System Protection Schemes Research Articles

Modeling of Power System Protection Scheme by Distance Relay for Distribution Lines

Modeling of Power System Protection Scheme by Distance Relay for Distribution Lines

Dependability Analysis of the Negative-Sequence Turn-to-Turn Fault Protection Schemes for MMC-HVDC Converter Transformers

This paper addresses two complex areas of research: the detection of turn-to-turn faults (TTF) in power transformers and the impact of inverter-based resources on the TTF protection scheme operation. Detecting turn-to-turn faults in power transformers by protection algorithms poses a challenge due to the minimal fault currents observed at transformer terminals. Yet, the demand for dependable TTF protection is very high because of the high fault currents inside the shorted turns and the resulting damage consequences. On the other hand, for such sensitive protection, adverse conditions such as transformer inrush currents or CT errors may lead to protection maloperation. Moreover, the fault current characteristic of the inverter-based source infeed is very different compared to the synchronous machine infeed, particularly concerning the negative-sequence current used in the TTF protection schemes, which calls for thorough research analysis. A simulation model of the converter transformer capable of simulating TTFs, and the Modular Multilevel Converter (MMC) for a High Voltage Direct Current (HVDC) transmission link, has been developed. The test results of turn-to-turn fault protection schemes in inverter-based generation-dominated power systems compared to the synchronous generator infeed are presented. The negative-sequence current protection quantities are analysed in more detail for TTFs with small and large number of shorted turns, i.e. without and with reactive negative-sequence current injection by the MMC control. Finally, the paper assesses the dependability of the transformer differential protection and sensitive TTF protection schemes in detecting faults with different numbers of shorted turns and fault resistance for TTFs occurring in the star and delta winding of the converter transformer.

Intelligent agents for advanced power system protection schemes

This study explores the incorporation of intelligent agents to improve power system safety, using several computational models including machine learning, rule-based systems, neural networks, and fuzzy logic. The research assesses the effectiveness and efficiency of these agents in promptly identifying, categorizing, and responding to faults in the power system architecture using empirical analysis. The results demonstrate the higher performance of agents based on neural networks, with an average improvement in fault prediction accuracy of 38% compared to systems based on rules. Furthermore, the evaluation of power system devices demonstrates a direct relationship between greater voltage ratings and increased expenses for both installation and maintenance, underscoring their crucial importance within the system. An examination of fault severity reveals that greater severity failures have a direct and significant influence on system downtime. These problems lead to longer interruptions, which emphasizes the need of implementing effective fault management systems. Intelligent agents' actions have different costs and reaction times. Actions based on neural networks have lower average costs and shorter response times, demonstrating their cost-effectiveness and efficiency in addressing faults. The study of percentage change highlights the importance of using various kinds of intelligent agents and higher-rated devices. This research offers insights into performance differences and the consequences for optimizing protection measures. This research provides a thorough understanding of how intelligent agents may enhance power system protection. It also offers guidance for future improvements in creating power grid infrastructures that are robust, dependable, and adaptable.

Behaviour analysis of H‐bridge high‐voltage capacitor banks fault on 230‐kV substation using discrete wavelet transform

AbstractThe protection of traditional high‐voltage capacitor banks relies on an unbalance relay which operates when an internal fuse is blown. However, the unbalance relay cannot indicate the cause of the fault. Thus, an operator wastes time and human resources investigating the fault issues. In this paper, a fault which occurred in a 230‐kV power system of Electricity Generating Authority of Thailand was observed by performing simulations using the Power Systems Computer Aided Design (PSCAD) program. The study system based on the double bus station and 72 MVAR capacitor banks was installed in the form of a back‐to‐back topology. Three scenarios were considered: normal condition, fault occurrence in one capacitor bank and fault occurrence in both capacitor banks. Current characteristics such as the current phase and difference in unbalance current were considered. In addition, discrete wavelet transform was applied to solve the ambiguity of current generated from the PSCAD. The authors’ results suggest that identifying fault events using a coefficient of wavelet is more efficient than relying on the current amplitude. The findings mentioned in this paper can be applied in a traditional power system protection scheme to enhance a system's reliability.

Dynamic risk analysis of accidents chain and system protection strategy based on complex network and node structure importance

Due to the increasing complexity and nonlinearity of complex industrial systems, traditional risk analysis methods have become inapplicable. A method of dynamic risk analysis and system protection based on complex networks and node structure importance was established. The effectiveness of this method is demonstrated through case studies, where we compare and analyze six protection strategies. In light of the topology and directivity of the accidents chain network (ACN) in the complex industrial system, a node structure importance evaluation method and an ACN evaluation method were established to measure the protection cost. An optimal protection strategy model with the protection cost constraint was proposed, and a study was carried out on the ACN of UHV converter transformer. The results show that ACN in UHV converter transformer belongs to a scale-free network. The structural importance evaluation method can identify the critical nodes in ACN, and better reflect the structural importance of nodes than the traditional degree indicator. Considering the dual objectives of the complex system, the optimal protection strategy proposed by the optimal protection model achieves better effect than other strategies, no matter how the protection cost factor and the protection cost budget coefficient change.

A novel transmission system protection scheme using optimal wide-area measurements

A novel transmission system protection scheme using optimal wide-area measurements

IoT Supervised PV-HVDC Combined Wide Area Power Network Security Scheme Using Wavelet-Neuro Analysis

Power system networks are one of the most widely used methods in the real world for transferring large amounts of electrical energy from one location to another. At present, High Voltage Direct Current Transmission is preferred for long distances over hundreds of miles due to minimal power loss and transmission cost of transmission.Due to an increase in power demand, integration of renewable sources to minimise the voltage fluctuations and compensate for power loss is necessary. This is a mandatory requirement to produce sophisticated protection methods for mainly smart systems under various balanced and unbalanced fault conditions. The system protection scheme must respond as quickly as possible to protect the connected devices in a smart environment. The network must be monitored and protected under various weather conditions as well as electrical parametric problems. The proposed research work is carried on the basis of physical monitoring with the aid of the Internet-of-Things and electrical parameters calibrated with the help of wavelet analysis. A wavelet is a mathematical tool to investigate the behaviour of transient signals at different frequencies, which provides important information related to the detailed analysis of faults in power networks. The major goals of this research are to analyse faults using detailed coefficients of current signals through the bior-1.5 mother wavelet for fault identification and artificial neural network analysis for fault localization. This proposed approach furnishes an IoT supervised Photovoltaic - High Voltage Direct Current (HVDC) combined wide area power network security scheme using wavelet detailed coefficients under various types of faults with Fault-Inception-Angles.

Systematic protective scheme for mega‐city power systems against stray currents caused by metro systems

AbstractIn modern megacities, stray currents from metro systems intrude into multiple transformers' neutral points becoming a potential threat to the high‐capacity transformers. Neutral current anomalies are exacerbated in unprotected substations when we instal guards at single stations. This paper presents a system protection strategy for multiple substations affected by stray currents in modern megacities. The model, taking Shanghai as an example, includes the spatial distribution information of the urban electrical energy transmission structure, the power system, and the metro system. A Particle swarm algorithm is used to calculate the resistance values of the devices for each station. Further stability tests are performed to select the optimal protection solution. The results show that when protection is considered as a system, the protection runs well and the neutral current level remains below the unprotected level when the protection fails at a single station or multiple stations.

On the methodology of fingerprint template protection schemes conception : meditations on the reliability

Among the most major potential attacks against fingerprint authentication systems are those that target the stored reference templates. These threats are extremely damaging as they can lead to the invasion of user privacy. The countermeasures to secure fingerprint templates are therefore an indisputable necessity. In literature, although there are so many approaches that address this kind of vulnerability, it turns out to be very difficult to generalize their uses. Given that each system has its own particularities, going from the fingerprint trait acquisition to the matching process, the majority of protection schemes, that are proposed as generic solutions, are not sufficiently mature for large-scale deployment. Consequently, we believe that the methodology of fingerprint template protection schemes conception should be oriented to build specific protection schemes for every unprotected system, which will provide the best compromise between performance and security compared to any generic protection solution. By adopting this methodology, we propose in this paper a new protection scheme for fingerprint templates that is well adapted to a well-known existing unprotected fingerprint minutia system. Our experimental results, obtained using standard benchmarks such as FVC 2002 DB1 and DB2, have proven that the proposed technique meets the requirements of revocability, unlinkability, non-invertibility, and high recognition accuracy.

Protection schemes for a battery energy storage system based microgrid

This paper evaluates directional and adaptive overcurrent protection schemes in microgrids. A microgrid supported by a centralised Battery Energy Storage System (BESS) is chosen for the study. The stringent PQ controller of BESS will not allow it to dissipate into a fault, during its charging mode, causing the conventional directional schemes to mal-operate. A direction estimation scheme using magnitude and angle of superimposed positive sequence impedance is proposed to address this issue in BESS. Further, two fault detection techniques are proposed for BESS integrated feeders. The Main Protection Unit (MPU) detects an internal fault when there is a mismatch in the direction of relays at either end of a feeder. The second scheme uses adaptive overcurrent relay settings. Since the fault current is limited with PQ control, the pickup current is calculated dynamically with this control. Whereas a fixed pickup current is chosen, when the BESS inverter is voltage controlled. Simulations have been carried out using MATLAB/SIMULINK software. The proposed schemes work well for bidirectional power flows and in grid connected and standalone modes of microgrid operation.

Validation of Voltage Instability Detection and Control Using a Real Power System Incident

This paper applies a voltage instability monitoring method based on voltage and current measurements from a transmission bus PMU on the Hellenic Interconnected System using both unstable and marginally stable scenarios, derived from the historical 12 July 2004 blackout of the Athens area. The effectiveness, selectivity and reliability of the proposed monitoring method is clearly demonstrated, allowing its integration into a System Protection Scheme with direct load shedding. It is shown that the proposed instability detection and control scheme could have prevented the voltage collapse if applied at the time of the event.

Machine learning applications in power system fault diagnosis: Research advancements and perspectives

Newer generation sources and loads are posing new challenges to the conventional power system protection schemes. Adaptive and intelligent protection methodology, based on advanced measurement techniques and intelligent fault diagnosis such as machine learning (ML), is found to be useful to meet these challenges. A large number of research works are reported on ML-based power system fault diagnosis. However, ML techniques are evolving at a very fast pace, and an inclusive, as well as state-of-the-art review on ML-based power system fault diagnosis, is not available in the literature. Given this need and growing trend towards ML, the study presented in this paper aims to provide a comprehensive review of ML-based power system fault diagnosis. At first, efforts have been made to enlist the issues present in conventional fault diagnosis which led to the popularity of ML techniques. Also, a baseline framework and workflow for ML-based fault diagnosis are presented. Next, various unsupervised and supervised learning techniques have been discussed separately which have been used by several researchers for fault diagnosis. The discussion throughout is supported with tabulated facts for fault detection, classification and localization works with techniques used, different simulation tools used, and their application system. The advantages and disadvantages of all the techniques of fault diagnosis have also been discussed which will help the readers in the selection of techniques for their research. A brief review of reinforcement learning and transfer learning is also given as they are gaining popularity in power system-related studies and have the potential to be used for fault diagnosis. Finally, the research trends, some key issues, and directions for future research have been highlighted.

Methodology for the improvements in synchrophasor based System Integrity Protection Schemes under stressed conditions

Nowadays, the power system is characterized by a conglomeration of ultra and extra-high voltage AC and DC transmission corridors, multi-terminal DC (MTDC), and a new generation having Ultra Mega Power Plants (UMPP). It consists of a large power transmission and distribution network across the country along with old conventional generating units and insertion of Renewable Energy Sources (RES). The System Integrity and Protection Schemes (SIPS) play a crucial role in maintaining a secure and reliable grid and assist in effective grid management during severe power system contingencies. In this article, the operational experiences of three prime important SIPS in India are presented. The demerits in existing SIPS are pointed out and a methodology is proposed to overcome them. The performance and effectiveness of the proposed methodology are evaluated by simulation studies on the 39-bus New England system nested with the HVDC link in MATLAB. Simulation results confirmed the authenticity of a proposed methodology in preserving system integrity. Results are validated using Electrical Transient Analyzer Program (ETAP), which is a very powerful design and analysis tool and has an extremely user-friendly interface.

Estimating frequency stability margin for flexible under-frequency relay operation

SmartGrid solutions are often misinterpreted as complex approaches requiring large amounts of (online) data and computational power for delivering high-quality results. With today's technology, this is surely the most obvious and technically achievable approach for dealing with complex problems. However, by taking this road in the power system field, providing the required high-level reliability becomes a challenging task. Therefore, a thorough consideration of whether increased complexity justifies the gains is surely warranted, especially when it comes to power system protection, where the applied procedures are all about transparency, simplicity and robustness – which is often in contrast to the above interpretation of SmartGrids. Therefore, the motivation of the presented research was to design an effective SmartGrid solution for avoiding power system frequency instability, appropriate for real-life application. Under-frequency load-shedding protection is the subject of many research activities that often result in complex and, consequently, unfeasible suggestions. In contrast, this paper presents an effective RoCoF-based upgrade to the conventional approach, eliminating its most important shortcoming: inflexibility. By estimating frequency stability margin in real time, shedding decisions remain local, whereas the overall efficiency of this system protection scheme is brought to the level of the most sophisticated solutions available in the literature.

A Survey of Traveling Wave Protection Schemes in Electric Power Systems

As a result of the increase in penetration of inverter-based generation such as wind and solar, the dynamics of the grid are being modified. These modifications may threaten the stability of the power system since the dynamics of these devices are completely different from those of rotating generators. Protection schemes need to evolve with the changes in the grid to successfully deliver their objectives of maintaining safe and reliable grid operations. This paper explores the theory of traveling waves and how they can be used to enable fast protection mechanisms. It surveys a list of signal processing methods to extract information on power system signals following a disturbance. The paper also presents a literature review of traveling wave-based protection methods at the transmission and distribution levels of the grid and for AC and DC configurations. The paper then discusses simulations tools to help design and implement protection schemes. A discussion of the anticipated evolution of protection mechanisms with the challenges facing the grid is also presented.

Improvements in Existing System Integrity Protection Schemes Under Stressed Conditions by Synchrophasor Technology—Case Studies

In this modern era, the power system is stigmatized by a conglomeration of ultra-high voltage AC and DC, multi-terminal DC, and extra-high voltage AC transmission networks. It consists of a large distribution network beyond the country along with traditional generation having Ultra Mega Power Plants (UMPP) and growing ingress of Renewable Energy Sources (RES). The System Integrity and Protection Schemes (SIPS) play a crucial role in preserving a secure and reliable grid and facilitate efficient grid control during severe power system contingencies. In this paper, the operational experiences of three important SIPS in India are presented. Based on a thorough analysis, the drawbacks of these SIPS are identified and an algorithm is proposed to overcome the drawbacks using synchrophasor technology. The performance and capability of the proposed algorithm are evaluated by simulation studies on the 39-bus New England system embedded with HVDC link in MATLAB. Simulation results consummated confirm the effectiveness of the scheme in preserving system integrity. Results are validated using Electrical Transient Analyzer Program (ETAP), which is a very powerful design and analysis tool and has an extremely user-friendly interface.

Fault location in distribution system using convolutional neural network based on domain transformation

Distribution lines are integral parts of the modern power system, which can affect the security and stability of power supply directly. An effective power system protection scheme should be able to detect all occurring faults as soon as possible. There are two tasks in fault diagnosis. One is the fault classification, where high accuracy rates have already achieved. Thus, this paper focuses on the other task, i.e. fault location. Enlightened by Fourier transform, this paper proposes an online data-driven method, which transforms signals from time domain to image domain through signal-to-image (SIG) algorithm and then process the transformed images with framework based on convolutional neural network (CNN). On the one hand, we can extract more crucial characteristic and information from image domain. On the other hand, the CNN-based structure is much smaller than others. It needs less memory space and would be easier to be transplanted to hardware platform. Moreover, the proposed algorithm does not require synchronous devices. The numerical comparison shows that the proposed SIG-CNN fault location model achieves robust and accurate results compared with other data-driven algorithms.

Operational experience and performance evaluation of some of the system integrity and protection schemes

An Indian power system is characterized by a conglomeration of ultra-high voltage AC and DC, multi-terminal DC, and extra-high voltage AC transmission networks. It consists of a large distribution network across the country along with conventional generation having Ultra-Mega Power Plants (UMPP) and increasing penetration of Renewable Energy Sources (RES). The System Integrity and Protection Schemes (SIPS) play an important role in maintaining a secure and reliable grid and assists in effective grid management during severe power system contingencies. This paper presents the operational experience of some SIPS implemented in India along with their performance evaluations. The operational experience of three important SIPS, one in the Northern Regional (NR) grid and another two in the Western Regional (WR) grid of India are presented. The drawbacks in existing SIPS are pointed out and an algorithm is proposed to overcome these drawbacks. The performance and effectiveness of the proposed algorithm are evaluated by simulation studies on the 39-bus New England system embedded with an HVDC link in MATLAB/Simulink. Simulation results consummated confirm the authenticity of the scheme in preserving system integrity. Results are validated using Electrical Transient Analyzer Program (ETAP), which is a very powerful design and analysis tool and has an extremely user-friendly interface.

Dynamic Tuning of the Controller Parameters in a Two-Area Multi-Source Power System for Optimal Load Frequency Control Performance

Frequency control is becoming increasingly critical today due to the growing size and changing structure of complex interconnected power networks. Scaling up economic pressures for efficiency and reliability of the power system has necessitated a requirement for maintaining system frequency, and tie-line power flows as close as possible to scheduled values. High-frequency deviations may degrade load performance, damage equipment, resulting in overloading of transmission lines, which may interfere with system protection schemes, and, finally, may also result in an unstable condition of the power system. More so, Load Frequency Control ( LFC) plays a vital role in the modern power system as an auxiliary service to support power exchanges and, at the same time, to provide better conditions for the trading of electricity. Therefore, the tuning of the dynamic controller (i.e., net frequency and net power interchange errors) is a significant factor in achieving optimum LFC performance. Appropriate tuning of the controller parameters is required in order to achieve excellent control action. In view of this, this paper introduces the dynamic tuning of controller parameters in a two-area multi-source power system with an AC-DC parallel tie line for optimum load-frequency control performance. Matlab/Simulink software is used to realize the system simulation. System dynamic performance is observed for conventional PID tuning by the Ziegler Nichols method and the Kitamori method, fuzzy logic controllers, fuzzy-logic PID controllers, fuzzy PID controllers, and polar-Fuzzy controllers. Furthermore, the frequency and tie-line power response of the interconnected areas were compared based on the setting-time, peak-overshoot, and peak-undershoot. The simulation results show that the responses of the fuzzy-based controllers are faster than those of the classical controllers, resulting in minimized frequency and tie-line power deviations.

Protection scheme for hybrid transmission system using fuzzy inference system and microcontroller

This paper presents a fuzzy inference system and microcontroller-based protection scheme for a combined underground (UG) cable and overhead (OH) transmission line system. The scheme detects, classifies, and locates the fault occurring either in an UG cable or OH transmission line network. Furthermore, the scheme identifies the faulty section. An existing Indian power network i.e., real power system network of C.G. state, consisting of 132 kV, 50 Hz power transmission network connecting Doma substation 220/132 kV to the 132/33 kV Gas Insulated Substation Rawanbhata through combined transmission network is considered. This real power transmission network is simulated by using MATLAB/Simulink software. In this paper, the hardware implementation is also carried out using an open-source hardware, Arduino, which consists of an Atmel 8-bit AVR microcontroller. Both the simulation and hardware results validate that the proposed scheme is accurately detecting, classifying, and locating the fault in less than a half cycle time. Moreover, the percentage error in determining the location of a fault is less than 0.7%.