Optimal protective relaying scheme of distributed generation connected distribution network using particle swarm optimization-gravitational search algorithm technique

This paper develops particle swarm optimization integrated with gravitational search algorithm (PSO-GSA) to coordinate the relays in a distribution system with distributed generation (DG) connectivity. This algorithm combines PSO and GSA to improve the performance of the relay protection system. To prevent relay malfunctions following DG penetration, a suitable primary and backup relay is chosen. The PSO-GSA is coded using MATLAB software and tested on an IEEE 4-bus system simulated in Simulink. Results indicate that, when compared to using regular PSO and GSA procedures individually, the PSO-GSA technique reduces the operating time of the relay significantly

Optimal coordination of directional overcurrent relays using PSO-TVAC considering series compensation

The integration of system compensation such as Series Compensator (SC) into the transmission line makes the coordination of directional overcurrent in a practical power system important and complex. This article presents an efficient variant of Particle Swarm Optimization (PSO) algorithm based on Time-Varying Acceleration Coefficients (PSO-TVAC) for optimal coordination of directional overcurrent relays (DOCRs) considering the integration of series compensation. Simulation results are compared to other methods to confirm the efficiency of the proposed variant PSO in solving the optimal coordination of directional overcurrent relay in the presence of series compensation

Distribution system reliability enhancement

Practically all everyday life tasks from economic transactions to entertainment depend on the availability of electricity. Some customers have come to expect a higher level of power quality and availability from their electric utility. Federal and state standards are now mandated for power service quality and utilities may be penalized if the number of interruptions exceeds the mandated standards. In order to meet the requirement for safety, reliability and quality of supply in distribution system, adaptive relaying and optimal network reconfiguration are proposed. By optimizing the system to be better prepared to handle a fault, the end result will be that in the event of a fault, the minimum number of customers will be affected. Thus reliability will increase. The main function of power system protection is to detect and remove the faulted parts as fast and as selectively as possible. The problem of coordinating protective relays in electric power systems consists of selecting suitable settings such that their fundamental protective function is met under the requirements of sensitivity, selectivity, reliability, and speed. In the proposed adaptive relaying approach, weather data will be incorporated as follows. By using real-time weather information, the potential area that might be affected by the severe weather will be determined. An algorithm is proposed for adaptive optimal relay setting (relays will optimally react to a potential fault). Different types of relays (and relay functions) and fuses will be considered in this optimization problem as well as their coordination with others. The proposed optimization method is based on mixed integer programming that will provide the optimal relay settings including pickup current, time dial setting, and different relay functions and so on. The main function of optimal network reconfiguration is to maximize the power supply using existing breakers and switches in the system. The ability to quickly and flexibly reconfigure the power system of an interconnected network of feeders is a key component of Smart Grid. New technologies are being injected into the distribution systems such as advanced metering, distribution automation, distribution generation and distributed storage. With these new technologies, the optimal network reconfiguration becomes more complicated. The proposed algorithms will be implemented and demonstrated on a realistic test system. The end result will be improved reliability. The improvements will be quantified with reliability indexes such as SAIDI.M.S.Committee Chair: A.P. Meliopoulos; Committee Member: Carlos S Grijalva; Committee Member: Deepakraj M Diva

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)

Overcurrent relays coordination optimisation methods in distribution systems for microgrids: a review

Electric power networks connected with multiple distributed generations (microgrids) require adequate protection coordination. In this paper, the overcurrent relay coordination concept in distribution system has been presented with details. In this available literature, the previous works on optimisation methods utilised for the coordination of over current relays; classification has been made based on the optimisation techniques, non-standard characteristics, new constraints that have been proposed for optimal coordination and dual setting protection schemes. Then a comprehensive review has been done on optimisation techniques including the conventional methods, heuristic and hybrid methods and the relevant issues have been addressed

Optimal relay coordination of an adaptive protection scheme using modified PSO algorithm.

Recently, future smart grids are described by a dominantly fluctuating character due to the power consumption change from peak to off-peak loading conditions, the operation of micro-grids in grid-connected or islanded mode and other possible network topologies resulting in an effective change in network impedances and short circuit current level. Therefore, the situation from protection sensitivity, selectivity and speed may become more and more challenging. In this paper, Adaptive protection scheme is proposed to respond to structural variations occurred in interconnected power systems. A designed software based on Modified Particle Swarm Optimization (MPSO) algorithm is suggested to solve the relay coordination problem in modern distribution networks. In this study, the 14 IEEE bus system is tested via three power system scenarios showing the effect of adding and disconnecting of DG units and the occurrence of sudden line outages on the system. The obtained results show that the proposed algorithm has achieved optimum relay settings for each existing network topology

INTELLIGENT METHODS FOR OPTIMUM ONLINE ADAPTIVE COORDINATION OF OVERCURRENT RELAYS

During the operation in a modern power distribution system, some abnormal events may happen, such as over-voltage, faults, under-frequency and overloading, and so on. These abnormal events may cause a power outage in a distribution system or damages on the equipment in a distribution system. Hence these abnormal events should be identified and isolated by protection systems as quickly as possible to make sure we can maintain a stable and reliable distribution system to supply adequate electric power to the largest number of consumers as we can. To sum up, we need stable and reliable protection systems to satisfy this requirement. Chapter 1 of the dissertation is a brief introduction to my research contents. Firstly, the background of a distribution system and the protection systems in a power system will be introduced in the first subchapter. Then there will be a review of existing methods of optimum coordination of overcurrent relays using different optimal techniques. The dissertation outline will be illustrated in the end. Chapter 2 of the dissertation describes a novel method of optimum online adaptive coordination of overcurrent relays using the genetic algorithm. In this chapter, the basic idea of the proposed methods will be explained in the first subchapter. It includes the genetic algorithm concepts and details about how it works as an optimal technique. Then three different types of simulation systems will be used in this part. The first one is a basic distribution system without distributed generations (DGs); the second one is similar to the first one but with load variations; the last simulation system is similar to the first one but with a distributed generation in it. Using three different simulation systems will demonstrate that the coordination of overcurrent relays is influenced by different operating conditions of the distribution system. In Chapter 3, a larger sized distribution system with more distributed generations and loads will be simulated and used for verifying the proposed method in a more realistic environment. In addition, the effects of fault location on the optimum coordination of overcurrent relays will be discussed here. In Chapter 4, the optimal differential evolution (DE) technique will be introduced. Because of the requirement of the online adaptive function, the optimal process needs to be accomplished as soon as possible. Through the comparison between genetic algorithm and differential evolution on the optimum coordination of overcurrent relays, we found that differential evolution is much faster than the genetic algorithm, especially when the size of the distribution system grows. Therefore, the differential evolution optimal technique is more suited than the genetic algorithm to realize online adaptive function. Chapter 5 presents the conclusion of the research work that has been done in this dissertation

Particle Swarm Optimization Solution for Power System Operation Problems

Application of particle swarm optimization (PSO) algorithm on power system operation is studied in this chapter. Relay protection coordination in distribution networks and economic dispatch of generators in the grid are defined as two of power system-related optimization problems where they are solved using PSO. Two case study systems are conducted. The first case study system investigates applicability of PSO on providing proper overcurrent relay settings in the grid, while in the second case study system, the economic dispatch of a 15-unit system is solved where PSO successfully provides the optimum power output of generators with minimum fuel costs to satisfy the load demands and operation constraints. The simulation results in comparison with other methods show the effectiveness of PSO against other algorithms with higher quality of solution and less fuel costs on the same test system

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

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/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.Peer reviewe