Relay Performance Research Articles

Performance Evaluation of Distance Relay Operation in Distribution Systems with Integrated Distributed Energy Resources

This article presents the evaluation of the performance of the distance relay (ANSI function 21) when integrating Distributed Energy Resources (DERs) in a Local Distribution System (LDS). The aim is to understand the impacts of and the necessary modifications required in the operation of distance relays, considering different levels of DER aggregation, and identifying any threshold levels before issues arise. To achieve this, first, a comprehensive review was carried out to analyze the impacts generated in the protection systems. Second, by using the DigSilent Power Factory software, the implementation of the distance relay using a IEEE 13 Node Test Feeder was validated. The aggregation of the three fundamental types of DG, synchronous machines, solar panels, and wind turbines, was evaluated. The threshold at which distributed generation power injection begins to compromise distance protection performance was identified. This study compares the outcomes of using mho and quadrilateral protection schemes.

Analyzing error probability in aerial full-duplex relay systems: Exact formulations and optimization techniques

In this study, we investigate the performance of aerial full-duplex relay (AFDR) systems. In particular, we examine two practical scenarios: one where there is no direct link between the transmitter and user, and another where such a link exists. For both scenarios, we develop mathematical models to calculate the closed-form expressions of symbol error probabilities (SEPs) for AFDR systems, using a realistic channel aligned with the fifth generation (5G) and beyond yardsticks. To take care of residual self-interference (RSI) in AFDR, we propose an optimal power allocation strategy. Our numerical findings indicate that the performance in the case with a direct link is considerably higher than that in the case without this link. Additionally, we analyze thoroughly the effects of key parameters such as transmit power, RSI levels, carrier frequencies, and AFDR positions. The effect of RSI is significantly strong, and our proposed optimal power allocation method substantially improves system performance, especially in high transmit power scenarios where error floors may occur. Importantly, the optimal power level is dramatically lower than the conventional value where the optimal power cannot be found. Thus, besides reducing the SEPs, optimal power also helps to prolong the time of operation of AFDR. Monte-Carlo simulations are performed to confirm the accuracy of our derived expressions and demonstrate the efficacy of the proposed approaches in practical scenarios.

Robust distance protection for cross-country faults in power grids with high penetration of inverter- based resources

Cross-country faults can adversely affect the operation of protection devices. Relays whose pickup is based on overcurrent or impedance elements are more likely to fail during cross-country faults. The failure can be expressed as an unnecessary trip of all phases during a single-phase fault or even blocked relay functions. Relays may also fail to operate due to low fault currents, which is the case when power grids make use of many inverter-based resources (IBR) or when two simultaneous faults occur in the same phase and in different locations. This paper proposes a Recursive Discrete Stockwell Transform (RDST) method for addressing the mentioned challenges. The energy content computed by the RDST is used for fault detection and faulty phase selection. A robust distance relay model is proposed to ensure correct relay performance and is combined with a directional and an impedance trajectory module. The proposed method performance is thoroughly evaluated by applying real-time simulations for 6480 different cross-country faults, including three repetitions, four different generators (Synchronous generators, Wind turbine type-III, Wind turbine type-IV), two rating powers, three different fault distances, five different types of faults, and six grid codes. Ninety cases are also tested with real devices in hardware in the loop. Simulation results confirm the method's ability to detect different fault types, even during low fault currents, and to ensure high accuracy in phase selection.

A new relaying approach for protecting TCSC compensated transmission line connected to DFIG based wind farm

In modern power systems, Thyristor Controlled Series Capacitor (TCSC)-compensated transmission lines are crucial in transporting bulk power from large wind farms. However, the performance of conventional distance relays is adversely impacted by the typical fault characteristics of the Doubly Fed Induction Generator (DFIG) and TCSC. To address this challenge, this paper presents a new relaying algorithm such as Complete Ensemble Empirical Mode Decomposition with Adaptive Noise-based Dominant Mode Algorithm-Hilbert Transform (CEEMDAN-DMA-HT) for fault detection and CEEMDAN assisted Enhanced Jaya Optimization-based Random Vector Functional Link Network (EJAYA-RVFL) for fault classification. In proposed fault detection algorithm, the differential current from both ends of the line is subjected to Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, leading to the extraction of distinct intrinsic mode functions (IMFs). Employing the Dominant Mode Algorithm, the IMF with the highest Pearson correlation coefficient, referred to as the dominant IMF, is identified. Subsequently, a comparison between this dominant mode IMF and the original input signal is conducted after passing the obtained signal through the Hilbert Transform (HT), enabling effective fault detection. The proposed classifier leverages a straightforward feature set that quantifies the energy of each phase and the ground. These features serve as inputs for the proposed classifier, facilitating the categorization of different fault types. To evaluate the effectiveness of the proposed relaying algorithm, several fault and non-fault scenarios are simulated on a test power system using MATLAB/Simulink. The results demonstrate that; the proposed fault detection and classification algorithm are able to detect and classify faults in less than a half-cycle. The proposed method gives 100% fault accuracy for fault detection and 99.97 % accuracy for fault classification. Furthermore, the proposed classifier achieves the performance metrics like Precision (0.998), Recall (0.997) and F1-Score (0.996), providing quantitative insights into its accuracy and dependability. Finally, a comparative analysis is carried out with existing approaches.

Cislunar [formula omitted] and [formula omitted] axial orbits and their applications

Cislunar L4 or L5 axial orbit families are continuous asymmetrical periodic orbits from the figure-8 orbit around L4 or L5 Lagrange point of the Earth–Moon system to the halo-family around the Moon. They provide special locations of lunar relay satellites for the lunar south pole due to their offset locations. In this paper, we investigate the orbital characters and applications of cislunar L4 and L5 axial orbits. A construction method of cislunar L4 and L5 axial orbit families is proposed according to their topological feature in the torus space. Then, lunar relay performances, including coverage and eclipse, are analyzed for different cislunar L4 and L5 axial orbits. Numerical computation indicates that 3:1 resonant L4 and L5 axial orbits are the optimal options in terms of the stability, coverage and eclipse avoidance. Lunar relay performances of a two-satellite constellation deployed in these orbits are compared with that in a near rectilinear halo orbit (NRHO). Numerical results show that the constellation of axial orbits can provide longer contact duration to the lunar equator and southern hemisphere than that of the NRHO. Finally, a station-keeping strategy and a transfer design of cislunar L4 and L5 axial orbits are developed, and their fuel costs are studied.

Advancing Distance Relaying Reliability: S Transform Solution for Renewable Energy-Infused Smart Grid

Distance relaying is a crucial component in safeguarding transmission lines globally. However, the presence of Sub-Synchronous Resonance (SSR) introduces challenges, as oscillations in voltage and current magnitudes adversely affect the performance of conventional distance relays. Detecting faults accurately during these oscillations poses a significant challenge for traditional relaying mechanisms. This paper addresses the issue of SSR-induced maloperations in distance relays, particularly in the context of the increasing penetration of renewable energy resources in smart grids. The integration of wind power into the grid generates sub-synchronous oscillations, leading to protection issues. In response, a novel solution leveraging the S transform, a modern signal processing technique, is proposed to enhance the robustness of distance relaying under such challenging conditions. The developed algorithm is implemented in MATLAB and rigorously tested on the First Benchmark Model of sub-synchronous resonance. Simulation of the model is conducted in the PSCAD simulation software, and the results are thoroughly validated in MATLAB. The study demonstrates the efficacy of the S transform-based approach in accurately identifying faults and mitigating maloperations caused by SSR, thereby improving the reliability of distance relaying in smart grids with high renewable energy integration.

A Setting Optimization Ensemble for a Distributed Power Grid Protective Relay

To ensure a stable and reliable power supply, the valid and timely response of protective relays are indispensable. Through the prevention of fault expansions, potential equipment damage or system collapse can be averted, where their setting is one vital prerequisite for such effective implementations. However, the increasing complexity of distribution power systems results in more challenges for protection tuning strategies. Ergo, this paper presents an ensemble that combines the independent factor evaluation (IFE) and quantum genetic optimization (QGO) models to further optimize the performance of relays according to their distributed tuning environment. In this ensemble, both near and far-end fault characteristics can be incorporated. In the first stage, the IFE dimensional reduction model is deployed for massive heterogeneous input data, where the statistical independence of input signals is calculated, the linear transformation matrix to decouple mixed signals is found, the linear combination of such signals is formed, and the non-Gaussian property to sort them is established. This can ameliorate the following calculation efficiency under those high-dimensional data scenarios. Subsequently, the QGO model is designed to further improve relay settings, where qubit representation is built to reduce required chromosomes, the linear superposition of the optimal solution probability in different states is implemented for a better diversity and convergence performance, and a self-adaption quantum gate is established to dynamically update the qubit chromosome groups and two-state solution combinations. Lastly, an empirical case study is presented, which validates the enhanced convergence, accuracy, and rapidity of the proposed ensemble.

Development of 3-phase fault detection, protection, and automation application with the present of DG in AC power system using GOOSE protocol

In this research work, a protection and automation solution is developed, encompassing SEL751 and SEL751A protection relays that communicate through the IEC-61850 Generic Object-Oriented Substation Event (GOOSE) protocol to deliver high-speed detection and clearance of a 3-phase (3P) fault. The study case is a standard IEEE 13-bus grid including the main system generator (G1), power lines, loads, distributed generation (DG), bus bars, and feeders, equipped with protection relays for detecting over-current faults based on time and current. Two protection relays, B1 in the main system and B2 on the DG side, are integrated with a GOOSE protocol communication system. These settings are configured in such a way that, in the event of the main system breaker being disconnected, the DG cannot be connected to the network, making it a suitable setting for anti-islanding mode (AIM). The efficiency of the relay settings is tested by subjecting the power grid to a 3P fault, by the selected Time-Overcurrent (TOC) U3 inverse curve. Throughout the paper, the descriptions of the study, the grid, assumptions, settings calculations, and analysis of results are systematically presented. For the verification of relay settings, the performance of relays is practically tested and accurately analyzed in detail. The results obtained indicate that the presented strategy is quite effective for the configuration, setting operation, and coordination of relays for fast detection and communication through the GOOSE protocol.

A New Approach to Current Transformer Saturation Compensation for Transmission Line Differential Protection

A non-linear autoregressive network with external inputs (NARX) model to reconstruct the current transformer (CT) secondary waveform distortion in the presence of protected transmission lines is presented. The qualitative analysis carried out on the autonomous model reveals the accurate performance of the current differential relay, because of the ability of the NARX to make accurate predictions and signal reconstruction even when faced with noisy or incomplete datasets. The suggested method uses samples of the line-protected remote current signal to produce a desired waveform. The unsaturated section is artificially expanded because it can estimate up to one sample after saturation with a respectable level of accuracy. The proposed method is evaluated by MATLAB and PSCAD software. The effectiveness of the suggested method for different fault types under varied situations has been proved. The simulation outcome confirms the method’s high accuracy concerning the unusual system conditions in the presence of CT saturation.

Optimal relay performance using advanced fault diagnostic techniques

This paper describes application of Artificial Intelligence (AI) methods in the diagnostic operation of the protective relays in power system with a particular emphasis on neuro-fuzzy method, as a viable enhancement to the existing classical protection technique in use on the Nigeria’s national grid. The proposed method is simulated to showcase its advantages over the existing methods. It will not replace the latter but rather serves as a means of improving its reliability as a protection scheme. This work can also be applied to any other complex power system spread over a wide geographical area like Nigeria’s.

Effective protection scheme for transmission lines connected to large scale photovoltaic power plants

The performance of a distance relay can be significantly affected by various uncontrolled factors such as fault resistance, fault type, fault location and noise. Moreover, when photovoltaic power plants are integrated into electrical grids, they exhibit distinct fault current characteristics compared to conventional power systems with synchronous generators. These factors introduce variations in the recorded apparent impedance, deviating from the predefined settings of the distance relay. This paper presents an effective scheme for fault detection using ITD methodology. The ITD method decomposes the target signal into proper rotation and monotonic signals, which are then used to calculate the Energy Index. The performance of this scheme has been extensively investigated under various scenarios, including fault resistance, fault location, fault type, CT saturation, GC compliance, noise, and sampling frequency. To validate the effectiveness of the proposed scheme, simulations are conducted using both the PSCAD/EMTDC and MATLAB software. The proposed scheme is assessed using both the 2-bus and IEEE 39-bus test systems. The results show the merit and effectiveness of the proposed scheme in the accurate diagnosis of fault detection with 400 Ω fault resistance, in the presence of 20 dB noise, with variable sampling frequency (0.5-16 kHz) and variable irradiance values (600-1000(W/m2)) in power systems.

On the Performance of Multi-Way Massive MIMO Relay With Linear Processing

On the Performance of Multi-Way Massive MIMO Relay With Linear Processing

Outage Performance of Multiple Hybrid Active Relays and RISs-Assisted NOMA Networks

Outage Performance of Multiple Hybrid Active Relays and RISs-Assisted NOMA Networks

Statistical Design of Experiments for Power System Protection Testing: A Case Study for Distance Relay Performance Testing

Statistical Design of Experiments for Power System Protection Testing: A Case Study for Distance Relay Performance Testing

Flying Trap (Fly-T): An Automatic Termite Trapping Based on IoT and Hybrid Energy System using NodeMCU

This paper proposes an automated productive caste termite trap device based on a hybrid energy system and the Internet of Things called Flying Trap (Fly-T). This tool is equipped with ultraviolet light with a frequency of 365 nm which is used to attract termites to enter and trap into Fly-T storage tank until they die. Dead termites will be detected by an ultrasonic sensor with a certain limit value then the relay cuts off electric current so that the light turns off and the tank door automatically opens to expel dead termites. The automatic control system on Fly-T is built using the NodeMCU ESP32 microcontroller to optimize the performance of sensors, relays, servo, and wifi connections in recording data to an IoT-based cloud database. The Fly-T is also controlled by command via a Telegram Bot equipped with solar panels and a windmill turbine generator. The results show that Fly-T can run automatically, easily, and save time efficiently, and is environmentally friendly.

On the block error rate performance of cooperative non‐orthogonal multiple access short‐packet communications with full‐duplex relay and partial relay selection

AbstractIn this paper, we mathematically investigate a downlink non‐orthogonal multiple access (NOMA) system for short‐packet communications (SPC) in which the near users are used as full‐duplex (FD) relays to forward intended signals from the source to a far user. In addition, partial relay selection is employed to enhance the performance of the FD relays under the impact of imperfect interference cancellation. At the far user, selection combining (SC) or maximal ratio combining (MRC) is employed to combine the signals received from the source and the selected FD relay. The analytical expressions for the average block error rate (BLER) of two users over flat Rayleigh fading channels are derived. Furthermore, closed‐form asymptotic expressions of the average BLERs at the near and far users in high signal‐to‐noise ratio (SNR) regimes are obtained. The numerical results show that the analytical BLERs of the near user and far user closely match the simulation results.

Heuristic Path Search and Multi-Attribute Decision-Making-Based Routing Method for Vehicular Safety Messages

Efficient routing in urban vehicular networks is essential for timely and reliable safety message transmission, and the selection of paths and relays greatly affects the quality of routing. However, existing routing methods usually face difficulty in finding the globally optimal transmission path due to their greedy search strategies or the lack of effective ways to accurately evaluate relay performance in intricate traffic scenarios. Therefore, we present a vehicular safety message routing method based on heuristic path search and multi-attribute decision-making (HMDR). Initially, HMDR utilizes a heuristic path search, focusing on road section connectivity, to pinpoint the most favorable routing path. Subsequently, it employs a multi-attribute decision-making (MADM) technique to evaluate candidate relay performance. The subjective and objective weights of the candidate relays are determined using ordinal relationship analysis and the Criteria Importance Through Intercriteria Correlation (CRITIC) weighting methods, respectively. Finally, the comprehensive utility values of the candidate relays are calculated in combination with the link time and the optimal relay is selected. In summary, the proposed HMDR method is capable of selecting the globally optimal transmission path, and it comprehensively considers multiple metrics and their relationships when evaluating relays, which is conducive to finding the optimal relay. The experimental results show that even if the path length is long, the proposed HMDR method gives preference to the path with better connectivity, resulting in a shorter total transmission delay for safety messages; in addition, HMDR demonstrates faster propagation speed than the other evaluated methods while ensuring better one-hop distance and one-hop delay. Therefore, it helps to improve the performance of vehicular safety message transmission in intricate traffic scenarios, thus providing timely data support for secure driving.

Remanent flux detection method for a protection current transformer based on fluxgate theory

Protection current transformer (CT) saturation caused by the remanent flux will affect the performance of protective relays. The saturation can be suppressed by demagnetizing the iron core. Detecting remanent flux can make demagnetization more effective. This paper proposes a remanent flux detection method based on the fluxgate theory, which can effectively measure the magnitude and polarity of the remanent flux using the second harmonic of the current generated by a single-phase electronic inverter. The proposed method can detect the remanent flux without changing it, no matter whether the CT is connected to the power system or not, which means that this method can measure the remanent flux when the CT is under normal operating conditions. The effectiveness of this method is verified in EMTP-RV software, and the simulation results show that this method can detect the remanent flux with high accuracy.

A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

The increasing penetration of distributed generation (DG) to power distribution networks mainly induces weaknesses in the sensitivity and selectivity of protection systems. In this manner, conventional protection systems often fail to protect active distribution networks (ADN) in the case of short-circuit faults. To overcome these challenges, the accurate detection of faults in a reasonable fraction of time appears as a critical issue in distribution networks. Machine learning techniques are capable of generating efficient analytical expressions that can be strong candidates in terms of reliable and robust fault detection for several operating scenarios of ADNs. This paper proposes a deep group method of data handling (GMDH) neural network based on a non-pilot protection method for the protection of an ADN. The developed method is independent of the DG capacity and achieves accurate fault detection under load variations, disturbances, and different high-impedance faults (HIFs). To verify the improvements, a test system based on a real distribution network that includes three generators with a capacity of 6 MW is utilized. The extensive simulations of the power network are performed using DIgSILENT Power Factory and MATLAB software. The obtained results reveal that a mean absolute percentage error (MAPE) of 3.51% for the GMDH-network-based protection system is accomplished thanks to formulation via optimized algorithms, without requiring the utilization of any feature selection techniques. The proposed method has a high-speed operation of around 20 ms for the detection of faults, while the conventional OC relay performance is in the blinding mode in the worst situations for faults with HIFs.

An enhanced sensitive power differential protection for series compensated transmission lines in renewable generation intensive power systems

Series compensation is widely used to improve the electrical characteristics of long transmission lines and increase the power transfer capability. However, the insertion of a series capacitor introduces various phenomena that affect the performance of traditional distance relays. Moreover, the fault characteristics of renewable generation systems coupled with generation outputs that vary with weather patterns produce additional complications to the protection of transmission lines. This paper proposes the application of an enhanced sensitive power differential protection (SPDP) algorithm to the protection of series compensated transmission lines. The algorithm incorporates a criterion that improves the security of the protection by inhibiting the SPDP algorithm from operating for faults external to the protected line. Performance of the enhanced SPDP algorithm has been evaluated on a test system built in Digsilent Powerfactory software. Various in-zone and out-of-zone fault cases were simulated at different compensation levels and fault resistances. The results showed that the enhanced SPDP protection technique can detect in-zone faults along practically the entire transmission line (99.99 %) for compensation levels up to 90 %. The method operated reliably for faults with resistances up to 330 Ω.