Applying Hybrid PSO to Optimize Directional Overcurrent Relay Coordination in Variable Network Topologies

In power systems, determining the values of time dial setting (TDS) and the plug setting (PS) for directional overcurrent relays (DOCRs) is an extremely constrained optimization problem that has been previously described and solved as a nonlinear programming problem. Optimization coordination problems of near-end faults and far-end faults occurring simultaneously in circuits with various topologies, including fixed and variable network topologies, are considered in this study. The aim of this study was to apply the Nelder-Mead (NM) simplex search method and particle swarm optimization (PSO) to solve this optimization problem. The proposed NM-PSO method has the advantage of NM algorithm, with a quicker movement toward optimal solution, as well as the advantage of PSO algorithm in the ability to obtain globally optimal solution. Neither a conventional PSO nor the proposed NM-PSO method is capable of dealing with constrained optimization problems. Therefore, we use the gradient-based repair method embedded in a conventional PSO and the proposed NM-PSO. This study used an IEEE 8-bus test system as a case study to compare the convergence performance of the proposed NM-PSO method and a conventional PSO approach. The results demonstrate that a robust and optimal solution can be obtained efficiently by implementing the proposal

Optimal overcurrent relay coordination in wind farm using genetic algorithm

Wind farms are ones of the most indispensable types of sustainable energies which are progressively engaged in smart grids with tenacity of electrical power generation predominantly as a distribution generation system. Thus, rigorous protection of wind power plants is an immensely momentous aspect in electrical power protection engineering which must be contemplated thoroughly during designing the wind plants to afford a proper protection for power components in case of fault occurrence. The most commodious protection apparatus are overcurrent relays (OCRs) which are responsible for protecting power systems from impending faults. In order to employ a prosperous and proper protection for wind farms, these relays must be set precisely and well-coordinated with each other to clear the faults at the system in the shortest possible time. These relays are set and coordinated with each other by applying IEEE or IEC standards methods, however, their operation times are relatively long and the coordination between these relays are not optimal. The other common problem in these power systems is when a fault occurs in a plant, several OCRs operate instead of a designated relay to that particular fault location. This, if undesirable can result in unnecessary power loss and disconnection of healthy feeders out of the plant which is extremely dire. It is necessary to address the problems related inefficient coordination of OCRs. Many suggestions have been made and approaches implemented, however one of the most prominent methods is the use of Genetic Algorithm (GA) to improve the function and coordination of OCRs. GA optimization technique was implemented in this project due to its ample advantages over other AI techniques including proving high accuracy, fast response and most importantly obtaining optimal solutions for nonlinear characteristics of OCRs. In addressing the mentioned problems, the main objective of this research is to improve the protection of wind farms by optimizing the relay settings, reducing their operation time, Time Setting Multiplier (TSM) of each relay, improving the coordination between relays after implementation of IEC 60255-151:2009 standard. The most recent and successful OF for GA technique has been used, unique parameters for GA was selected for this research to significantly improve the protection for wind farms that is highly better compared to any research accomplished before for the purpose of wind farm protection. GA was used to obtain improved values for each relay settings based on their coordination criteria. Each relay operation time and TSM are optimized which would contribute to provide a better protection for wind farm. Thus, the objective of this work which is improving the protection of wind farms by optimizing the relay settings, reducing their operation time, Time Setting Multiplier (TSM) of each relay, improving the coordination between relays, have been successfully fulfilled and solved the problems associated with wind farm relay protection system settings. The new approach has shown significant improvement in operation of OCRs at the wind farm, have drastically reduced the accumulative operation time of the relays by 26.8735% (3.7623 seconds)

A review of networked microgrid protection: Architectures, challenges, solutions, and future trends

The design and selection of advanced protection schemes have become essential for the reliable and secure operation of networked microgrids. Various protection schemes that allow the correct operation of microgrids have been proposed for individual systems in different topologies and connections. Nevertheless, the protection schemes for networked microgrids are still in development, and further research is required to design and operate advanced protection in interconnected systems. The interconnection of these microgrids in different nodes with various interconnection technologies increases the fault occurrence and complicates the protection operation. This paper aims to point out the challenges in developing protection for networked microgrids, potential solutions, and research areas that need to be addressed for their development. First, this article presents a systematic analysis of the different microgrid clusters proposed since 2016, including several architectures of networked microgrids, operation modes, components, and utilization of renewable sources, which have not been widely explored in previous review papers. Second, the paper presents a discussion on the protection systems currently available for microgrid clusters, current challenges, and solutions that have been proposed for these systems. Finally, it discusses the trend of protection schemes in networked microgrids and presents some conclusions related to implementation

Computational Intelligence Application in Electrical Engineering

The Special Issue "Computational Intelligence Application in Electrical Engineering" deals with the application of computational intelligence techniques in various areas of electrical engineering. The topics of computational intelligence applications in smart power grid optimization, power distribution system protection, and electrical machine design and control optimization are presented in the Special Issue. The co-simulation approach to metaheuristic optimization methods and simulation tools for a power system analysis are also presented. The main computational intelligence techniques, evolutionary optimization, fuzzy inference system, and an artificial neural network are used in the research presented in the Special Issue. The articles published in this issue present the recent trends in computational intelligence applications in the areas of electrical engineering

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

This paper investigates the application of the Firefly Algorithm for solving the coordination problem in the IEEE 3-bus network. It analyzes the impact of key parameters, including the number of generations, population size, absorption coefficient (γ), and randomization parameter (α), on the algorithms performance. Through extensive experimentation, the study demonstrates the impact on solution quality, feasibility, computational requirements, and efficiency. Results indicate that increasing the number of generations improves solution quality, but benefits diminish beyond a certain point. Feasibility improves with higher generations, but a balance between solution quality and feasibility becomes apparent at very high generations. Objective function evaluations and computation time increase linearly with generations. Larger population sizes yield better solution quality and feasibility, but a balance is observed at very high population sizes. Objective function evaluations and computation time scale proportionally with population size. The randomization parameter has a modest influence on performance, with no significant changes observed. However, extreme values impact solution quality, feasibility, and computation time. The absorption coefficient significantly affects convergence and solution quality. Lower values expedite convergence but may lead to suboptimal solutions, while higher values enhance exploration at the cost of increased computational effort. This study provides a comprehensive understanding of parameter selection and optimization in the Firefly Algorithm for solving the coordination problem of the IEEE 3-bus network, offering valuable guidance for future research in enhancing performance through parameter refinement and adaptive techniques

Metodologías de optimización aplicadas a la coordinación óptima de protecciones de sobrecorriente

La coordinación de relés de protección en los sistemas eléctricos de potencia (SEP) es una de las tareas más importantes y dispendiosas, debido al impacto de una mala operación por descoordinación y a la cantidad de información que se debe procesar. En este artículo se presenta una revisión del estado del arte en la coordinación de relés de sobrecorriente. También se presentan algunas de las consideraciones a tener en cuenta para el empleo de protecciones adaptativas y varias de las metodologías que se han desarrollado desde la modelación matemática, hasta el uso de sistemas de inteligencia artificial para la coordinación de relés de sobrecorriente. Entre los métodos estudiados se encuentran: programación lineal, algoritmos evolutivos, algoritmos genéticos, optimización mediante colonia de partículas y algoritmos de colonias de abejas. Se presentan gráficos y tablas mostrando la evolución de las diferentes técnicas empleadas para abordar el problema de coordinación óptima de protecciones de sobrecorriente.Palabras clave: Coordinación de relés de sobrecorriente, Computación evolutiva, Inteligencia artificial.ABSTRACTCoordination of protection relays is one the most important and time consuming tasks in power systems due to the consequences that a lack of coordination might cause, and to the amount of information that must be processed. A review of the state of the art on overcurrent relay coordination is presented as well as some considerations to be taken into account in the use of adaptive protections and several methodologies that have been developed from the mathematical modeling to the use of artificial intelligence for the coordination of overcurrent relays. Among the discussed methods are: linear programming, evolutionary algorithms, genetic algorithms, particle swarm optimization and artificial bee colony algorithms. Several figures and tables are shown to depict the evolution of different techniques applied to the optimal overcurrent relay coordination problem.Keywords: Overcurrent relay coordination, Evolutionary computation, Artificial intelligence

Optimal adaptive protection of smart grids using high-set relays and smart selection of relay tripping characteristics considering different network configurations and operation modes

Much attention has been paid to optimizing smart grids (SGs) and microgrids (MGs) protection schemes. The SGs' operation in different operating modes (especially grid-connected and islanded conditions) and various system configurations (such as the outage of each of the distribution generations) adversely influence the protection system. The adaptive protection schemes using different setting groups are suitable and reliable solutions to achieve a fast protective system. However, the literature shows a research gap in developing optimized adaptive protection schemes, focusing on constraint reduction, besides the optimal selection of time-current characteristics for direction overcurrent relays (DOCRs) and high-set relays (HSRs). This research aims to fill such a research gap. The power system analyses, such as power flow and short circuit studies, are done in DIgSILENT, and the genetic algorithm (GA) is used to find the optimum solutions. Test results of the IEEE 38-bus distribution system illustrate the advantages of this study compared to existing ones. The comparative test results emphasize that 31.78% and 21.62% decrement in time of the protective scheme in different topologies for the distribution networks of the IEEE 38-bus and IEEE 14-bus test systems could be achievable by simultaneously optimizing relay characteristics and HSRs compared to existing approaches.Much attention has been paid to optimizing smart grids (SGs) and microgrids (MGs) protection schemes. The SGs' operation in different operating modes (especially grid-connected and islanded conditions) and various system configurations (such as the outage of each of the distribution generations) adversely influence the protection system. The adaptive protection schemes using different setting groups are suitable and reliable solutions to achieve a fast protective system. However, the literature shows a research gap in developing optimized adaptive protection schemes, focusing on constraint reduction, besides the optimal selection of time-current characteristics for direction overcurrent relays (DOCRs) and high-set relays (HSRs). This research aims to fill such a research gap. The power system analyses, such as power flow and short circuit studies, are done in DIgSILENT, and the genetic algorithm (GA) is used to find the optimum solutions. Test results of the IEEE 38-bus distribution system illustrate the advantages of this study compared to existing ones. The comparative test results emphasize that 31.78% and 21.62% decrement in time of the protective scheme in different topologies for the distribution networks of the IEEE 38-bus and IEEE 14-bus test systems could be achievable by simultaneously optimizing relay characteristics and HSRs compared to existing approaches

Highly sensitive multifunction protection coordination scheme for improved reliability of power systems with distributed generation (PVs)

The high penetration of distribution generators (DGs), such as photovoltaic (PV), has made optimal overcurrent coordination a major concern for power protection. In the literature, the conventional single or multi‐objective function (OF) for phase overcurrent relays (OCRs) scheme faces challenges in terms of stability, sensitivity, and selectivity to handle the integration of DGs and ground fault scenarios. In this work, a new optimal OCR coordination scheme has been developed as a multifunction scheme for phase and ground events using standard and non‐standard tripping characteristics. This research introduces and validates a coordinated optimum strategy based on two new optimization approaches, the Tug of War Optimization algorithm (TWO) and the Charged System Search algorithm (CSS), to mitigate the effects of DGs on fault currents and locations across the power network. Industrial software is used to create a case study of a CIGRE power network equipped with two 10 MW PV systems, and the results of the proposed new optimum coordination scheme are compared to traditional schemes. The findings show that the proposed multifunction OCR scheme is able to reduce the tripping time of OCRs over different fault and grid operation scenarios and increase the sensitivity of the relays in islanding operation mode

Application of evolutionary algorithms for optimal directional overcurrent relay coordination

Includes bibliographical references.Relay coordination is necessary to ensure that while protection relays operate as fast as possible, they are also able to isolate only the faulted parts of the system from the network, ensuring that a power system disturbance does not result in interruption of the power supply to a larger part of the power system network. Optimal relay coordination for overcurrent relays depends on two parameters, namely, Time Multiplier and Pickup Current Setting. The conventional method of setting these two parameters for overcurrent relays applied on the power system network is to first determine the main and backup relay pairs which form part of the clockwise and anti-clockwise loops around the power system network. The relays are then set through an iterative process to ensure coordination. Initially, a general rule of setting relays to operate in 0.2 seconds for faults in the primary zone, to ensure fast operation, and in 0.2 seconds plus additional grading time, to ensure coordination, for faults in the backup zone is applied. The next relay in the loop is tested to check if it fulfils the requirements of the initial general rule. If the conditions of the general rule are not met, the previous relay’s setting is adjusted to meet the requirements. This process is repeated until all the relays around the loop are set. Conventional relay coordination process has a limitation in the sense that it is deterministic and the settings of subsequent relays depend on the initial guess of the settings of the initial relay. Therefore, this method does not necessarily provide solutions which guarantee optimal relay coordination but the best of the solutions tried