Transformer Load Research Articles

Design improvements in modern distribution transformers

In the paper design improvements of distribution transformers related to improved energy efficiency and environmental awareness are discussed. Eco design of transformers, amorphous transformers, voltage regulated transformers and transformers filled with ester liquids are analyzed. As a consequence of growing energy efficiency importance, European Commission has adopted new regulation which defines maximum permissible levels of load and no-load losses of transformers with rated power ≤ 3150 kVA, and minimum peak efficiency index for transformers with rated power > 3150 kVA up to 40 MVA. The impact of new regulation on the design and economy of transformer is presented. Amorphous transformers, with up to 70 % lower no-load losses in comparison to the conventional transformers, could be an alternative with respect to energy efficiency. Although their initial price is higher than the price of conventional transformers, some studies show that they might have economic advantages. The increasing penetration of distributed energy sources can cause an increase in voltage variations in low voltage networks. To keep the voltage within limits defined by EN50160, voltage regulated distribution transformers could be used. Although mineral oil has been used as a dielectric fluid in transformers for many years, there are some environmentally friendlier alternatives – natural and synthetic ester-based fluids.

ANALISIS HOSTING CAPACITY PADA JARINGAN TEGANGAN MENENGAH UNTUK SUPLAI DAYA LISTRIK DAERAH PEDESAAN

As technology advances, the use of electrical energy increases for this reason, energy conversion is needed, one of which is the installation of photovoltaic. Analysis hosting capacity on the distribution network serves to determine the flow of power when photovoltaic is installed and can analyze voltage, conductor loading, power loss, and good transformer loading when connected to the network.The analysis of hosting capacity on rooftop PV mini-grid spread over the distribution network is very useful for future planning if there is a massive energy transition that is implemented on rooftop PV mini-grid. The hosting capacity analysis on the distribution network was carried out in 2 scenarios, which were Scenario A for the Bangli feeder without being connected to the PLTS 1 MWp and Scenario B for the parameter B for the Bangli feeder being connected with the PLTS 1 MWp. The analyzed parameters included voltage, conductor loading, transformer loading and power losses in network. The results of the analysis showed that the distribution network hosting capacity is 40%, for both Scenario A and Scenario B.

Load Flow Analysis at Babakan Substations for Industry Growth Devolopment Using ETAP Power Station 12.6 Softwere

Based on transformer loading at GI 70kV Babakan which is already 80% high bigger than capacity 30 MVA by reason there is a need for additional power supply for industrial development, one of which is the addition of PT. Longrich Indonesia for 25 MVA. With the existing condition of transformer loading at GI 70kV Babakan is currently unable to meet the power supply needs and the construction of GI 150kV Kanci is still in progress, therefore the installation of a mobile transformer at GI 70kV Babakan is intended to meet the need for additional power supply. In this study, simulating Electrical power in GI 70kV Babakan uses the ETAP Power Station 12.6 software and compares it with the results of manual calculations. Installing a Mobile Transformer with a capacity of 30 MVA at GI 70kV Babakan can increase the MVA capacity at GI 70kV Babakan so that it can meet the need for additional power supply,
 With the load on the mobile transformer and the daytime loading history of 48 MW and the highest load reached at 61 MW, the Mobile Transformer can be loaded with a maximum of 25 MVA. And transformers are still able to supply the area properly so there is no overload. and increase revenue through the sale of electricity.

Solving Unit Commitment Including Wind Power Generation Using PSS®E

Operating the power system in an optimal way and keeping it safe and reliable is very important in power systems planning and operation. The power system currently has a large variety of power plants that operate with different kinds of fossil fuel or use renewable energy to produce power. As the demand on electricity is fluctuated, utilities are obligated to provide consumers with power at any time during a day. Power system operators try to supply electricity in an economic operation by turning on the cheapest generating units and turning off the most expensive ones at off-peak value of the load. Finding the optimal combination of units to supply forecasting load is called unit commitment problem (UC). The second step of the optimization problem is finding the optimal output power from each committed unit, which known as economic dispatch (ED). The main benefits of solving the unit commitment problem and economic dispatch are to minimize generation cost over the objective period horizon while applying all system constraints that come from generating units’ limits and the transmission system’s characteristics, as well as to verify the balance between power generation and power demand. While, the optimal power flow (OPF) tries to find the optimal dispatch for the whole power system, but by taking into account all systems constrain, such as voltage security and transmission line limit. The optimal power flow can control many variables to find the optimal operation of the system, like a transformer tap changer, phase shifter, switched shunt, and load adjustment. In this paper, power system simulator for engineering (PSS®E) is used to solve unit commitment, economic dispatch, and optimal power flow. The implementation is performed on IEEE 30-bus system for a 24-hour period. In the first stage, the UC, ED, and OPF were solved for the systems without including wind power generation. In the second stage, UC, ED, and OPF were solved by including a wind-power farm with 100 MW rated power connected to the system. The solution is based on 24-hour wind data forecasting, and 24-hour power demand's prediction.

ANALISIS DAMPAK OVERLOAD TRANSFORMATOR TERHADAP KUALITAS DAYA GARDU K622 PENYULANG PELANGI PT. PLN ( PERSERO ) ULP KARANG

Transformer overload occurs in one of the distribution transformers in PT. PLN (Persero) ULP Karang,namely the K622 Distribution Transformer at the Rainbow Feeder with a load of 110.16% exceeding the standard set by SPLN, which is 80%. This study aims to find out how to overcome the Overload problem in the K622 distribution substation transformer on The Rainbow and get the size of the K622 distribution substation transformer load before and after the Uprating Transformer. From the results of uprating, the percentage of transformer loading value before uprating transformers was carried out by 110.16% and after uprating transformers by 26.38% so that it decreased by 83.78%. This means that the uprating transformer is one of the methods that can be used to overcome excess loads.

Automatic Load Sharing of Transformer

Transformer plays a major role in the power system. It works 24 hours a day and provides power to the load. The transformer is excessive full, its windings are overheated which leads to the judgment of the transformer installation which leads to disruption of the power supply to the load. It takes a lot of time to repair and involves a lot of costs. This project deals with transformer protection under conditions of overcrowding. The transformer could be protected by reducing the additional the transformer's load by connecting and using another transformer in conjunction the primary transformer using a microcontroller and a switch relay. The load on the first transformer is compared to the reference value by the Arduino. When the load exceeds the reference value, the slave transformer is automatically attached to the first transformer and the extra load is shared. Therefore, the number of transformers works well under conditions of overcrowding and damage could be prevented. In this project, slave transformers share the master transformer's duty in the event of overcrowding and overheating. Sensor circuit with Arduino, current transformer, and other components is designed to collect data from the master transformer, and if it is determined to be overloaded, the slave transformer is immediately attached to the master transformer and the load is shared. The Arduino keeps track of the transformer's current volume and displays it. If loads are introduced to the current transformer's second side in the second side riser. As the current volume exceeds the estimated current value of the transformer, so the microcontroller sends a travel signal to the relay, thus opening the slave transformer. Initially when we open the load, it will be shared by the first transformer. Once the load on the first transformer has been raised above its maximum capacity, the standby transformer will automatically share the load.

FEASIBILITY STUDY OF ELECTRIC VEHICLES INTEGRATION IN RWANDA DISTRIBUTION NETWORK

Purpose: This paper investigates the impacts of electric vehicles integration in Rwandan Power system by assessing harmonic distortion, power loss, system loading, and voltage stability.
 Methodology: Distribution network test was conducted on 34 buses taken from KINIGI feeder of Camp Belge substation in northern corridor of nation grid by using ETAP software.
 Findings: The test came up with locating electric vehicles charging stations by taking into account the total harmonic distortion, transformer loading, voltage sensibility factor and the power loss where 4, 1, 2, 2, and 1 vehicles are located at buses 19, 20, 23, 25, and 26 respectively. The study determined the location of charging stations to enhance technical perspectives while implementing policies as policy maker motivates the public to shift from diesel powered EV to mitigate greenhouse gases emissions and fuel resources scarcity.
 Recommendations: The number of integrated EVs has been shown to be low compared to the demand for EVs and the industry's annual target of 1000 EVs per year. This requires a utility to manage the proposed load increase by planning for the power generation, transmission and distribution infrastructure. In addition, EV charging stations generate current and voltage harmonics that affect negatively electrical equipment, nearby loads, and neighboring telecommunications lines. Harmonic filtering devices such as RHS, SC and hybrid devices built on RHS and SC are required in the distribution network to eliminate the effects generated by the harmonics.

A 24 GHz FMCW/Doppler Dual-Mode Frequency Synthesizer With 68.8 kHz RMS FM Error and 1.25 GHz Chirp Bandwidth

This brief presents a 24 GHz dual-mode frequency synthesizer designed in a 55-nm CMOS technology supporting both Doppler and frequency modulated continuous wave (FMCW) radars. The effects of chirp linearity and delta-sigma modulation (DSM) resolution on the rms FM error is analyzed. A design procedure for the PLL loop bandwidth and time interval of the frequency step to reduce the rms FM error is proposed. A voltage-controlled oscillator (VCO) featuring a four-coil transformer load is developed providing differential local oscillation (LO) signals for the transmitter (TX) and quadrature LO signals for the 2-channel receiver (RX). The prototype is designed with a loop bandwidth of 350 kHz, a frequency step time interval of <inline-formula> <tex-math notation="LaTeX">$2 ~\mu s$ </tex-math></inline-formula>, and a VCO tuning linearity of 26&#x0025;. In the FMCW mode, it achieved an rms FM error of 68.8 kHz over a 1.25 GHz chirp bandwidth. In the Doppler mode, the VCO operates in the free-running mode to save power consumption. An 8-bit digital-to-analog converter (DAC) is used to provide the VCO control voltage compensating process and voltage variations. The free-running VCO operates at a 24.125 GHz and has a frequency error of less than 1 MHz.

Analisis Ketidakseimbangan Beban pada Transformator Bambang Djaja ULP Fakfak

Research has been carried out on the load imbalance analysis on the transformer with the aim of knowing the percentage of load imbalance on the transformer. From the results of the analysis that has been carried out, it is known that the percentage of transformer loading is unbalanced and is in bad condition because it exceeds the balance standard that has been set, which is above 25% with a percentage for line 1 of 60% during the day and 80% at night. While on line 2 has a percentage of 35% during the day and 33% during the day.

Meningkatkan kinerja gardu distribusi SK76 Penyulang Sukasada dalam menangani overblast menggunakan simulasi perangkat lunak ETAP

Distribution transformer serves to transform electrical energy from the power source to the customer. In the transformation process there are power losses which of course can reduce the efficiency of the transformer. The relatively high loading on the transformer will cause an increase in power losses, so its efficiency will decrease. The Sukasada Feeder SK76 Distribution Substation with a transformer capacity of 100 kVA supplies 253 customers with an installed power of 273 kVA. Based on the measurements that have been made during the peak load time (WBP), the average percentage of the transformer loading is 99.57% with an efficiency of 98.02%. Referring to the Circular of the Directors of PT. PLN (Persero) No.: 0017.E/DIR/2014, then the transformer has been declared overload (overblast) because the load has exceeded 80%. Efforts that can be made to improve the performance of the transformer include: upgrading the capacity of the transformer, adding additional substations or through network reconfiguration. Based on the trials that have been carried out by the author through the simulation of the ETAP 16.0 software, several results were obtained. If an uprating is carried out with a transformer capacity of 160 kVA, the percentage of loading decreases to around 61.46% with efficiency increasing to about 98.77%. If additional substations are added with a capacity of 50 kVA as well as network reconfiguration by transferring some of the load to another Distribution Substation (SK63), the result is that the percentage of loading is reduced to around 63.17% and efficiency increases to about 98.46%. The simulation results that have been carried out show that this condition has met the provisions/regulations set by PT. PLN (Persero).

MTS-LSTDM: Multi-Time-Scale Long Short-Term Double Memory for power load forecasting

As reducing greenhouse emissions and carbon footprint have drawn more and more attention, predicting the power load of distribution transformers in an intelligent way is critical for electric safety and equipment protection. It is essential to perform accurate regression and generate stationary residual series in critical fields such as power load forecasting. In this paper, we introduce a fusion operator to combine critical historical information of different kinds and propose an ensemble Long Short-Term Double Memory based on Multiple Time Scale (MTS-LSTDM) for power load prediction in smart grid. Compared with some state-of-the-art and existing regression methods, both excellent accuracy and residual series stationarity are shown with MTS-LSTDM, which is conducive to the stability and robustness of power load forecast and is easier to popularize in real-world application scenarios. In addition, the comprehensible reason for generating stationary residual series is given, and generalized applications are discussed in detail. This work not only conducts a complete model research and analysis on the smart grid, but also has great reference significance for the regression of multi-time-scale time series data.

Research on operation status and fault deduction system design of transformer in large sports venues

The problem of low transformer load rate (less than 60%) in the actual operation of large stadiums and gymnasiums has affected the waste of power energy and the improvement of power cost in the industry. The transformer failure of large stadiums and gymnasiums may further cause serious power accidents in the future. In order to solve the above problems, firstly, this paper analyzes the transformer load rate data of the two large sports venues(Nanchang International Sports and Tennis Stadium in Jiangxi Province)and probes into the design data and calculation coefficient of the transformer of the large sports venues; Secondly, this paper puts forward some suggestions on how to improve the operation load rate of transformers in stadiums from the aspects of transformer design and selection of demand coefficient; Thirdly, the paper establishes the system hardware environment by using firewall, special switch and information database, and then realizes the design of software deduction program through correlation analysis, fault diagnosis and cluster deduction, and completes the design of transformer fault deduction system in large sports venues. Finally, the results clearly show that the transformer load rate is relatively low in large sports stadiums(the highest value is only about 55% and well below the 60% standard). On other hand, compared with the traditional system and based on big data association, the average relative errors of fault points 1, 2 and 3 decreased by 67.8%, 56.4% and 51.6% respectively and the diagnosis time has also been greatly shorten by the transformer fault deduction system. In short, this paper uses association rules to mine and obtain transformer fault characteristics, combined with the advantages of virtual reality technology, designs an effective and reliable transformer fault deduction visualization system for large sports venues.

Analysis and Simulation of a Typical Two Winding Transformer

In this study, we show how input power, terminal voltage, and efficiency changes as a function of load current. In this situation, we've chosen three scenarios they are- Coil connection in Parallel Coil connection in Series Two Winding Transformer Here, we have connected the coils of a single-phase transformer in series and parallel, then observed the transformer's loading as an autotransformer and as a two-winding transformer. It is essential to comprehend the instant polarities of the secondary terminals in relation to the primary in order to properly connect the winding.

Mitigating the Impact of an Official PEV Charger Deployment Plan on an Urban Grid

Plug-in electric vehicles (PEVs) are rapidly increasing all over the world as electromobility is being promoted to reduce the greenhouse gas (GHG) emissions. PEVs locally produce zero emissions and they are more efficient in contrast to internal combustion engine vehicles. On the other hand, the impact of the uncoordinated charging of PEVs is expected to create new challenges for the established distribution grid. This article initially evaluates the impact of uncoordinated charging on the voltage regulation and transformer loading in the city of Heraklion, Greece. Then, a coordinated charging strategy is proposed to deal with the issue of transformer capacity violation by PEVs. Two cases were considered when the transformer overloading from PEV charging was taken into consideration: (a) keeping the transformer below its nominal capacity limit and (b) keeping the transformer below 90% of its nominal capacity limit. This was achieved by distributing the available capacity (nominal capacity minus the residential loads) of the transformer to the PEV chargers in a way that the aforementioned limits were satisfied. Real-world data of the distribution grid and the hourly power consumption of the city were used to validate the proposed method. Results show that possible transformer capacity violation can be tackled by the proposed coordinated charging, without exceeding the voltage regulation limits.

Application of operational modal analysis to investigate transformer vibration patterns

This paper develops an operational modal analysis application framework for vibration measurement-based condition monitoring of transformer winding structure. Within the framework, load transient signals generated by turning on and off transformer or changing transformer load are used as the broadband excitations. Frequency domain decomposition (FDD) technique is used to process the measured transformer vibration signals to detect possible mechanical changes to the transformer's winding and core structure. Case studies demonstrate the OMA application framework (broadband excitation and FDD) can achieve higher accuracy of natural frequency detection of windings, which can pave a way for online transformer winding and core condition monitoring.

Design of transformer load management system based on multi-resources data

Ensuring data quality, the main transformer load risk assessment model based on load rate characteristics is established. Further, using deep learning algorithm, the main transformer heavy and overload risk prediction model is constructed to realize the risk grade assessment and risk prediction on load feature defects. Finally, through the construction of the system platform, the basic functions such as multi-dimensional index calculation, statistics and visual display of real-time load characteristics of the main transformer are realized.

Buildings-to-distribution-network integration considering power transformer loading capability and distribution network reconfiguration

A novel buildings-to-distribution-network integration framework is developed in this paper. The joint objective of the proposed framework is to schedule flexible resources, so that the overall performance is optimized regarding the safe operation of transformers, the thermal comfort of building occupants, and the energy savings of distribution network. To fulfill the joint objective, buildings are coupled to the distribution network via transformers and power balance constraints firstly. Then, the integrated energy system is optimized considering the operation constraints of distribution lines, various devices, and flexible resources. Afterwards, the safe operation of transformers is analyzed, and the maximum allowable load ratios of transformers are adjusted according to the analysis. After that, the reconfiguration of distribution network is utilized to optimize the scheduling control of flexible resources for the coordination of the safe operation of transformers and the thermal comfort of building occupants. Simulation results on three case studies demonstrate that the scheduling problems of flexible resources, introduced by the contradiction between the safe operation of transformers and the thermal comfort of building occupants, can be fully dealt with the reconfiguration of distribution network. Simulation results also show that the gap in the joint objective values between the developed framework and its baseline counterpart are all within 0.5%, further verifying the effectiveness of the developed framework.

Improving Clustering-Based Forecasting of Aggregated Distribution Transformer Loadings With Gradient Boosting and Feature Selection

Load forecasting is more important than ever to enable new monitor and control functionalities of distribution networks aiming to mitigate the impact of the energy transition. Load forecasting at medium voltage (MV) level is becoming more challenging, because these load profiles become more stochastic due to the increasing penetration of photovoltaic (PV) generation in distribution networks. This work combines medium to low voltage (MV/LV) transformer loadings measured with advanced metering infrastructure (AMI) and machine learning (ML) algorithms to propose a new clustering based day-ahead aggregated load forecasting approach. This four-step approach improves the day-ahead load forecast of a city. First, MV/LV transformer loadings are clustered based on the shape of their load pattern. Second, a gradient boosting algorithm is used to forecast the load of each cluster and calculate the related feature importance. Third, feature selection is applied to improve the forecast accuracy of each cluster. Finally, the day-ahead load forecast of all clusters are aggregated. The case study presented uses 519 measured MV/LV transformer loadings in a city to perform 30 day-ahead load forecasts. Compared against the day-ahead aggregated load forecast without clustering, the average normalized root mean squared error (NRMSE) reduced 12.7 &#x0025;, the average mean absolute percentage error (MAPE) reduced 18.2 &#x0025; and the average Pearson Correlation Coefficient (PCC) increased 0.37 &#x0025;. The 95 &#x0025; confidence interval of the difference between the average NRMSE, MAPE and PCC without clustering and with the proposed method indicates a statistically significant improvement in accuracy.

Linear Arrhenius-Weibull Model for Power Transformer Thermal Stress Assessment

Arrhenius equations with Weibull distribution have been broadly deployed to quantify the loss of life and probability of failure of power transformers. This model is highly nonlinear, and this non-linearity makes it challenging to use this model for grid management and optimization. In this study, equations are linearized using Taylor series expansion to provide a linear formulation for transformer loss of life and probability of failure as a function of ambient temperature and transformer loading. The proposed formulation allows transformer constraints to be incorporated in grid management applications within conventional optimization approaches, such as linear programming, and decreases the calculation burden caused by nonlinearity.

Data-Driven Study of Low Voltage Distribution Grid Behaviour With Increasing Electric Vehicle Penetration

In this paper, the impact of Electric Vehicle (EV) uncontrolled charging with four levels of EV penetration in overall 21 real low voltage distribution grids in two seasons are analysed. The employed real grid data is provided by distribution system operators from three European countries: Austria, Germany and the Netherlands. At least six grids in each country were considered and they are categorised into three types, namely rural grids, suburban grids and urban grids. The EV charging data used in this study is based on real measurements or surveys. The seasonal and the weekday-weekend factors are also considered in the EV charging impact research. Three key congestion indicators, the transformer loading, line loading and node voltage as well as several other evaluation indexes are studied. The results reveal that the majority of the simulated grids had no or minor moments of mild overloading while the rest grids had critical issues. Among all the grids, suburban grids are most vulnerable to massive EV integration. Out of the evaluated grids, those who are located in Germany have the highest redundancy for high EV penetration accommodation. Overall, the impact of uncontrolled EV charging depends on the combination of EV charging demand as well as the grid inherent features.