Air-insulated Substation Research Articles

Partial Discharge Positioning Method in Air-Insulated Substation With Vehicle-Mounted UHF Sensor Array Based on RSSI and Regularization

Partial Discharge Positioning Method in Air-Insulated Substation With Vehicle-Mounted UHF Sensor Array Based on RSSI and Regularization

Substation technology selection for environment efficient power distribution system in India: an integrated AHP-TOPSIS-based approach

PurposeThis study aims to provide a scientific framework for the selection of suitable substation technology in an electrical power distribution network.Design/methodology/approachThe present paper focuses on adopting an integrated multi-criteria decision-making approach using the Delphi method, analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS). The AHP is used to ascertain the criteria weights, and the TOPSIS is used for choosing the most fitting technology among choices of air-insulated substation, gas-insulated substation (GIS) and hybrid substation, to guarantee educated and supported choice.FindingsThe results reveal that the GIS is the most preferred technology by area experts, considering all the criteria and their relative preferences.Practical implicationsThe current research has implications for public and private organizations responsible for the management of electricity in India, particularly the distribution system as the choice of substations is an essential component that has a strong impact on the smooth functioning and performance of the energy distribution in the country. The implementation of the chosen technology not only reduces economic losses but also contributes to the reduction of power outages, minimization of energy losses and improvement of the reliability, security, stability and quality of supply of the electrical networks.Social implicationsThe study explores the impact of substation technology installation in terms of its economic and environmental challenges. It emphasizes the need for proper installation checks to avoid long-term environmental hazards. Further, it reports that the economic benefits should not come at the cost of ecological degradation.Originality/valueThe present study is the first to provide a decision support framework for the selection of substation technologies using the hybrid AHP-TOPSIS approach. It also provides a cost–benefit analysis with short-term and long-term horizons. It further pinpoints the environmental issues with the installation of substation technology.

Improved Methods for UHF Localization of Partial Discharge in Air-Insulated Substations

A time-difference-of-arrival-based partial discharge (PD) location system that utilises prior knowledge of substation layout is presented. We propose a new time delay estimator that employs onset detection techniques and demonstrate, through experimental results, that it is at least 2.8 times more accurate than other conventional estimators. Using knowledge of a substation’s layout, we develop a minimum mean-square-error (MMSE)-based location estimator and an algorithm that optimises antenna placement to maximise location accuracy in regions occupied by high-voltage equipment. Simulation results show that a system that uses the proposed techniques is 5.9 times more accurate than a more conventional system in a high-noise environment.

UHF Sensors Based Localization of Partial Discharge Sources in Air-Insulated Electrical Substation Using TDOA and Relative RSS Information

Time-difference of arrival (TDOA) based localization of partial discharge (PD) sources using Ultra High Frequency (UHF) technique often provides uncertain accuracy because of unavoidable errors in TDOA estimation between PD pulses. This paper presents a novel localization approach utilizing TDOA and relative received signal strength (RRSS) information together for improving the localization accuracy of PD sources within air-insulated substations (AIS). A complete PD localization system governed by this approach has been developed using multiple UHF PD sensors. The effectiveness of the proposed PD source localization approach has been validated through laboratory and field-based experiments in real-life AIS.

An Integrated Lightning Risk Assessment of Outdoor Air-Insulated HV Substations

Although various lightning protection methods have been used in the industry, many outdoor high-voltage (HV) substations are still experiencing high failure rates due to lightning strikes. The applications of these rule-of-thumb-based methods generally lack coherence among the practitioners. IEC 62305-2 provides a systematic way for practitioners to assess the lightning risk for buildings or structures in a probabilistic way. However, this standard has not explicitly covered the application of HV substations. Moreover, IEC 62305-2 involves a tedious set of risk factors which may hinder many practitioners from applying the aforementioned standards while other preferred rule-of-thumb methods are available. As IEC 62305-2 does not specify the applicability to lightning risk assessment in HV substations, this paper proposes a novel approach to complement the standard-based risk assessment process. During this integrated risk assessment process, significant risks are identified, followed by ambiguous risks that will be adjusted in subsequent phases. The significant ambiguous risk factors such as fire load function (rf), environmental factor (CE), LPL class, and other governing factors have been analyzed and discussed. By adjusting these significant risk factors, the practitioners will understand the adjusted risk factors in relation to the practical implementation of lightning protection system (LPS). Therefore, integrating the substation characteristics, assumptions, and findings of ambiguous risk factors can result in a successful integrated lightning risk assessment process.

Localization of Multiple Partial Discharge Sources in Air-Insulated Substation Space by RF Antenna Sensors Array

This paper proposes a method to localize multiple partial discharge (PD) sources in air-insulated substation by using radio frequency (RF) antenna sensors combining with clustering algorithm, which solves the problem that multiple PD or interference sources are difficult to localize in air-insulated substation (AIS). Our research group made four omnidirectional RF antenna sensors, the detection frequency band was 250 MHz-3 GHz, the voltage standing wave ratio (VSWR) of the RF antenna in the detection frequency band was less than 2, which meets the detection requirements. The scenes of multiple PD sources in AIS were simulated in the laboratory, the time difference of arrival (TDOA) was collected through four RF antennas, and the clustering effects of K-means and Two Step algorithms were compared. Based on the normal distribution characteristics of TDOAs and the better Two Step algorithm, a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\sigma $ </tex-math></inline-formula> -Two Step algorithm was proposed to process TDOAs and output the centers of TDOAs. Newton iterative algorithm was used to solve the localization equations. The results show that the average localization error of two PD sources was 0.21 m and that of three PD sources was 0.45 m. The PD localization tests were carried out in an actual AIS in China, the proposed method localized a corona discharge on a post insulator and a corona discharge on a disconnector. Through the verifications with an ultraviolet camera, it was obtained that the localization errors at each position were within the range of 0.6-2 m.

3D Localization Method of Partial Discharge in Air-Insulated Substation Based on Improved Particle Swarm Optimization Algorithm

Partial discharge (PD) localization in an air-insulated substation (AIS) can be used to assess insulation conditions efficiently. Many localization methods have been reported during the past few years. However, the error of the localization results has been large or the localization algorithm too inefficient. The reason is that the localization equation set is nonlinear and non-symmetrical. In this paper, an improved particle swarm optimization (PSO) algorithm is proposed to improve the localization accuracy in 3D. Firstly, the proposed localization method is based on the symmetrical antenna array and the location error distribution is analyzed. Secondly, the objective function of PSO is constructed using the error distribution. Specifically, the 3D location target is divided into two steps—plane coordinates and height. The two targets are optimized respectively. To verify the method, a test is carried out by a prefabricated fault bushing in the laboratory to compare with the existing methods. According to the results, the localization error is 0.21 m, which can locate the PD source accurately. A complete calculation takes 42.29 s, and the efficiency is increased by 16.13 times under the same accuracy. The comparison results show that the proposed method can greatly improve the efficiency while ensuring accuracy.

Analysis of lightning transient performance of 132 kV transmission line connected to Miramar wind farm: A case study

Lightning strikes are one of the main causes of power system trip-outs. When the overhead transmission line (TL) connected to a wind farm is struck by lightning, large currents propagate to the substation, resulting in severe problems. To enhance the performance of wind farm substations, the transient behavior during lightning must be analyzed. The main contribution of this paper is to study the lightning behavior of wind farm substations whose design is different from other conventional substations. The lightning surge overvoltages caused by back flashover and shielding-failure of the 132 kV overhead TL connected to the 33/132 kV air-insulated substation (AIS) of Miramar wind farm are calculated. This wind farm has been built in Argentina to achieve grid connection and power transmission with a total capacity of 98.7 MW. The work investigates the fast-front lightning transient overvoltages in the AIS caused by lightning flashes striking the 132 kV overhead TL. The distributed parameter model of the TL, including towers, phase-conductors, the shielding-wire, insulators, and the span, is investigated using Digsilent Power Factory software. In addition, the AIS apparatus, including surge arresters (SAs), two 60 MVA transformers, and circuit breakers, are also considered in the model. The strike is applied first at the shielding-wire, and the impact on the transient overvoltages at the TL and the substation during the back flashover phenomenon are analyzed. On the other hand, the shielding-failure is studied and the transient overvoltages at the TL and the substation are analyzed. The impact on the transient overvoltages at the TL and the substation is investigated, taking into account the SA protection operation, and its dissipated energy during lightning flashes is calculated. The study results are important for the lightning protection systems design of wind farm substations connected to overhead TLs.

Statistical analysis of non-standard overvoltage waveforms measured at 220 kV terminals of a power transformer,,

Power transformers are designed to withstand switching and lightning overvoltages which can occur in the power system. The knowledge about waveshapes of these events grows rapidly with the introduction of online transient monitoring systems. Consequently, it is important to compare standard test voltage impulses with the ones existing in the power system. In this paper, 123 measured overvoltages in 220 kV air-insulated substation are analyzed. The observed overvoltages are fitted using double exponential mathematical function. Function parameters are calculated using genetic algorithm. To compare measured signals with the standard ones, statistical analysis of their parameters is performed. This approach can help in better dimensioning of the transformer insulation in order to withstand the real overvoltages that can occur in the power network and in avoiding potentially dangerous situation due to the resonances. Additionally, frequency domain severity factor is calculated for the observed signals.

A New Approach for Decision Support of the Selection of Construction Technology of High-Voltage Substations Based on AHP Method

The process of building and modernizing the high voltage substations generate the problems concerning the determination of the optimal technological solutions, which should be friendly to the environment, meet the criteria of sustainable development and be cost effective. Since many institutions are involved in the decision making process to reach an optimal solution for the planned substation, consensus is sometimes not possible without the commitment of the instruments which support this decision. Hence, in this paper the authors proposed a new approach based on the Analytic Hierarchy Process (AHP) method in relation to supporting the decision of choice of high voltage substation technology between two commonly applied solutions: Air Insulated Substation (AIS) and Gas Insulated Substation (GIS). On the basis of applied regulations as well as expert opinions a survey was prepared and then analyzed in terms of the elaborated criteria. The results show that the AHP method is well suited to the issue under consideration, indicating clearly that GIS technology is strongly preferred. Hence, this opens the discussion for the use of the AHP method in a wider form in the decision support process in the specific field, which high-voltage engineering is.

A RSSI-AOA-Based UHF Partial Discharge Localization Method Using MUSIC Algorithm

To monitor the insulation deterioration of power equipment and realize prompt fault warning systems in air-insulated substations, in this study, we propose a multiple signal classification (MUSIC) algorithm-based partial discharge (PD) localization method with an angle of arrival (AOA) and ultrahigh frequency (UHF)-received signal strength indicator (RSSI). Compared with traditional UHF time-difference-based techniques, this RSSI-based AOA localization method is a more economical solution. In addition, by comparing the measured RSSI vector to a prebuilt reliable reference data set, the MUSIC method can effectively locate the direction of the PD source with high accuracy. Compared with the method that directly determines the smallest RSSI values by several sensors, this method can accomplish localization by fewer sensors without impeding accuracy. Furthermore, the interpolation method was adopted to improve the precision of the relationship curve of AOA/RSSI, which it did with a limited number of sensors. Laboratory tests were conducted to verify the accuracy of the proposed method, and most of the localization errors were less than 1°, which indicates its potential application in the prompt identification of faults regarding the insulation deterioration of power equipment in substations.

A UHF Sensor Based Partial Discharge Monitoring System for Air Insulated Electrical Substations

A Partial Discharge (PD) monitoring system for Air Insulated Substations (AIS) has been developed for monitoring of partial discharge activities of various insulators and insulating media that are distributed over an electrical substation. The proposed system utilizes four UHF sensors, which are to be placed around the area of interest so that any impulsive UHF signal originated from PD activity can be captured and subsequently processed for detection and localization of multiple PD sources. To improve the localization accuracy and to improve the detection specificity, i.e. to eliminate false impulsive UHF signals originated from other sources, a novel nearest-neighbour based approach is proposed, which utilizes the physical layout of the AIS to identify most probable PD source locations. The proposed algorithm can accurately find the PD source locations even in the presence of high time-delay-of-arrival (TDOA) estimation error by making necessary corrections in the PD source location estimation. The proposed algorithm has been field trialed in many small and medium-size distribution substations. A detailed comparative study with the other algorithms in different extreme situations has been performed with the help of simulation and laboratory-based testing. The obtained results are worthwhile for supporting widespread implementation of the proposed method.

Partial discharge direction‐of‐arrival estimation in air‐insulated substation by UHF wireless array and RSSI maximum likelihood estimator

The quick detection and localization of partial discharge (PD) in an air-insulated substation (AIS) based on ultrahigh-frequency (UHF) sensor arrays are efficient for power equipment monitoring. The adopted UHF PD time difference of arrival (TDOA) methods mainly use the time difference of electromagnetic wave signals. Thus, the system requires both a high sampling rate and time synchronization accuracy, leading to a high cost and large size. In this study, the feasibility and accuracy of PD DOA in an AIS were investigated using a UHF wireless sensor array and the received signal strength indicator. First, the power pattern of the designed UHF wireless sensor array was obtained via an offline experiment. Then, a statistical approach to the PD DOA method based on the maximum likelihood estimator was employed to obtain the preliminary DOA result. Finally, interpolation and clustering algorithms were used to improve the accuracy of the DOA. A laboratory test was conducted. The average error of the PD DOA was less than 6{\deg}, and the cost-effectiveness and portability were clearly improved.

Intelligent learning approach for UHF partial discharge localisation in air‐insulated substations

To achieve comprehensive insulation deterioration motoring of power equipment and early fault warning in air-insulated substations, a data-driven partial discharge (PD) source localisation method employing noisy ultra-high frequency (UHF) received signal strength indicator (RSSI) and particle filter is proposed in this study. Compared with the existing UHF time-difference-based techniques, UHF wireless sensor arrays and RSSI-based methods provide an economical and high-adaptability solution. However, owing to the multi-pathing and shadowing effects, UHF signal attenuation cannot be modelled. Therefore, a Kalman filter was employed to smoothen the RSSI signal. Furthermore, a semi-parametric regression model is proposed to achieve a more accurate relationship between the RSSI and the transmission distance. Finally, in contrast to traditional localisation algorithms directly based on the RSSI ranging model, a particle filter was used to achieve higher accuracy. It predicted the best distribution of the position of PD by learning and considering all the system states of the previous moment. The laboratory test was performed within an area of 6 m × 6 m, and the results demonstrate that the mean PD source localisation error was 1.16 m, which gives a potential application for the identification of power equipment with insulation deterioration in a substation, while the accuracy is still needed to be verified further by field tests.

Fault early warning in air‐insulated substations by RSSI‐based angle of arrival estimation and monopole UHF wireless sensor array

To achieve comprehensive insulation deterioration monitoring of power equipment and fault early warning in air-insulated substations, the detection and localisation of partial discharge (PD) using ultra-high frequency (UHF) antennas were widely studied. The existing UHF PD localisation system is mainly based on time-difference of electromagnetic wave signal, which requires very high time synchronisation accuracy and sampling rate. This study proposes a received signal strength indicator (RSSI)-based angle of arrival (AoA) method using the monopole UHF wireless sensor array. Multiple antennas are evenly placed in a circle frame and form an antenna array. Then an AoA estimation scheme is derived from the radiation pattern of designed UHF antenna. RSSI difference data, interpolation, and clustering are applied to improve the AoA resolution. A field test is performed to verify the effectiveness of the proposed PD localisation system. The results show that the estimated error on average is below 3.5°. Compared to the time-difference-based method, the accuracy of the designed system is more feasible for practical application of fault early warning considering its significant low-cost feature.

Analysis and development of an electromagnetic exposure map based in spatial interpolation

The increasing demand for electricity has led humans to a growing exposure to artificial sources of electromagnetic emission, making it essential to determine the intensity of electromagnetic fields (EMFs), which is subject to the population of a given area. This Letter proposes an analysis of EMF exposure levels and spatial distribution over the region of the input and power circuits of a 230 kV/60 Hz air-insulated substation. For this, measurement protocols were determined based on current standards and from spatial interpolation methods, a contour map was developed, allowing a complete evaluation of the behaviour and levels of EMF throughout the region. The results obtained indicate that exposure levels in this region are below those recommended by regulatory agencies.

Radiometric localisation of partial discharge sources inside Air‐insulated electrical substation

Monitoring partial discharge (PD) activities inside electrical substation using few ultra high frequency (UHF) sensors mounted around the periphery of the substation could be a useful and economical tool. In this work, an experimental study has been conducted in the laboratory and in substations to investigate the localisation ability of the UHF PD detection system. For localisation, one needs to calculate time difference of arrivals (TDOAs) between the UHF waveforms obtained from the multiple sensors mounted around the substation. After that these TDOAs are used for localisation of the PD sources. In this paper a novel joint entropy (JE)-based TDOAs calculation method is proposed and also compared with the existing techniques. For localisation of PD sources, a modified direction of arrival (DOA)-based method for the near field is proposed, as found to be suitable when the sensors are mounted around the substation. Obtained results in TDOA estimation using the proposed JE method is in line with other technique; however, it was found to provide consistent results and is useful in an extreme situation. Modified DOA-based localisation algorithm found to provide improved performance due to the elimination of approximation as required in previously reported far-field-based localisation system for the air-insulated substations.

RSSI-Power-Based Direction of Arrival Estimation of Partial Discharges in Substations

The localization of partial discharges in air-insulated substations using ultra-high frequency technology is widely studied for power equipment early warning purposes. Ultra-high frequency partial discharge localization systems are usually based on the time-difference of electromagnetic wave signals. However, the large size of test equipment and the need for a high sampling rate and time synchronization accuracy limit their practical application. To address this challenge, this paper proposes a power-based partial discharge direction of arrival method using a received signal strength indicator from an ultra-high frequency wireless sensor array. Furthermore, the Gaussian mixture model is used for noise suppression, and the Gaussian process classifier is used for line of sight received signal strength indicator data identification. Laboratory tests are performed and the results show the average error of direction of arrival is less than 5°. The results verify the effectiveness of the proposed partial discharge localization system.

Partial Discharge Angle of Arrival Estimation Using UHF Wireless Sensor Array

The detection and localization of partial discharge (PD) in air-insulated substations by ultra-high frequency (UHF) technology is widely studied. Existing UHF PD localization system mainly focus on time-difference of UHF signal, which requires very high synchronized sampling rate. This paper proposes a received signal strength (RSS) based angle of arrival (AoA) method by a circle UHF wireless sensor array. An AoA estimation scheme is derived through the radiation pattern of designed UHF antenna. Interpolation and neural network are applied to improve the AOA resolution. A field test is performed to verify the effectiveness of the proposed PD localization system. The results show that the estimated error on average is below 7°. Compared to the time-difference-based method, the accuracy of our designed system is more feasible for practical application considering its significant low-cost feature.

Partial Discharge Localization through a UHF Signal Amplitude Strength Attenuation Approach

Accurate measurement and localization of Partial Discharge (PD) is necessary for safe and stable operation of power equipment. Recently, the method based on the amplitude strength of Ultra High Frequency (UHF) signals has been proposed that bearing a low hardware requirement compared to time-difference-based methods. However, the widely studied fingerprinting based positioning technology is hard to deployed due to a heavy burden of fingerprinting map building. Therefore, this paper proposes an amplitude strength attenuation model and localization equation is proposed for PD localization in air-insulated substation. The field test is performed and the results show that the mean PD source localization error is 2.51 meters which is enough to distinguish the power equipment that having insulation deterioration.