Penggunaan Transformator Sisipan Untuk Mengatasi Rugi Tegangan dan Pembebanan Lebih

On the JD267 distribution transformer with a capacity of 100 kVA at the Kalibaru feeder on the PT PLN (Persero) ULP Genteng experienced overloading at WBP (88.03%) and high voltage losses. The magnitude of the load exceeds 80% of the standard transformer capacity and is in the bad category (load >= 80%) according to Table I. SE No. 0017.E/DIR/2014, related to transformer loading percentage. Meanwhile, the voltage loss of the JD267 transformer when the WBP is in Phase R is 19.05%, Phase S is 17.08%, and Phase T is 18.33%. This exceeds the voltage tolerance limit in SPLN 1:1995 that the voltage is not allowed to exceed +5% and -10% of the PLN standard voltage, namely 220 V. To handle this problem, PT. PLN (Persero) ULP Genteng carried out the installation of insert transformers by estimating load growth in the next 5 years using the Least Square method. After the addition of the insert transformer, the loading on the JD267 distribution transformer fell to 58.93% on WBP. Meanwhile, the magnitude of the JD267 transformer voltage loss when the WBP after insertion in the R Phase decreases to 0.84%, the S Phase is 1.04%, and the T Phase is 1.63%, and when the LWBP after insertion in the R Phase decreases to 0 .76%, S Phase 0.30%, and T Phase 0.6%. Based on the data above, adding an insert transformer can improve the loading percentage on the transformer and reduce voltage losses that occur at the end voltage of the transformer.

Reliability Comparison of Rural & Urban LVDS Networks with Corresponding HVDS Networks Including Substation Reliability

This paper mainly determines the comparison of reliability of an existing rural area & urban area LVDS (low voltage distribution system) with their respective proposed high voltage distribution system (HVDS) and also including their 33/11 kV Substation. Ring main substation and single bus bar substation configuration are considered for urban and rural distribution systems respectively. The reliability of ring bus substation used in urban area is more as compared to single bus substation used in rural area. The load point reliability indices are calculated considering both substation reliability indices and radial feeder indices. The substation failure rate is calculated by considering overlapping outages approach and whereas the radial feeder indices are calculated by using cut set approach. Further, the LVDS Network is converted into the HVDS Network by replacing a high rating distribution transformer (DTR) supplying to a group of customers with Large in number with multiple small rating distribution transformers near to consumer terminals with less number of customers in each group. This conversion leads to Minimum length of LT Lines in HVDS Which results in improving voltage profile, reliability and efficiency. In this paper the disconnecting switches and alternative supply are also considered on both LVDS and HVDS Networks in the calculation of the reliability of to assess the reliability of the radial distribution system (FMEA)Failure mode effect analysis is used. This study uses a LVDS and HVDS system, and uses an alternative power source and disconnectors, to determine reliability indices of the rural area network and urban area network distribution system. In this paper the important distribution reliability indices to reduce system average interruption durations (SAIDI), Energy Not Supplied (ENS) and ASAI for LVDS and corresponding HVDS are calculated. The research idea is proposed on a Indian practical networks.

Energy consumption analysis of power grid distribution transformers based on an improved genetic algorithm

With the promotion of energy transformation, the utilization ratio of electrical power is progressively rising. Since electrical power is challenging to store, real-time production and consumption become imperative, imposing significant demands on the dependability and operational efficiency of electrical power apparatus. Suppose the load distribution among multiple transformers within a transformer network exhibits inequality. In such instances, it will amplify the total energy consumption during the voltage conversion process, and local, long-term high-load transformer networks become more susceptible to failures. In this article, we scrutinize the matter of transformer energy utilization in the context of electricity transmission within grid systems. We propose a methodology grounded on genetic algorithms to optimize transformer energy usage by dynamically redistributing loads among diverse transformers based on their operational status monitoring. In our experimentation, we employed three distinct approaches to enhance energy efficiency. The experimental findings evince that this approach facilitates swifter attainment of the optimal power level and diminishes the overall energy consumption during transformer operation. Moreover, it exhibits a heightened responsiveness to fluctuations in power demand from the electrical grid. Experimental results manifest that this technique can truncate monitoring time by 27% and curtail the overall energy consumption of the distribution transformer network by 11.81%. Lastly, we deliberate upon the potential applications of genetic algorithms in the realm of power equipment management and energy optimization issues.

A Stochastic Load Forecasting Approach to Prevent Transformer Failures and Power Quality Issues Amid the Evolving Electrical Demands Facing Utilities

New technologies, such as electric vehicles, rooftop solar, and behind-the-meter storage, will lead to increased variation in electrical load, and the location and time of the penetration of these technologies are uncertain. Power quality, reliability, and protection issues can be the result if electric utilities do not consider the probability of load scenarios that have not yet occurred. The authors’ approach to addressing these concerns started with collecting the electrical load data for an expansive and diverse set of distribution transformers. This provided approximately two-and-a-half years of data that were used to develop new methods that will enable engineers to address emerging issues. The efficacy of the methods was then assessed with a real-world test dataset that was not used in the development of the new methods. This resulted in an approach to efficiently generate stochastic electrical load forecasts for elements of distribution circuits. Methods are also described that use those forecasts for engineering analysis that predict the likelihood of distribution transformer failures and power quality events. 100% of the transformers identified as most likely to fail either did fail or identified a data correction opportunity. The accuracy of the power quality results was 92% while allowing for a balance between measures of efficiency and customer satisfaction.

GNSS/IMU/LiDAR fusion for vehicle localization in urban driving environments within a consensus framework

The continuous, reliable, and accurate acquisition of position information is a fundamental requirement for autonomous vehicles. It underpins perception, decision-making, and planning modules in automated driving systems. However, the performance of multi-modal sensors, including the Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), and LiDAR, typically found in autonomous vehicles, is easily influenced by complex environmental factors encountered in urban driving conditions. This creates challenges for existing localization algorithms. More specifically, while GNSS performs accurately in open-sky areas, it is susceptible to the multi-path effect. Although the IMU-based Inertial Navigation System (INS) provides continuous position data, it suffers from cumulative errors. LiDAR-based map-matching is highly effective when sufficient point cloud features are present but fall short in plain environments. To address these individual sensor deficiencies, we propose the application of a consensus framework for GNSS/IMU/LiDAR fusion, and it is able to be expanded for multi-modal sensor fusion. Our approach seeks to take advantage of the redundancy inherent in these sensor systems. Our method begins with the derivation of the INS mechanization and its error dynamics. Subsequently, based on the Consensus Kalman Filter (CKF), we establish a GNSS measurement node and a Normal Distribution Transformation (NDT) map-matching measurement node. These are designed to estimate position errors in the INS. To counter sensor measurement failure or degradation, we introduce an adaptation mechanism for the CKF. This ensures position accuracy and continuity by normalizing measurement quality across different measurement nodes. Finally, to validate our consensus-based localization framework, we conducted extensive real-world vehicle tests in urban driving conditions. The results have confirmed the superior accuracy and robustness of our approach, even in the face of individual sensor failure. In our experiments, the proposed method reduces the localization mean absolute error by around 17% compared to INS/map-matching fusion, and around 59% compared to INS/GNSS fusion while map-matching fails. While the GNSS and map-matching measurements contain large noises, our framework achieves at least approximately a 30% improvement compared to traditional methods.

Fuzzy logic applied to the diagnosis of technical conditions of distribution transformers

The distribution transformers are one of the most important elements for the operation of the distribution networks, considering their quantity and dispersion in the network, and that the failures cause great economic losses, both from the point of view of the transformer itself and of the cost of the energy left to serve. The technical condition of the distribution transformers depends on multiple external factors that influence the loss of useful life of the same, and therefore, it is necessary to relate them for a correct diagnosis. In the present work, a method based on fuzzy logic is developed for the diagnosis of distribution transformers, considering the international regulations that govern its operation. The resulting procedure was implemented using the fuzzy toolbox of MATLAB programming tools version 9.8 (R2020a). A random sample of transformers in three distribution circuits was evaluated, and the results correspond to that established in the IEEE C57.91 standard of 2011.

Analisa Susut Teknis Pada Transformator Distribusi Di Wilayah Kerja PT. PLN (Persero) ULP Bawean

Along with the development of the times, the need for electricity is very necessary. Electrical energy is one of the energy that is needed in using equipment that is related to electrical energy such as household, office and commercial industrial equipment that requires electrical energy. Bawean Island is one of the islands that requires a large amount of electricity due to the growing development of these sectors. With the rapid development of large-scale developments, the need for electricity needs to be increased in order to meet people's demands related to electricity needs. Technical losses are losses that occur for technical reasons where energy is reduced by turning into heat or heat energy. Basically technical losses occur based on energy losses in components caused by errors in the components themselves. Technical losses that occur in distribution transformers are common. In principle, losses always occur because efficiency cannot be 100%. Energy is lost along with distribution from upstream to downstream of distribution transformers. Based on the formulation of the problem taken, the researchers calculated losses at neutral currents, copper losses, total losses, output power and total losses in the form of prices. From the results of the conclusions above, it can be seen that the greater the current in the neutral of the transformer, the more losses that occur in the transformer.

Day-Ahead Operational Planning for DisCos Based on Demand Response Flexibility and Volt/Var Control

Considering the integration of distributed energy resources (DER) such as distributed generation, demand response, and electric vehicles, day-ahead scheduling plays a significant role in the operation of active distribution systems. Therefore, this article proposes a comprehensive methodology for the short-term operational planning of a distribution company (DisCo), aiming to minimize the total daily operational cost. The proposed methodology integrates on-load tap changers, capacitor banks, and flexible loads participating in demand response (DR) to reduce losses and manage congestion and voltage violations, while considering the costs associated with the operation and use of controllable resources. Furthermore, to forecast PV output and load demand behind the meter at the MV/LV distribution transformer level, a short-term net load forecasting model using deep learning techniques has been incorporated. The proposed scheme is solved through an efficient two-stage strategy based on genetic algorithms and dynamic programming. Numerical results based on the modified IEEE 13-node distribution system and a typical 37-node Latin American system validate the effectiveness of the proposed methodology. The obtained results verify that, through the proposed methodology, the DisCo can effectively schedule its installations and DR to minimize the total operational cost while reducing losses and robustly managing voltage and congestion issues.

New coordination framework for smart home peer-to-peer trading to reduce impact on distribution transformer

The emergence of distributed energy resources (DERs) is expected to result in an increase in the amount of power transmitted through the distribution power grid. If these DERs are not managed properly, the increased power transmission can cause faster degradation of distribution grid assets (pole-top transformers). To prevent this, measures can be taken to manage the DERs connected to a specific pole-top transformer. This paper presents a new coordination framework for home energy management system (HEMS)-integrated peer-to-peer (P2P) trading, with a focus on the impact of such trading on a Distribution Transformer. The proposed framework provides a comprehensive solution to manage the distribution of power within a smart grid environment by enabling HEMS to engage in P2P trading. This paper also examines optimal energy management in a smart neighborhood to minimize the total cost of energy usage. In addition, to prevent power peaks — that could create excessive power transmission and damage the distribution transformer, a cap within the flexibility bound of the household is placed on the total power households can draw/penetrate from/to the power grid. By optimizing P2P energy trading while considering the limitations of the distribution transformer, this approach enables a more efficient, reliable, and sustainable energy system.

Assessment of Load Losses Caused by Harmonic Currents in Distribution Transformers Using the Transformer Loss Calculator Software

Transformer load losses cause various adverse effects, such as derating, a decreased lifetime, and greenhouse gas emissions. In this paper, the load losses caused by non-linear loads on distribution transformers are analyzed. For this study, the load loss expressions provided by the IEEE Standard C57.110 and ANSI/UL 1561-1562 were adapted to the usual case where the transformer currents differ in each phase. The novel load loss expressions adapted from the IEEE Standard C57.110 were applied using the software known as the “Transformer Loss Calculator” (TLC), implemented with LabVIEW. For the application of new load loss expressions, carbon dioxide (CO2) emissions were determined by multiplying the load losses by the emission factors of each country. The experimental results are based on the recordings made by a FLUKE 435 Series II analyzer on the second of two 1000 kVA transformers, feeding real residential distribution networks with very differently distorted loads. An analysis of these transformers shows that the annual energy losses and CO2 emissions obtained from the adapted load loss expressions could be more than 5% of those determined by the original IEEE and ANSI Standard expressions. Due to these percentage loss and emission differences, it is advisable to use the TLC software in transformer monitoring instruments.

Electricity Theft Mitigation at Low Voltage Distribution End Using Indirect Matrix Converter

This paper presents the design and implementation of an indirect matrix converter for electricity theft mitigation at low voltage distribution network. The power distribution network saddle with the responsivity of delivering electricity to consumers are been face with electricity theft through meter bypassing and hook up connections, causing significant financial inflow problem to the utility company, particularly in a developing country. A step-down indirect matrix converter was designed and simulated with a frequency range of (10 – 20Hz) at the converter’s output. The analysis of the results favours the choose of 10Hz being the wort-case scenario to mitigate electricity with a total harmonic distortion (THD) of 204.99%. With different resistive and inductive loads, the effectiveness of the real-world system was investigated and the effects of lowering the frequency from 50Hz to 10Hz were observed and in particular make the electricity unusable. The proposed system is intended to be connected at the output of the distribution transformer to convert the power frequency to 10Hz and the other unit incorporated to the meter at the consumer end to convert their power frequency to 50Hz to make it usable. This system prevents unregistered clients from using the electricity, substantially lowering electricity theft and boosting the utility company's bottom line. In comparison to previous studies, the key advantage of matrix converters is that they don't require a DC-Link capacitor, making them more reliable and suitable for installation at the customer's premises.

Distribution Transformer Remaining Useful Life Estimation Considering Electric Vehicle Penetration

A major portion of a power system's asset portfolio comprises distribution transformers on residential premises. The rapid and massive acceptance of electric vehicles is posing challenges for distribution transformers to operate over their expected lifespan. This work proposes a four-layer framework to assess the real-time and anticipated aging of a distribution transformer and estimate the remaining useful life of a distribution transformer. The first layer stores residential smart meter data to be utilized for the kVA load estimation of a distribution transformer in the second layer. The performance of two powerful forecasting tools, i.e., Time Series Decomposition and Hidden Markov Model, is compared in the third layer. The historical and forecast data, along with the distribution transformer's thermal parameters, are used for its remaining useful life assessment. Numerical validation is conducted on real-world data utilizing electricity consumption and ambient temperature of fifteen households in London, Ontario, Canada. This work also includes the penetration of the most popular electric vehicles in Canada, along with service drop cable data and practical secondary distribution circuit configuration.

Application of graphene gas sensor technological convergence PSO-SVM in distribution transformer insulation condition monitoring and fault diagnosis

This study aims to improve the real-time monitoring and fault diagnosis of distribution transformers by utilizing a combination of five thin film gas detectors, these detectors include metal-modified graphene composite films and SnO2/RGO humidity sensors, which were prepared using the hydrothermal method. The experiment focused on investigating humidity and main fault characteristic gases that can reflect the insulation status of transformers. Additionally, a gas sensor array was constructed using a deep confidence neural network model. Based on the analysis of dissolved gas in transformer oil, the study extensively discusses the insulation fault diagnosis model and constructs the transformer fault diagnosis model using various methods including TRM, Particle swarm optimization support vector machine. The results demonstrated that the SnO2/RGO thin film humidity sensor exhibited high humidity sensitivity, and the other thin film gas sensors also exhibited good sensitivity. The average accuracy of the three classification methods mentioned is 80%, 92%, and 96%, respectively. These findings highlighted that the vector machine model not only improved the fault diagnosis accuracy but also possessed the characteristics of fewer parameters and a fast rate of convergence. Consequently, it effectively addressed the issue of early diagnosis of potential transformer faults. This study was of significant practical importance for ensuring the secure operation of the power grid.

Kajian Manajerial Efektifitas Pemeliharaan Jaringan dan Transformator Distribusi 20 kV Menggunakan Uji ANOVA

PT PLN (Persero) is an electricity company in Indonesia which supports the development and industrial sectors. Process Business PLN starts from power plant, Transmission and distribution until Retail to Customers. For Supply the needed for customer in electricity power, PLN keep the reliability electricity network for fulfil it. The reliability of electric power distribution network depends on several factors, including the quality of materials, maintenance, operating patterns, protective equipment used and also network configuration. One of the ways to maintain electricity service is to carry out distribution transformer maintenance. After the maintenance is carried out, it is necessary to evaluate the distribution transformer maintenance activities that have been carried out, whether the maintenance activities have an impact or not on management, this is measured by the quality of the voltage and the rupiah per kWh that can be distributed and is denominated in rupiah. The purpose of this study is to find out whether the network and transformer maintenance has had an impact or not. One way that can be done statistically is through the ANOVA test. From the result, Minitab results obtained a value of 0.321 > α = 0.05 and the results of the autocorrelation do not show plots that are outside the lines or margins. This means that the maintenance activities of the 20 kV distribution transformers in data collection unit affect the company’s income. This means that maintenance activities affect the company's income. Therefore, the maintenance factor affects the company's income. Thus, it can be the main focus for improving distribution reliability by doing transformer 20 kV maintenance.

Distribution Transformer Failure Prediction for Predictive Maintenance Using Hybrid One-Class Deep SVDD Classification and Lightning Strike Failures Data

The distribution transformer failure may be influenced by its maintenance history and risk index in a distribution network associated with keraunic level, average number of lightning strikes, and protection devices employed. Transformer failure is a rare event, and the number of "failed" labels is much smaller than that of "non-failed" labels in field monitoring data. Therefore, the transformer failure prediction can be formulated as an anomaly detection or binary classification with an imbalanced dataset, which is challenging to handle. In this paper, we propose a novel distribution transformer failure prediction method through a hybrid one-class deep support vector data description (SVDD) that uses the synthetic minority oversampling technique (SMOTE) to handle the data imbalance between minority and majority class labels. Minimum redundancy maximum relevance (mRMR) is used as a feature selection technique to improve the model's accuracy. The proposed method uses the current condition data of transformers and the distribution network to predict transformer failure for the next year. Real-world field data for 15,066 distribution transformers is used to train and validate the proposed method. It shows superior performance when compared against five benchmark approaches.

An Irradiance Driven Adaptive PQV Droop for Voltage Regulation in Active Distribution System

Gradual increasing installation of solar photovoltaic inverters (SPVIs) at the low voltage (LV) network causes over-voltage issue at the SPVI-connected point-of-common-couplings (PCCs). Further, this problem deteriorates the voltage regulation of distribution transformers in active distribution system (ADS) due to high R/X ratio of the lines. To mitigate such issues, IEEE-1547-2020 recommends the constant QV-droop and PV-droop characteristics in the SPVIs. However, due to lack of adaptability of such characteristics with the variable irradiance level, the controller in SPVIs may under-utilize capacity of the SPVIs. In this paper, an irradiance driven adaptive PQV (IAPQV) droop control technique is proposed for the SPVIs to improve the voltage regulation of an ADS as compared to IEEE-1547-2020 recommended droop characteristic. Moreover, a Two-Bit-Priority (TBP) algorithm is proposed for distributed coordination among the SPVIs. During overvoltage situations, the TBP assists in minimizing active power curtailment at the SPVIs. Performance of the proposed method is verified under different scenarios in ADS. The results are validated through MATLAB/Simulink to show that the proposed IAPQV is more effective as compared to the IEEE-1547-2020.

A New Control Strategy of Hybrid Reactive Power Compensation System in Distribution Network

Reactive power compensation is an important measure to improve the power quality of distribution networks, especially with the increasing connection of distribution transformers, heavy industrial electrical equipment, and asynchronous motors, which generate a large amount of reactive power demand. Traditional reactive power compensation devices, such as fixed capacitors (FC) and thyristor switched capacitors (TSC), have some drawbacks, such as low response speed, harmonic generation, and switching shock. A static synchronous compensator (STATCOM) is a flexible AC transmission system (FACTS) device that can provide fast and continuous reactive power compensation, but it also has some limitations, such as high cost, large capacity requirement, and low utilization rate. Therefore, hybrid reactive power compensation systems that combine FC or TSC with STATCOM have attracted much attention in recent years. Many researchers have proposed and studied different topologies and control methods of hybrid systems to overcome the disadvantages of single devices and achieve better performance. However, most of the existing hybrid systems are designed for low or medium-voltage distribution networks, and their performance under high-voltage distribution networks is still unclear. Moreover, the coordination control strategy of the hybrid system and its subsystems is also a key issue that affects the effectiveness and efficiency of reactive power compensation. In view of this, this paper aims to propose a TSC+STATCOM hybrid reactive power compensation system for high-voltage distribution networks, which optimizes the shortcomings of traditional reactive power compensation devices. The system uses the synergistic effect of TSC and STATCOM to achieve large-scale static reactive power and small-scale dynamic reactive power compensation and adopts a switching strategy based on an expert decision system. This paper introduces the working principle of each subsystem of the hybrid reactive power compensation system in detail and builds a simulation model of the hybrid reactive power compensation system under a high voltage distribution network on Matlab/Simulink platform. The simulation results verify the feasibility and excellent performance of the system control method in reactive power compensation and improving power quality.

Risk-Aware Operating Regions for PV-Rich Distribution Networks Considering Irradiance Variability

This paper proposes a framework to identify, visualize, and quantify risk of potential over/under voltage due to annual energy consumption and PV generation growth. The stochastic modeling considers the following: (i) Active and reactive power profiles for distribution transformers, dependent on annual energy consumption and activity in the serviced areas. (ii) Variable solar irradiance profiles that allow a broader range of PV generation scenarios for sunny, overcast, and cloudy days. The proposed framework uses multivariate- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$t$</tex-math></inline-formula> copulas to model temporal correlations between random variables to generate synthetic scenarios. A probabilistic power flow is computed using the generated scenarios to define critical static operating regions. Results show that classical approaches may underestimate the maximum PV capacity of distribution networks when local irradiance conditions are not considered. Moreover, it is found that including annual energy consumption growth is critical to establishing realistic PV installation capacity limits. Finally, a sensitivity analysis shows that taking a 5% of overvoltage risk could increase up to 15% of the PV installed capacity limits.