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

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 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 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

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

Upgrading Plan for Conventional Distribution Networks Considering Virtual Microgrid Systems

It is widely agreed that the integration of distributed generators (DGs) to power systems is an inevitable trend, which can help to solve many issues in conventional power systems, such as environmental pollution and load demand increasing. According to the study of European Liaison on Electricity grid Committed Towards long-term Research Activities (ELECTRA), in the future, the control center of power systems might transfer from transmission networks to distribution networks since most of DGs will be integrated to distribution networks. However, the infrastructure of conventional distribution networks (CDNs) has not enough capabilities to face challenges from DG integration. Therefore, it is necessary to make a long-term planning to construct smart distribution networks (SDNs). Although many planning strategies are already proposed for constructing SDNs, most of them are passive methods which are based on traditional control and operating mechanisms. In this thesis, an active planning framework for upgrading CDNs to SDNs is introduced by considering both current infrastructure of CDNs and future requirements of SDNs. Since conventional centralised control methods have limited capabilities to deal with huge amount of information and manage flexible structure of SDNs, virtual microgrids (VMs) are designed as basic units to realise decentralised control in this framework. Based on the idea of cyber-physical-socioeconomic system (CPSS), the structure and interaction of cyber system layer, physical system layer as well as socioeconomic system layer are considered in this framework to improve the performance of electrical networks. Since physical system layer is the most fundamental and important part in the active planning framework, and it affects the function of the other two layers, a two-phase strategy to construct the physical system layer is proposed. In the two-phase strategy, phase 1 is to partition CDNs and determine VM boundaries, and phase 2 is to determine DG allocation based on the partitioning results obtained in phase 1. In phase 1, a partitioning method considering structural characteristics of electrical networks rather than operating states is proposed. Considering specific characteristics of electrical networks, electrical coupling strength (ECS) is defined to describe electrical connection among buses. Based on the modularity in complex network theories, electrical modularity is defined to judge the performance of partitioning results. The effectiveness of this method is tested in three popular distribution networks. The partitioning method can detect VM boundaries and partitioning results are in accord with structural characteristics of distribution networks. Based on the partitioning results obtained in phase 1, phase 2 is to optimise DG allocation in electrical networks. A bi-level optimisation method is proposed, including an outer optimisation and an inner optimisation. The outer optimisation focus on long-term planning goals to realise autonomy of VMs while the inner optimisation focus on improving the ability of active energy management. Both genetic algorithm and probabilistic optimal power flow are applied to determine the type, size, location and number of DGs. The feasibility of this method is verified by applying it to PG&E 69-bus distribution network. The operation of SDNs with VMs is a very important topic since the integration of DGs will lead to bidirectional power flow and fault current variation in networks. Considering the similarity between microgrids and VMs, a hybrid control and protection scheme for microgrids is introduced, and its effectiveness is tested through Power Systems Computer Aided Design (PSCAD) simulation. Although more research is needed because SDNs are more complicated than microgrids, the hybrid scheme has great potential to be applied to VMs

Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review

YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000

Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems

Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. Also, it provides a comprehensive survey on the power system applications that have benefited from the powerful nature of PSO as an optimization technique. For each application, technical details that are required for applying PSO, such as its type, particle formulation (solution representation), and the most efficient fitness functions are also discussed

Power quality and electromagnetic compatibility: special report, session 2

The scope of Session 2 (S2) has been defined as follows by the Session Advisory Group and the Technical Committee: Power Quality (PQ), with the more general concept of electromagnetic compatibility (EMC) and with some related safety problems in electricity distribution systems. Special focus is put on voltage continuity (supply reliability, problem of outages) and voltage quality (voltage level, flicker, unbalance, harmonics). This session will also look at electromagnetic compatibility (mains frequency to 150 kHz), electromagnetic interferences and electric and magnetic fields issues. Also addressed in this session are electrical safety and immunity concerns (lightning issues, step, touch and transferred voltages). The aim of this special report is to present a synthesis of the present concerns in PQ&EMC, based on all selected papers of session 2 and related papers from other sessions, (152 papers in total). The report is divided in the following 4 blocks: Block 1: Electric and Magnetic Fields, EMC, Earthing systems Block 2: Harmonics Block 3: Voltage Variation Block 4: Power Quality Monitoring Two Round Tables will be organised: - Power quality and EMC in the Future Grid (CIGRE/CIRED WG C4.24, RT 13) - Reliability Benchmarking - why we should do it? What should be done in future? (RT 15