Coordination Of Directional Overcurrent Relays Research Articles

Distance optimization and directional overcurrent relay coordination using edge-powered biogeography-genetic algorithms

The effective functioning and regulation of power systems crucially rely on the coordination of distance and directional overcurrent relays. Accurate fault detection and successful clearing sequences require support for each relay and the maintenance of the coordination time interval (CTI) between major distance relays, directional overcurrent relay support, and other relay zones. Efficiently initiating relays while adhering to complex coordination limitations poses a challenging task that demands innovative solutions. This study addresses the intricate problem of relay coordination by employing heuristic methods, specifically genetic algorithms (GA) and biogeography-based optimization (BBO), in both a 9-bus and 39-bus system. The primary objective is to determine the most efficient time setting factor (TSM) that minimizes the duration of relay operation. Additionally, the intelligent features of the overcurrent relay are carefully chosen to enhance the research's results. The integration of edge computing capabilities plays a significant role in advancing this coordination method. By incorporating advanced algorithms and communication technologies at the edge, the prompt activation of relays becomes possible, thereby meeting coordination demands. This study explores the combination of edge-based servers with genetic algorithms (GA) and biogeography-based optimization (BBO) techniques to enhance relay coordination. The findings indicate a notable enhancement compared to conventional approaches. However, comparative research suggests that BBO's performance is similar to GA, without a distinct advantage in achieving higher outcomes.

Optimizing directional overcurrent relay coordination with jellyfish search algorithm

Optimizing directional overcurrent relay coordination with jellyfish search algorithm

Optimizing DOCRs coordination when synergizing energy management with V2G using innovative optimization algorithms

This manuscript proposes an optimal coordination approach for directional overcurrent relays (DOCRs) within electric vehicle charging stations (EVCS), considering energy management and Vehicle-to-Grid (V2G) integration. The study focuses on maximizing efficiency and grid interaction in charging stations by addressing the challenge of DOCRs coordination. Three innovative optimization algorithms, namely the Hunger Games Search (HGS), Hunter Prey Optimization (HPO), and Sparrow Search algorithm (SSA), are employed to determine the optimal coordination for the DOCRs and get the time dial setting (TDS) and pickup current (IP) targeting minimum operating time for all DOCRs, considering factors such as load balancing, fault detection, and power quality in three different scenarios. EVSC has two types of charges DC and AC with two modes: V2G mode when EV is discharged into the grid, and G2V mode when EV is charged from the grid. Fast chargers are used to proceed as it can work in two modes V2G and G2V. Through extensive simulations and performance evaluations, the results demonstrate the effectiveness of the proposed approach. The three scenarios are simulated by using ETAP and MATLAB software according to fault location and to achieve voltage regulation and sufficient power for loads to achieved continuity of service for up to 1960.7 kW loads that kept fed. The proposed approach achieved the target of protecting the EVCS in minimum operating time of relays using the three algorithms and SSA introduces the best result more than other algorithms for the relay operating time with reduction up to 21 %.

A Novel Application of Fractional Order Derivative Moth Flame Optimization Algorithm for Solving the Problem of Optimal Coordination of Directional Overcurrent Relays

The proper coordination of directional overcurrent relays (DOCRs) is crucial in electrical power systems. The coordination of DOCRs in a multi-loop power system is expressed as an optimization problem. The aim of this study focuses on improving the protection system’s performance by minimizing the total operating time of DOCRs via effective coordination with main and backup DOCRs while keeping the coordination constraints within allowable limits. The coordination problem of DOCRs is solved by developing a new application strategy called Fractional Order Derivative Moth Flame Optimizer (FODMFO). This approach involves incorporating the ideas of fractional calculus (FC) into the mathematical model of the conventional moth flame algorithm to improve the characteristics of the optimizer. The FODMFO approach is then tested on the coordination problem of DOCRs in standard power systems, specifically the IEEE 3, 8, and 15 bus systems as well as in 11 benchmark functions including uni- and multimodal functions. The results obtained from the proposed method, as well as its comparison with other recently developed algorithms, demonstrate that the combination of FOD and MFO improves the overall efficiency of the optimizer by utilizing the individual strengths of these tools and identifying the globally optimal solution and minimize the total operating time of DOCRs up to an optimal value. The reliability, strength, and dependability of FODMFO are supported by a thorough statistics study using the box-plot, histograms, empirical cumulative distribution function demonstrations, and the minimal fitness evolution seen in each distinct simulation. Based on these data, it is evident that FODMFO outperforms other modern nature-inspired and conventional algorithms.

Coordination of Directional Overcurrent Relays using Growth Optimizer

The protection system plays a crucial role in the generation, transmission, and distribution systems of a power network. Among various protection relay types, Directional Overcurrent Relays (DOCRs) are the most used. When abnormal conditions are detected, these relays trigger the tripping of protection devices by detecting the direction and magnitude of current flow and isolating faulty parts of the system. The present article proposes a novel approach for the coordination and settings of DOCRs using the Growth Optimizer (GO) algorithm; the main objective is to minimize the sum of operation time of the relays while ensuring the minimal time gap between primary and backup relays. This optimization problem is subject to different constraints including maximum allowable operating times, relay coordination margins, and discrete values for pickup current settings. The technique is applied to the IEEE 4-bus, 8-bus, and 15-bus test systems, and its performance is compared with that of other optimization algorithms. Results show that the proposed approach provides the proper coordination of protection systems with a high, robust, and computationally acceptable speed of convergence.

An adaptive protection coordination for microgrids utilizing an improved optimization technique for user-defined DOCRs characteristics with different groups of settings considering N-1 contingency

Due to the increased integration of distributed generation (DG) in electric power systems, optimal coordination of overcurrent relays has become a key problem in power distribution systems. However, there is a lack of expertise in the creation of optimum microgrid coordination that takes into account all N-1 scenarios through the nonstandard relay characteristics. This work presents a novel technique for optimal coordination of directional overcurrent relays (DOCRs) in terms of relay curve settings (A and B), time dial setting (TDS) and plug setting (PS) to achieve the shortest running time and attain optimal settings. The optimization is carried out using a modified version of the Hanger Games Search algorithm (MHGS). The performance of the proposed method is assessed using the 14 bus distribution system while considering all the N-1 contingencies. DIgSILENT software was utilized to perform the required power system analysis, such as power flow and short circuit analysis. The MHGS method is used to determine the best settings for the DOCRs problem. The results are compared to the traditional HGS as well as those obtained by other current optimization approaches provided in the literature in order to demonstrate the effectiveness and superiority of the proposed MHGS in lowering relay operation time for optimum DOCRs coordination.

Particle Swarm Optimization for Directional Overcurrent Relay Coordination with Distributed Generation

The Directional Overcurrent Relays (DOCRs) Coordination with Distributed Generation (DG) optimization problem is addressed in this study using the optimization method Particle Swarm Optimization (PSO). Changes in fault current, bus voltages, power flow, and reliability may result from DG integration. Thus, it might have an impact on the current protection coordination system. The formulation is built on a Mixed Integer Non-Linear Programming (MINLP) problem to address this DOCR issue. MATLAB was used to validate the technique on the IEEE-14 bus system, and Electrical Test Transient Analyzer Programming (ETAP) version 2021 software was used to model the test system. According to the simulation results, the suggested PSO with DG for Case 2 has reduced power loss by 6.24% and relay operating time by 46.79% when compared to PSO without the presence of DG.

Optimization Techniques for Directional Overcurrent Relay Coordination: A Comprehensive Review

Optimization Techniques for Directional Overcurrent Relay Coordination: A Comprehensive Review

An adaptive protection method with directional overcurrent relay coordination using hybrid chaotic artificial humming bird optimization

An adaptive protection method with directional overcurrent relay coordination using hybrid chaotic artificial humming bird optimization

Improving Directional Overcurrent Relay Coordination in Distribution Networks for Optimal Operation Using Hybrid Genetic Algorithm with Sequential Quadratic Programming

In recent years, with the growing popularity of smart microgrids in distribution networks, the effective coordination of directional overcurrent relays (DOCRs) has presented a significant challenge for power system operators due to the intricate and nonlinear nature of their optimization model. Hence, this study proposes a hybrid GA-SQP algorithm to enhance the coordination of directional overcurrent relays (DOCRs) in radial and non-radial interconnected distributed power networks. The proposed approach combines the advantages of both the genetic algorithm (GA) and sequential quadratic programming (SQP) methods to optimize the objective function of relay coordination in the best manner. Thus, the proposed hybrid techniques improved the convergence of the problem and increased the likelihood of obtaining a globally optimal solution. Finally, to validate the effectiveness of the proposed algorithm, it was tested through three case studies involving the IEEE 3-Bus, 8-Bus, and modified 30-Bus distribution networks. In addition, the results were compared to those obtained using previous methods. The results obtained from the comparison of the proposed method and recent advanced research indicate that the proposed optimization approach is preeminent in terms of accuracy and total operating time as well as the continuity of the minimum margin time requirements between the primary/backup relay pairs.

An Investigation of the Impact of Distributed Generation Penetration on Directional Overcurrent Relay Coordination in a Distribution Network

Distributed generation units (DGs) are rapidly becoming widespread in distribution systems due to their advantages such as power loss reduction, voltage profile improvement, and economic returns. Many researchers seek new ways to maximize their these advantages. However, their impact on the fault current is a problem for the field of power system protection. The changes in the short-circuit currents due to DGs cause the miscoordination of the directional overcurrent relays (DOCRs). In this paper, the impact of distribution generation penetration on DOCR coordination is analyzed and investigated. Besides this negative impact of DGs, their contributions to reducing power loss and improving the voltage profile are also analyzed for different DG penetration levels. The gazelle optimization algorithm is utilized to solve the DOCR coordination problem studied in this paper. The method is performed on the distribution section of the IEEE 14-bus system. It is seen that a significant number of miscoordinations occur when even the DG penetration is increased by about 10%. With the increase in DG penetration, the number of miscoordinations does not increase proportionally, but there is a proportional increase in active and reactive power loss reduction and voltage profile improvement.

Optimal coordination of directional overcurrent relays in complex networks using the Elite marine predators algorithm

The integration of renewable energy sources in the distribution network (DN) has had a significant influence by reducing power loss and enhancing network dependability. Aside from that, the protection system has met coordination issues as a result of bidirectional power flow and variations in fault levels. Therefore, an optimal coordination strategy is required to deal with relays coordination problem. The coordination problem of the directional overcurrent relays (DOCRs) is a restricted optimization issue that involves determining appropriate time dial settings (TDS) and plug setting (PS) to reduce relays operating time. Currently, a various nontraditional optimization strategies have been presented to overcome this challenge. In this paper, a modified version of the marine predators algorithm (MPA) referred to as Elite marine predator (EMPA) is developed for the optimal coordination of DOCRs. Therefore, the EMPA method is used to find out the optimal settings for the DOCRs problem. The suggested algorithm's performance is evaluated using standard test systems, including 3-bus, 8-bus, 9-bus, and 15-bus. The findings are compared with the traditional MPA and with other recent optimization methods presented in the literature to prove the efficiency and superiority of the proposed EMPA in reducing relay operation time for optimal DOCRs coordination.

Adaptive Directional Overcurrent Relay Coordination in Microgrid Considering Optimal Full Setting Parameters

This article proposes a novel approach for the optimal coordination of adaptive directional overcurrent relay (ADOCR) for modernized active distribution system (ADS) with microgrid (MG) functions. The goal is to keep the coordinating circumstances while reducing the protective relay operation time, as much as possible. With the proposed round-off mixed-integer particle swarm optimization (ROMI-PSO), the setting parameters are not limited to only relay time multiplier setting (TMS) and pickup current setting (PS) but can include the discrete parameter as relay characteristic curve setting (CS). In the proposed framework, The CS can be both IEC and IEEE standard curves in the proposed framework. Four buses radial system and IEC-benchmark MG system were used in a number of simulation experiments. Comparing the suggested methodology to other current methods revealed that it is more effective at determining the minimum relay operating times and ensuring the proper operation of protections under various fault allocations and operating circumstances.

Optimal Coordination of Directional Overcurrent Relays Using Hybrid Firefly–Genetic Algorithm

The application of directional overcurrent relays (DOCRs) plays an important role in protecting power systems and ensuring their safe, reliable, and efficient operation. However, coordinating DOCRs involves solving a highly constrained and nonlinear optimization problem. The primary objective of optimization is to minimize the total operating time of DOCRs by determining the optimal values for decision variables such as the time multiplier setting (TMS) and plug setting (PS). This article presents an efficient hybrid optimization algorithm that combines the modified firefly algorithm and genetic algorithm to achieve improved solutions. First, this study modifies the firefly algorithm to obtain a global solution by updating the firefly’s brightness and to prevent the distance between the individual fireflies from being too far. Additionally, the randomized movements are controlled to produce a high convergence rate. Second, the optimization problem is solved using the genetic algorithm. Finally, the solution obtained from the modified firefly algorithm is used as the initial population for the genetic algorithm. The proposed algorithms have been tested on the IEEE 3-bus, 8-bus, 9-bus and 15-bus networks. The results indicate the effectiveness and superiority of the proposed algorithms in minimizing the total operating time of DOCRs compared with other optimization methods presented in the literature.

Optimizing TOC and IOC units of directional overcurrent relays in mutually coupled circuits using evolutionary PSO: Requirements and modeling

The efficient coordination of directional overcurrent relays is a challenging problem. Recent papers in the literature have focused on developing efficient algorithms to solve this issue. However, there is a lack of reporting practical procedures that affects the mathematical formulation to ensure accurate outputs by any optimization algorithm. In this paper, we show a comprehensive procedure that considers mutually coupled circuits via Graph Theory, the requirements of short-circuit current calculation, contingencies to be considered as well as the setting of Instantaneous Overcurrent (IOC) and Time Overcurrent (TOC) units, both for phase and ground protection. The simulation has been carried out by using a real electric network and C++ language programming. Computational simulation has shown the performance of the method, which provides high-quality solutions, with adequate coordination of the selected protective devices that increase the efficiency in setting this type of protection with safety. Evolutionary Particle Swarm Optimization (EPSO) outperformed conventional Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) as the best metaheuristic for optimally minimizing the proposed problem, achieving faster convergence times for the phase overcurrent protection scenario (16.36 s vs. 22.27 s and 17.03 s, respectively), and also for the ground overcurrent protection scenario (19.87 s vs. 20.44 s and 20.11 s, respectively).

Artificial intelligence based optimal coordination of directional overcurrent relay in distribution systems considering vehicle to grid technology

Optimal coordination of overcurrent relays has become a major challenge in power distribution systems due to the increasing participation of distributed generation (DG) and electric vehicle (EV) charging stations, especially vehicle-to-grid (V2G) technology. This paper proposes a novel approach for optimal coordination of directional overcurrent relays (DOCRs) to achieve the minimum operating time and obtain optimal tuning in terms of time dial setting (TDS) and pick-up current (IP) considering V2G integration. The optimization was conducted using three different Artificial Intelligence (AI) techniques: grey wolf optimization (GWO), cuckoo search (CS), and Hunger Games Search (HGS), and was performed on two systems: IEEE 33-bus system and a local grid located in El-Shorouk City–district#8 (ShC-D8), Cairo, Egypt. The proposed methodology is constructed and validated on ETAP and MATLAB software packages. The simulation results demonstrate that the proposed optimization techniques provide high dynamic performance and accurate coordination of DOCRs. The results show that HGS achieves the minimum operating time of all overcurrent relays as compared with GWO and CS. The effect of V2G integration on the coordination methodology is also considered. The proposed approach provides a significant contribution to the field of power system protection and can help improve the reliability and efficiency of power distribution systems with V2G integration.

Optimizers for optimal coordination of distance relays and non-standard characteristics of directional overcurrent relays

In this paper, different methods are utilized to solve the coordination issue involving directional overcurrent relays (DOCRs) and distance relays. The proper coordination of DOCRs and distance relays is a critical issue for system security in electrical networks. Finding the DOCRs setting, pickup current(Ip) and timed dial setting (TDS), and operating time for zone-2 of distance relays is the primary objective of solving the coordination problem. The constant parameters A & B of the directional overcurrent relay that are responsible to control the form of the relay´s characteristics as well as the Ip and TDS have been regarded as variables in this problem. The optimal value for these four DOCR settings has been determined using different optimization techniques. The primary and backup relays must operate sequentially and without any violations, and this must be guaranteed by optimization techniques. In order to determine the operation time for zone-2 and DOCRs setting, optimization methods are examined utilizing the 8-bus and IEEE 30-bus networks. Different optimization algorithms, including recent and traditional techniques, are compared. The obtained results show the superiority of the genetic algorithm (GA) in solving the coordination problem of distance relays and DOCRs. Also, the obtained results prove the ability of the GA method compared to the particle swarm algorithm (PSO), grey wolf optimization (GWO), water cycle technique (WCA), equilibrium optimizer (EO), African vultures optimization algorithm (AVOA), flow direction algorithm (FDA), and gorilla troops optimizer (GTO) techniques.

Optimizing Firefly Algorithm for Directional Overcurrent Relay Coordination: A case study on the Impact of Parameter Settings

Optimizing Firefly Algorithm for Directional Overcurrent Relay Coordination: A case study on the Impact of Parameter Settings

Adaptive coordination of directional overcurrent relays for meshed distribution networks with distributed generations using dragonfly algorithm

Adaptive coordination of directional overcurrent relays for meshed distribution networks with distributed generations using dragonfly algorithm

Protection coordination of DOCRs for different modes of microgrid operation

The present study is focussed on solving the relay coordination problem. Protection of microgrids is performed through the placement of directional overcurrent relays (DOCR). The efficacy of microgrid protection depends on coordination of all the DOCRs placed in the system. For this purpose, a number of optimization techniques have been employed by the power system researcher. In this paper, Grey Wolf Optimizer (GWO) is proposed for the protection coordination of DOCRs for different modes of microgrid operation. The proposed method is tested and validated on a 7-bus mesh system and a 9-bus radial test system. The proposed method has been compared with other meta-heuristic optimization approaches, namely Genetic Algorithm (GA), Artificial Bee Colony (ABC), Gravitational Search Algorithm (GSA), and Hybrid Particle Swarm Optimization Gravitational Search Algorithm (PSOGSA). Based on the obtained results, the GWO-based approach is very efficient in mitigating the problem of relay coordination as compared to other optimization techniques.