Optimal protection coordination of voltage-current time based inverse relay for PV based distribution system

Distributed energy resources (DERs) are electricity source generator to meet small scale electricity requirement. DER is gaining much importance nowadays due to its high efficiency and zero emission. To meet the peak demand integrating more number of DERs at the distribution section directly without disturbing the transmission section thus avoiding the losses from generating station to distribution section. As the density of the network increases the overall operating time also increases. The fault current impact from the PV based DER is very small the relay will be in stationary mode. To improve the performance of these inactive relay near PV distribution system the author has proposed a new voltage-current time inverse relay characteristics, as the operating time is inversely proportional to the rise in current and fall in bus voltage. The protection coordination problem is solved by using differential evolution algorithm. The proposed method is tested for IEEE 14 bus distribution system. The obtained results are validated with standard time inverse relay to check the superiority of the proposed method. © 2017 IEEE

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)

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

Omega grey wolf optimizer (ωGWO) for optimization of overcurrent relays coordination with distributed generation

Inverse definite minimum time (IDMT) overcurrent relays (OCRs) are among protective devices installed in electrical power distribution networks. The devices are used to detect and isolate the faulty area from the system in order to maintain the reliability and availability of the electrical supply during contingency condition. The overall protection coordination is thus very complicated and could not be satisfied using the conventional method moreover for the modern distribution system. This thesis apply a meta-heuristic algorithm called Grey Wolf Optimizer (GWO) to minimize the overcurrent relays operating time while fulfilling the inequality constraints. GWO is inspired by the hunting behavior of the grey wolf which have firm social dominant hierarchy. Comparative studies have been performed in between GWO and the other well-known methods such as Differential Evolution (DE), Particle Swarm Optimizer (PSO) and Biogeographybased Optimizer (BBO), to demonstrate the efficiency of the GWO. The study is resumed with an improvement to the original GWO’s exploration formula named as Omega-GWO (ωGWO) to enhance the hunting ability. The ωGWO is then implemented to the realdistribution network with the distributed generation (DG) in order to investigate the drawbacks of the DG insertion towards the original overcurrent relays configuration setting. The GWO algorithm is tested to four different test cases which are IEEE 3 bus (consists of six OCRs), IEEE 8 bus (consists of 14 OCRs), 9 bus (consists of 24 OCRs) and IEEE 15 bus (consists of 42 OCRs) test systems with normal inverse (NI) characteristic curve for all test cases and very inverse (VI) curve for selected cases to test the flexibility of the GWO algorithm. The real-distribution network in Malaysia which originally without DG is chosen, to investigate and recommend the optimal DG placement that have least negative impact towards the original overcurrent coordination setting. The simulation results from this study has established that GWO is able to produce promising solutions by generating the lowest operating time among other reviewed algorithms. The superiority of the GWO algorithm is proven with relays’ operational time are reduced for about 0.09 seconds and 0.46 seconds as compared to DE and PSO respectively. In addition, the computational time of the GWO algorithm is faster than DE and PSO with the respective reduced time is 23 seconds and 37 seconds. In Moreover, the robustness of GWO algorithm is establish with low standard deviation of 1.7142 seconds as compared to BBO. The ωGWO has shown an improvement for about 55% and 19% compared to other improved and hybrid method of GA-NLP and PSO-LP respectively and 0.7% reduction in relays operating time compared to the original GWO. The investigation to the DG integration has disclosed that the scheme is robust and appropriate to be implemented for future system operational and topology revolutions

Optimal Overcurrent Relays Coordination using an Improved Grey Wolf Optimizer

Recently, nature inspired algorithms (NIA) have been implemented to various fields of optimization problems. In this paper, the implementation of NIA is reported to solve the overcurrent relay coordination problem. The purpose is to find the optimal value of the Time Multiplier Setting (TMS) and Plug Setting (PS) in order to minimize the primary relays’ operating time at the near end fault. The optimization is performed using the Improved Grey Wolf Optimization (IGWO) algorithm. Some modifications to the original GWO have been made to improve the candidate’s exploration ability. Comprehensive simulation studies have been performed to demonstrate the reliability and efficiency of the proposed modification technique compared to the conventional GWO and some well-known algorithms. The generated results have confirmed the proposed IGWO is able to optimize the objective function of the overcurrent relay coordination problem

Optimal Protection Coordination of Active Distribution Networks Powered by Synchronverters

The integration of distributed generators (DGs) into distribution networks leads to the emergence of active distribution networks (ADNs). These networks have advantages, such as deferring the network upgrade, lower power losses, reduced power generation cost, and lower greenhouse gas emission, DGs are classified due to their interface with the network as inverter-interfaced or synchronous-interfaced. However, DGs integration results in bidirectional power flow, higher fault current levels, deterioration of the protection coordination of the directional overcurrent relays (DOCRs) which are used in ADNs, reduced system stability due to the inverters’ lack of damping. The stability can be enhanced by controlling the inverters to behave as synchronous generators, which are known as synchronverters. In this thesis, a two-stage optimal protection coordination (OPC) scheme is proposed to guarantee reliable protection of ADNs while protecting synchronverters from overcurrent using virtual impedance fault current limiters (VI-FCLs). VI-FCLs provide a cost-effective way to protect synchronverters from overcurrent. The first stage integrates the fault current calculations of synchronverters in the fault analysis to find the parameters of VI-FCLs used to limit the synchronverter’s fault current. In the second stage, the fault current calculations, along with the designed VI-FCLs from the first stage, are employed to determine the optimal relays’ settings to minimize the total operating times for all the DOCR. It is found that fixed VI-FCLs can limit synchronverters’ fault currents but may make the OPC problem infeasible to solve. Thus, an adaptive VI-FCL is proposed to ensure a feasible OPC under various fault conditions, i.e., locations and resistances

Sistema automatizado para coordenação de ajustes de proteção de sobrecorrente direcional em sistemas malhados

Orientadora: Prof.ª. Dra. Thelma S. P. FernandesCoorientador: Prof. Dr. Mateus Duarte TeixeiraDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica. Defesa : Curitiba, 17/12/2021Inclui referências: p. 88-90Resumo: Para que um Sistema Elétrico de Potência opere satisfatoriamente, deve haver uma adequada coordenação do sistema de proteção, que é feita através de parametrização de ajustes de relés de proteção. Essa parametrização envolve estudos relacionados aos cálculos de correntes de curto-circuito, seletividade e coordenação entre os dispositivos de proteção. Esses estudos devem garantir que os sistemas de proteção operem no menor tempo possível e desliguem o mínimo de circuitos possíveis, ou seja, que os relés de proteção mais próximos da ocorrência do curto-circuito operem mais rapidamente do que os relés das linhas adjacentes. Por ser uma tarefa complexa, esse trabalho propõe que a obtenção desses parâmetros de ajustes, relacionados especificamente a relés de sobrecorrente instalados em sistemas malhados, seja feita utilizando um processo de otimização. Os parâmetros de entrada do problema de otimização são os valores de impedâncias de sequência das linhas de transmissão, geradores e transformadores que compõem o sistema elétrico. A partir desses dados são simulados alguns casos de curto-circuito que são necessários para inicializar o processo de otimização dos parâmetros de ajustes de sobrecorrente direcional de neutro instantâneo (67NI) e sobrecorrente direcional de neutro temporizado (67NT) em todos os terminais de linha do sistema em análise. A otimização envolve o ajuste de tempo de atuação dos relés temporizados 67NT que é dado por curvas inversas padronizadas, time dial (TDS) e corrente de Pick-up (IPS). Portanto, os parâmetros de ajuste do 67NT têm 3 variáveis que devem ser ajustadas: tipo de curva, TDS e IPS. A formulação do problema de otimização proposto para realização dos ajustes ótimos é resolvida via Algoritmos Genéticos e foi testada utilizando sistemas de 5 e 30 barras. Foi testada a coordenação de várias combinações desses ajustes até obter os valores ótimos coordenados para todos os relés dos sistemas testados.Abstract: For an Electric Power System to operate satisfactorily there must be an adequate coordination of the protection system, which is done through parameterization of protection relay settings. This parameterization involves studies related to the calculation of short-circuit currents, selectivity and coordination between protection devices. These studies must ensure that the protection systems operate in the shortest time possible and disconnect as few circuits as possible, that is, that the protection relays closest to the occurrence of the short circuit operate faster than the relays in the adjacent lines. As it is a complex task, this work proposes that the obtaining of these adjustment parameters, specifically related to overcurrent relays installed in meshed systems, be done using an optimization process. The input parameters of the optimization problem are the sequence impedance values of the transmission lines, generators and transformers that make up the electrical system. From these data, some short-circuit cases are simulated that are necessary to start the optimization process of the instantaneous directional overcurrent (67NI) and timed directional overcurrent (67NT) adjustment parameters in all the line terminals of the system under analysis. The optimization involves adjusting the actuation time of the 67NT timed relays which is given by standardized inverse curves, time dial (TDS) and Pick-up current (IPS). Therefore, the 67NT adjustment parameters have 3 variables that must be adjusted: curve type, TDS and IPS. The formulation of the optimization problem proposed to perform the optimal fits is solved via Genetic Algorithms and was tested using 5 and 30 bus systems. Coordination of various combinations of these settings was tested until the optimal coordinated values were obtained for all relays in the tested systems

Exploiting Heterogeneity in Networks of Aerial and Ground Robotic Agents

By taking advantage of complementary communication technologies, distinct sensing functionalities and varied motion dynamics present in a heterogeneous multi-robotic network, it is possible to accomplish a main mission objective by assigning specialized sub-tasks to specific members of a robotic team. An adequate selection of the team members and an effective coordination are some of the challenges to fully exploit the unique capabilities that these types of systems can offer. Motivated by real world applications, we focus on a multi-robotic network consisting off aerial and ground agents which has the potential to provide critical support to humans in complex settings. For instance, aerial robotic relays are capable of transporting small ground mobile sensors to expand the communication range and the situational awareness of first responders in hazardous environments. In the first part of this dissertation, we extend work on manipulation of cable-suspended loads using aerial robots by solving the problem of lifting the cable-suspended load from the ground before proceeding to transport it. Since the suspended load-quadrotor system experiences switching conditions during this critical maneuver, we define a hybrid system and show that it is differentially-flat. This property facilitates the design of a nonlinear controller which tracks a waypoint-based trajectory associated with the discrete states of the hybrid system. In addition, we address the case of unknown payload mass by combining a least-squares estimation method with the designed controller. Second, we focus on the coordination of a heterogeneous team formed by a group of ground mobile sensors and a flying communication router which is deployed to sense areas of interest in a cluttered environment. Using potential field methods, we propose a controller for the coordinated mobility of the team to guarantee inter-robot and obstacle collision avoidance as well as connectivity maintenance among the ground agents while the main goal of sensing is carried out. For the case of the aerial communications relays, we combine antenna diversity with reinforcement learning to dynamically re-locate these relays so that the received signal strength is maintained above a desired threshold. Motivated by the recent interest of combining radio frequency and optical wireless communications, we envision the implementation of an optical link between micro-scale aerial and ground robots. This type of link requires maintaining a sufficient relative transmitter-receiver position for reliable communications. In the third part of this thesis, we tackle this problem. Based on the link model, we define a connectivity cone where a minimum transmission rate is guaranteed. For example, the aerial robot has to track the ground vehicle to stay inside this cone. The control must be robust to noisy measurements. Thus, we use particle filters to obtain a better estimation of the receiver position and we design a control algorithm for the flying robot to enhance the transmission rate. Also, we consider the problem of pairing a ground sensor with an aerial vehicle, both equipped with a hybrid radio-frequency/optical wireless communication system. A challenge is positioning the flying robot within optical range when the sensor location is unknown. Thus, we take advantage of the hybrid communication scheme by developing a control strategy that uses the radio signal to guide the aerial platform to the ground sensor. Once the optical-based signal strength has achieved a certain threshold, the robot hovers within optical range. Finally, we investigate the problem of building an alliance of agents with different skills in order to satisfy the requirements imposed by a given task. We find this alliance, known also as a coalition, by using a bipartite graph in which edges represent the relation between agent capabilities and required resources for task execution. Using this graph, we build a coalition whose total capability resources can satisfy the task resource requirements. Also, we study the heterogeneity of the formed coalition to analyze how it is affected for instance by the amount of capability resources present in the agents