kV Substation Research Articles

Force analysis and improvement of main transformer bushing terminal structure

Abstract After investigation, it was found that due to natural environmental conditions such as rain and snow temperature, equipment such as down conductor above the terminals, and natural swings of wires, the terminal blocks of the down conductor bushing on the high voltage side of the main transformer of a 500kV substation will deteriorate and deform. Following the force analysis and experiment on the down conductor bushing terminal block on the high voltage side of the main transformer, it is found that the weak structure of the bushing terminal block lies in the vertical orientation of the terminal and the connection point of the transverse structure, and its horizontal external force limit value is 1.91KN. In this paper, it was finally decided to improve the terminal structure by erecting diagonal supports between the vertical and transverse structures of the terminals. The improved terminal block can be subjected to an external force of 5KN horizontally, and the terminal shape is within the safe range. It can ensure the safety and stability of the main transformer bushing terminal block.

Enhanced thermal modeling of power transformers: A comparison of bond graph and IEEE methods considering external environmental factors

The optimal and secure operation of electrical power system is largely affected by the reliability of power transformers in operational and economic terms. The continuous monitoring of power transformer is crucial for ensuring the quality of electrical power supply. Hence, the thermal modeling of power transformer is very essential to prevent their failure. This paper aims to design thermal models of operating power transformer by considering the two external influencing parameters of solar irradiation and wind flow. This paper presents a Bond Graph (BG) method-based design of thermal models for power transformer under operating condition by comparison with the results obtained from IEEE Std. based thermal models and also with the practical readings. The models have been implemented on a 5MVA, 33/11 kV power transformer running at 33 kV Substation, Sardarpura, Jodhpur, by initially considering the input hourly dataset of load and ambient temperature. The designed thermal models were subsequently updated by integrating the impact of solar radiation and wind incident on the surface of power transformer. Comparative study of all the designed thermal models has been done that indicates improved accuracy of the model if the impact of solar radiation and wind flow are included. Also, the effectiveness of the BG based thermal models in accurately predicting the system behaviour validates their applicability for real world engineering applications.

Probabilistic seismic risk analysis of electrical substations considering equipment-to-equipment seismic failure correlations

When an earthquake occurs, electrical equipment in a substation exhibits a certain level of seismic failure correlation since they suffer similar ground motions and share similar structural characteristics. However, this equipment-to-equipment seismic failure correlation (E2ESFC) was neglected in previous substation-level probabilistic seismic risk analyses due to the lack of awareness and practical approach. To investigate the effect of different degrees of the E2ESFC on the substation seismic risk, an efficient method for considering partially correlated seismic failure was proposed. The concepts of “damage demand probability” and “damage capacity probability” were derived from the equipment's fragility curve. Then the partial correlation of equipment's capacity probabilities can be easily introduced and incorporated into the substation-level risk analysis through the combination of Copula functions and the Monte Carlo simulation. A case study on a real-world 220/110 kV substation using an equi-correlation model demonstrated that ignoring the E2ESFC among the same type of equipment will lead to an underestimate of the probability of seeing high seismic loss. Furthermore, a general method to assess the E2ESFC coefficients between equipment was also proposed, laying the foundation to facilitate applications of the introduced E2ESFC simulation method and to generate a more reliable system risk assessment result.

Automated monitoring of insulation by ultraviolet imaging employing deep learning

The corona effect on the surface of electrical system equipment and components generally indicates undesirable phenomena that can lead to physical degradation of materials or even equipment failure. One of the most promising techniques for monitoring corona discharges is the use of specialized cameras for the detection of ultraviolet radiation. This paper introduces an innovative algorithm for classifying the criticality of insulation based on attributes extracted from videos recorded using an ultraviolet detection camera. The attributes extracted from each facula origin include maximum persistence, area, and the minimum distance between the facula origin and the insulation. To obtain this distance, a technique combining a deep convolutional neural network model with an adaptive segmentation thresholding method is proposed. To validate the proposed methodology, inspections were conducted at a 500 kV substation. A total of 96 videos were recorded, within which 99 facula origins were identified. The object detection model applied demonstrated an accuracy of 85.5 % in detecting insulation in images, based on a validation set comprising 1,985 images and 8,730 instances. The results of the classification showed that 72.7 % of the facula origins recorded originated from regions far from the insulation (mainly cables and corona rings). These results demonstrate that the distance between the insulation and the facula origin is an essential attribute for video analysis, providing context for recorded discharges and allowing differentiation between cases where ultraviolet radiation originates from insulation and those where discharge location is less critical.

Reliability of SF6 Circuit Breaker Cells and Selection of Switchgear Circuits for 220 kV Substations

Reliability of SF6 Circuit Breaker Cells and Selection of Switchgear Circuits for 220 kV Substations

Load Flow Analysis and Loss Reduction Activities: A Case Study on Kawasoti 132/33/11 kv Substation

This paper deals with the study of energy flow patterns in INPS connected 132KV/ 33KV/11KV Kawasoti Sub-Station. From the monthly data as of April and May 2020, the base load for 30 MVA 132/33 KV transformer is about 12 MW and peak load is around 15 MW. Load forecast of 132/33/11 KV Kawasoti Sub-Station shows that the cumulative load growth percentage is around 70 % and around 8.75% per year. The peak load in 2020 was around 23.53 MW and it would approximately reach 40 MW at the end of fiscal year 2028. Load flow analysis as of 2020 shows total distribution loss was found to be 1.7833 MW when the demand is 23.658 MW at 0.7141 lagging and reactive power loss of 8.907 MVAR is found. Estimated total distribution loss for the year 2028 would be 3.851 MW when the demand is 40.238 MW at 0.76 lagging and reactive power loss of 20.572 MVAR. After the placement of a capacitor bank of 7000 KVar and 5000 Kvar on MV and LV Bus-Bar respectively, the total distribution loss was found to be 0.8695 MW with pay-back period of 1.427 Years for year 2020. After the placement of a capacitor bank of 10000 KVar and 7000 Kvar on MV and LV Bus-Bar respectively, the total distribution loss would be 2.2563 MW with pay-back period of 1.158 Years for forecasted condition. The simulated model, result and analysis are presented in this paper.

State Evaluation of Electrical Equipment in Substations Based on Data Mining

This paper explores the combination of a data mining-based state evaluation method for electrical equipment in substations, analyzing the effectiveness and accuracy. First, a Gaussian mixture model is applied to fit all raw data of electrical equipment. The Expectation Maximization algorithm summarizes the data distribution characteristics and identifies outliers. The a priori algorithm is then employed for data mining to derive frequent itemsets and association rules between equipment quality and measurement data. For new equipment samples, conditional probabilities of each feature are independently calculated and combined to classify and evaluate equipment quality. The results suggest that equipment reliability in smart substations can be inferred from historical and real-time operational data using improved association rule algorithms and Naive Bayes classifiers. Finally, the proposed method was applied to analyze statistical data from a 110 kV substation of a power supply company. The states prediction accuracy exceeded 95% when compared with actual equipment quality. The effectiveness evaluation metrics demonstrated that this method outperforms single-category algorithms in terms of accuracy and discrimination ability.

Analisis Arrester Sebagai Sistem Proteksi Pada Transformator di Gardu Induk Keramasan

Lightning overvoltage is a periodic overvoltage caused by external causes. An arrester is equipment that protects installations from overvoltage disturbances due to lightning strikes or electrical surges. The transformer functions to distribute electrical power by increasing or decreasing the voltage at the substation. This research focuses on substation equipment, namely the type 3EP 2150-2PL3 arrester connected to a 100 MVA IBT Transformer. Good protection is obtained if the arrester is placed as close to the transformer as possible. Therefore, this distance is determined so that protection can take place properly. The distance between the arrester and the transformer used at the Keramasan 150 KV substation is 5 m. while from the calculation results it is 22.5 m. based on SPLN 7: 1978 that for a 150 kV system the distance between the lightning catcher and the transformer does not exceed 80 m. This means that the distance between the arrester and the 100 MVA IBT Power Transformer is still within the limits set by PT PLN. The continuity of the spark that occurs in the arrester is still within safe limits and in accordance with mathematical analysis.

Cause analysis of the compression spring stress relaxation of circuit breaker operating mechanism in a 220 kV Substation

Cause analysis of the compression spring stress relaxation of circuit breaker operating mechanism in a 220 kV Substation

Selection of 110 kV Prefabricated Steel Substations Considering Seismic Vulnerability in China

Prefabricated modular substations are expected to become the mainstream construction type for substations in China. However, there is a lack of scientific basis for structural selection and seismic performance evaluation. Taking a 110 kV substation as an example, this study compares the construction cost of cast-in situ reinforced concrete (RC) substations and prefabricated steel (PS) ones. Two types of PS structures are considered: one with H-section steel columns and the other with box-section steel columns. A seismic vulnerability analysis is performed to compare the probability distribution of various damage states of substation building structures under different seismic damage levels. Results indicate that the construction cost of PS structures is approximately 27.9% higher than that of cast-in situ concrete. When using H-section steel columns, there is a significant difference in the flexural stiffness in two horizontal directions, resulting in reduced seismic performance in the weak-axis direction. The construction cost of using box-section steel columns is slightly higher than that of the H-section steel case, but its seismic performance is significantly improved. Although the probability of slight and moderate damage states for the box-section steel column scheme is generally higher than that of the cast-in situ RC scheme, the probability of collapse is reduced. Thus, box-section steel columns are recommended for prefabricated modular substation building structures.

Virtual Power Plant Response Strategy Considering Dynamic Aggregation of Different Flexible Resources

Abstract Aggregate and adjust distributed resources, the virtual power plant realizes the collaborative optimization of different forms of electric energy, which greatly improves the flexibility of the power system. Considering the flexibility of distributed resources, this paper designs the active power and frequency regulation modes of virtual power plants, and proposes a response strategy for dynamic resource aggregation of virtual power plants. Firstly, the distributed energy resources of virtual power plants are classified, and their dynamic characteristics are fully considered for dynamic aggregation, and the active power and based on these characteristics, a frequency regulation model is established. Secondly, according to the real-time operation status of sampled distributed resources, a response prediction model of virtual power plant based on dynamic resource aggregation was proposed. Finally, taking the 35kV substation workbench as an example, the response effect of the virtual power plant at different times of a typical day is verified.

We need more network capacity! But why do we get it? Infrastructural refraction and the contingencies of network growth and energy transitions

It is accepted that electricity networks need to grow in scale and scope to facilitate decarbonisation. It is also accepted that infrastructural change is incremental. Yet, the incremental delivery of network capacity and the relevance of this for energy transitions have received little attention. Instead, broader, evolutionary accounts of change predominate. Opportunities therefore remain to conceptualise and study the incrementality of network growth and to consider the implications of this for energy transitions. I conceptualise investment in network capacity as an outcome of infrastructural refraction: as emergent of varied and unevenly distributed histories and geographies of electrification beaming through and being refracted by the prism of socio-technical infrastructure in ways that condition the sited reconstitution of network capacities. Examining practices of translation, enacted by network operators, provides a method of revealing the constitutive details and dynamic of infrastructural refraction. A case study focused on the technological framing of the delivery of a 33 kV substation in Central Manchester is explored. The analysis stresses the importance of examining the contingencies of investment in capacity. This paper contributes a concept-method package that helps reveal such details and by proxy the polycentric politics of electrification, investment in electricity network capacity, and energy transitions.

Analysis of Ferroresonance Mitigation Effectiveness in Auxiliary Power Systems of High-Voltage Substations

Ferroresonance in power networks is a dangerous phenomenon, which may result in overcurrents and overvoltages, causing damage to power equipment and the faulty operation of protection systems. For this reason, the possibility of the occurrence of ferroresonance has to be identified, and adequate methods need to be incorporated to eliminate or reduce its effects. The aim of this paper is to evaluate the effectiveness of ferroresonance damping in auxiliary power systems of high-voltage substations by selected damping devices. Laboratory experiments, the results of which created bases for the development of models of selected damping devices, are presented. These models were used to simulate the effectiveness of ferroresonance damping in an auxiliary power system of a 220/110 kV substation in the EMTP-ATP program. The analyses showed that control systems with different algorithms of operation are used in damping devices. This knowledge is important when selecting parameters and settings of the applied damping devices for a given network and the disturbances in it. The presented research results have proved the effectiveness of commercially available damping devices, provided their parameters are correctly coordinated with the settings of the power system protection.

Construction of a recurrent neural network-based electrical load forecasting model for a 110 kV substation: a case study in the Western Region of The Republic of Kazakhstan

This paper presents an approach for using a long short-term memory (LSTM)-based recurrent neural network with various configurations to construct a forecasting model for electrical load prediction of a 110 kV substation. The issues of unbalances arising in energy management systems due to discrepancies between generated and consumed energy can lead to power outages and blackouts. With the introduction of the most accurate forecasts, the task of maintaining electrical reliability for grid operators can be greatly simplified. Through an investigation into 81 different parameter combinations, the research revealed the optimal setup for an LSTM model in the task of electrical load forecasting. This configuration comprised 15 neurons, a batch size of 16, and employed the Adamax optimization algorithm. Applying this specific setup yielded a mean squared error (MSE) of 5.584 MW2 and an R2 value of 0.99. High R2 values and low MSE values indicate that the LSTM model accurately captures changes in electricity consumption with minimal deviation between predicted and actual consumption values. Selection of appropriate parameters significantly enhances the performance of the predictive model and resulted in a reduction of the MSE error from 12.706 to 5.584 MW2. The optimized configuration of the LSTM model, tailored through extensive experimentation, enhances its predictive capabilities. The proposed LSTM model holds practical utility for integrating into systems for monitoring and forecasting mode reliability of electrical networks, particularly in the Western energy hub of the Republic of Kazakhstan. Its accuracy and reliability make it valuable for energy resource management and infrastructure planning

Comprehensive Structural Reliability Assessment When Choosing Switchgear Circuits for 35–220 kV Step-Up Substations

The basic requirements for the design of a switchgear for main 35–220 kV step-down substations are reliability and efficiency. Switchgear circuits are chosen depending on the number of supply and transit lines and transformers, the substation’s place in the power supply system, and the area that can be allocated under the substation construction. The substation switchgear’s reliability depends on the circuit type and the equipment to be installed. When designing, as a rule, standard substation switchgear circuit solutions are chosen with often unreasonably overstated reliability indicators and, as a consequence, capital costs. This paper explores the issues of automated choice of the best option for the 35–220 kV substation switchgear circuit, considering its structural reliability and additional costs for the area allocated under the electrical unit. A distinctive feature of the work is a comprehensive accounting of the reliability indicators of the substation and the influence of the layout of switchgear circuits as a whole on the performance indicators of future electrical installations. The developed technique is used at the pre-design stages and allows for reducing further capital, maintenance, and repair costs for electrical units by up to 14.5%. The developed approach is implemented in the original TER CAD software product.

Integrated micro thermoelectric devices with self-power supply and temperature monitoring: Design and application in power grid early warning

The Internet of Things (IoT) and wearable technology have led to the development of wireless sensors at an unprecedented pace. Within the IoT framework, smart grid systems require real-time temperature monitoring of various switch contacts. Especially in the process of power transformation (China: ultra-high voltage → 10 kV → 380 / 220 V), poor switch contact will lead to overheating, resulting in equipment damage and major safety accidents. Micro-thermoelectric devices (micro-TEDs) exhibit a significantly greater thermoelectromotive force than metal-based thermocouples. By establishing two bivariate first-order equations for hot-end and cold-end temperatures, accurate detection of both temperatures and simultaneous self-power supply can be achieved. In this work, we observe that the Seebeck coefficient of hot extruded n-type Bi2Te2.7Se0.3 and p-type Bi0.5Sb1.5Te3 thermoelectric couple exhibits slight fluctuations around 435 μV/K, while its resistivity follows an almost linear trend with temperature from room temperature to 120 °C. By utilizing these two bivariate first-order equations, the temperatures at both the hot and cold ends can be determined. Based on this, we have fabricated a micro-TED (size: 14 × 6 × 2.5 mm3, TE leg: 0.8 × 0.8 × 1.6 mm3) with a temperature measurement accuracy of up to ± 0.1 °C and a power density of 10.12 mW/cm2 under a temperature difference of 30 °C. Furthermore, we used thirteen micro-TEDs and one circuit board to build a self-power supply temperature monitor. When this TE sensor device was deployed on the plum blossom connector surface and conducted online assessments for the 10 kV substation over a span of approximately 200 h, it continuously outputs a temperature signal and the power supply maintained normalcy, exhibiting no aberrations. This temperature monitoring system can be extended to other fields that require all-weather wireless temperature monitoring, which provides a new direction for the development of micro-TEDs.

Feature statistics and analysis of transient overvoltage waveform measured from 220 kV substation

The electromagnetic transient overvoltage in the substation is an important factor that affects the life of insulation equipment. For evaluate the economy and reliability of the insulation design of substation equipment, it is necessary to study and analyze the actual measured overvoltage waveforms in the substation. In this paper, firstly, the 3018 pieces of overvoltage data monitored in the 220 kV substation from 2018 to 2019 are preprocessed to obtain the required overvoltage waveform. Next, by analyzing and classifying the overvoltage data, four typical overvoltage waveforms suffered by the insulation equipment in the substation are extracted. Combined with the IEC60060 standard, the time parameters of the overvoltage waveform are selected and defined: wave-front time (Tf), half-value time (Thalf), main oscillation frequency (f), and attenuation constant (α). Further, statistical analysis is performed on the parameters of each waveform. The distribution law, distribution characteristics and distribution range of the parameters are obtained. Finally, the parameters of four typical overvoltage waveforms are summarized and compared, the cumulative distribution functions are obtained. This results can guide and optimize the insulation design of the insulation equipment in the substation, reduce design errors. It provide data support for the economy and reliability of insulation design.

Analysis and Preventive Measures for an Abnormity of 220kV Isolating Switch

With the development of the power grid, the cutter brake is a kind of main equipment used cooperatively in the transmission and distribution line of the substations with the circuit breaker in the operation and maintenance of the electric power system. Its main role is to ensure the safety of the staff during the maintenance of high voltage equipment. The cutter brake forms a clear disconnection point to provide the staff with a sufficiently large insulation interval between the equipment in need of repair and other energized parts. In the long-term operation, various reasons may lead to various failures of the cutter brake, causing great security risks to the safe and stable operation of the power grid and personal safety. This paper is mainly focused on analyzing the abnormal phenomenon of the poor contact of the dynamic and static contact fingers of B phase of I cutter brake of Xinlang Line 1 in the 220kV substation, which causes most of the current to flow through the B phase of Xinlang Line 2. Future management and preventive measures for this type of cutter brake are also proposed in this paper.

A case study on transformer ferroresonance for subsea cable connected 230 kV substations using PSCAD

This research paper presents a comprehensive procedure on how to perform a ferroresonance study in a system dealing with the addition of subsea cable interconnector-2 between two 230 kV substations which is previously linked by subsea cable interconnector-1. Addition of a subsea cable interconnector-2 needs to be investigated for ferroresonance in planning and designing stages itself since the interaction between cable capacitive reactance and power transformers-magnetizing core which is a non-linear inductance may cause ferroresonance. The investigation is conducted in three stages namely energisation, de-energisation and stuck pole conditions of circuit breaker. Each stage concentrates on the overvoltage patterns as ferroresonance is characterized by overvoltage. The analysis is conducted in PSCAD/EMTDC software and the modelling of entire study network is done according to the CIGRE WG C4.307. The maximum overvoltage for each stage is found by performing 200 cases of statistical simulation and it is compared with the rated withstand voltage of the equipment. Through a rigorous analysis of overvoltage characteristics under different scenarios, suggestion has been given whether the subsea cable interconnector-2 can be safely operated during the studied cases without the risk of ferroresonance.

ДОСЛІДЖЕННЯ ПОДВІЙНИХ ЗАМКНЕНЬ НА ЗЕМЛЮ В МЕРЕЖАХ 10 КВ З ІЗОЛЬОВАНОЮ НЕЙТРАЛЛЮ

Reliability indicators of power supply systems as a whole are largely determined by the level of reliability of distribution electrical networks with a voltage of 6-35 kV. Emergency in networks with a voltage of 6-35 kV, operating in the mode with an isolated neutral, is often associated with internal overvoltages. Single-phase short-circuits occur in places of defects in the insulation of cable lines and substation equipment due to the aging of the insulation, non-compliance with the manufacturing technology of insulating structures at factories, non-compliance with the requirements of the instructions during the installation and operation of the equipment, as well as due to mechanical damage, which, sometimes at the time of their appearance, lead to only a partial decrease in electrical strength. Overloads lead to defects. Single-phase short-circuits in 10 kV networks that are not eliminated in time can lead to double earth faults. For protection in these networks, such protections as current cut-off, maximum current protection, current cut-off, zero-sequence current protection, current protections with blocking at minimum voltage are used. However, there are cases when there are cases of negative operation of such protections at a 10 kV substation during double earth faults. For example, a phase A short circuit occurred on the first line, which receives power from the buses of the investigated substation, and another short circuit (phase B) occurred on the second line. Instead of tripping the two damaged lines, the input circuit breaker tripped by mistake. This de-energized other (undamaged) lines that are fed from the same bus section as the damaged lines. Under such conditions, further studies of the currents in the lines during double circuits are required. For this, the use of the Matlab application program package is justified. This will significantly reduce the costs of physical modeling and verification of proposed proposals. The paper presents the results of studies of double earth faults in 10 kV networks with an isolated neutral in the "MATLAB" program package.