Review: Relay coordination in DGs with Electric Vehicle

. This research offers a comprehensive examination of the most effective approach to synchronize overcurrent relays within a protective system alongside protective relay. Every effort has been made to encompass all potential strategies for achieving optimal coordination among overcurrent relays. Both modern approaches, like Harris hawk optimisation, and more traditional ones, such ground-based circuit breakers, are included in this category of overcurrent protection with Electric Vehicle. The operation of a Smart Grid [1] is characterized by varying load demands, generation levels from DGs, and charging/discharging behaviours of EVs. These factors can lead to different fault currents and altered fault impedance profiles at various times. An adaptive coordination scheme can dynamically adjust relay settings based on these changing conditions to optimize sensitivity and minimize coordination time. In this paper briefly discuss traditional approaches but focus mostly on using Harris Hawk Optimisation to enhance the coordination of overcurrent relays. This document compiles citations for all relevant works and offers a concise overview of the study conducted. Furthermore, the outcomes of these methods are documented in their corresponding references.


Introduction
As the demand for electricity continues to grow, power sectors are struggling to keep up with maintenance and upgrades to outdated infrastructure.Present day electrical grids are antiquated and inefficient.High demand on the existing network might be caused by the present power system's inability to both fulfil load demand and deliver the electricity produced at the central power plant to consumers.As the quantity of electricity lost in the present system increases, its efficiency decreases.
Most of the energy that was produced was wasted in the form of transmission and distribution losses.These losses have a direct bearing on the network with respect to monetary results and system efficiency.Because of this, the essential objective of the ongoing examination is to amplify the capability of the existing network by careful planning and consistent use of easily accessible sources and emerging technologies.Recently, there has been significant attention focused on the utilization of sustainable energy resources for distributed generation (DG) [1].
Diverse interests in DG technologies have risen dramatically as a result of the potential to abandon conventional power plants in favour of long-term economic and environmental advantages.Network stability, line congestion alleviation, total loss reduction, and generating cost reduction are just a few of the ways in which DGs may aid with smart grid.In the evolving landscape of smart grids with distributed generation (DGs) and electric vehicle (EV) charging stations, ensuring reliable and efficient power distribution has become a complex challenge.One critical aspect of this challenge is the coordination of overcurrent transfers, which assume an essential part in safeguarding the grid from faults and overloads.However, the combination of DGs and EV charging stations introduces new dynamics, including bidirectional power flow and varying load patterns, that can compromise the sensitivity and accuracy of traditional overcurrent coordination schemes.

Distributed Generation
However, other nations use other criteria (such as the use of renewable, cogeneration, not being dispatchable, etc.) to define DG in addition to size and location.There is no generally acknowledged meaning of dispersed age (DG) in the writing; instead, several distinct terminology and concepts are used interchangeably.However, in academic literature, the definition of DG that enjoys widespread acceptance is as follows: "A power generation facility linked straightforwardly to the framework at circulation level voltage or arranged on the client's side of the meter " [2].Various synonymous terms for DG have surfaced in scholarly works, like implanted age, scattered age, appropriated energy assets (DER), and decentralized age.Dispersed generation is often used to describe any kind of distributed power production unit, whether it is grid-connected or fully off-grid [3].
No criteria or categorization of DG based on capacity has been specified in the preceding definitions.While there isn't a universally accepted standard, the subsequent interpretations find common use in numerous contexts and countries: In New Zealand, for a generating unit to fall under the category of DG, its output should not exceed 5 MW [4].As per data provided by the Gas Research Institute, the typical range for DG generating units spans from 25 kW to 25 MW [5].According to the Electric Power Research Institute (EPRI), distributed energy resources [6] encompass generating units, which can be pretty much as little as a couple of kilowatts (kW) and as extensive as 50 MW, along with energy storage devices that are often situated in close proximity to client burdens or circulation and sub-transmission substations.

Why Directional Overcurrent Relay
The feeder OC relay would trip when it detected a fault on the line, therefore eradicating the problem.There is still a fault current contribution from the DG in downstream places, however.Given that the DG's feeding influence would still threaten the microgrid system in an OC relay-only configuration, this is not an ideal situation.An application of directionsensitive security is warranted in this case.As a result, DOC relay is built into the network just upstream of the DG [ [7].In order to prevent damage to the distribution network's components, circuit breakers, relays, and fuses are installed [8].Even while relays are often assumed to be capable of properly determining the direction of current flow, this is not the case [9].This would make relays more useful for protecting power systems.When compared to conventional protection systems, directional overcurrent relays (DOCRs) provide dependable furthermore, proficient insurance at a lower cost, therefore they have been included into the development of financially savvy decisions for primary and reinforcement power framework safety.DOCRs enable for fewer relays to be used for protection, which lowers the cost of both the security gear and the establishment of such equipment by a considerable amount [10].These relays are the backbone of distribution and sub-transmission networks that talk to one another.They also serve as backup relays in transmission networks at the local level [11].In the aftermath of a power system failure, the current through the protected circuit surges significantly, which might cause further damage to the infrastructure.
To detect abnormalities like a short circuit or an overcurrent scenario, the DOCRs keep tabs on the current flow.At the point when an issue is recognized, the DOCR sends an outing sign to the electrical switch, causing it to activate and isolate the defective section of the electrical grid [12].In most cases, a DOCR will have two primary configuration settings: the time multiplier setting (TMS) and the plug setting (PS).With these parameters, you may select the amount of time that each relay is activated.Hand-off coordination studies are directed to decide the ideal settings for the TMS and PS, guaranteeing the correct sequence of relay operations and a total operating time optimised to reduce network downtime.Ensuring the necessary Coordination Time Interval (CTI) between the essential and reinforcement wellbeing measures is fundamental for protecting the respectability of selectivity research.This CTI addresses the term between the initiation of the essential and reinforcement transfers, and it should be of adequate span to empower the essential hand-off to successfully address the fault while also being brief enough to prevent unwarranted tripping of the backup relay [13].Coordination of the relays is crucial to avoiding accidental actions like the tripping of circuit breakers or the isolating of areas of the electrical system that are not faulty.The optimal timing of the relays' activation might help achieve this.On the other hand, the DOCR coordination issue may be formulated as a streamlining issue determined to limit the general working season of the DOCRs subject to a number of restrictions and boundary limitations, including the settings of the relays and the selectivity requirements.Static Differential Relays: Static relays[41], such as 2-phase and 3-phase protection against a variety of faults, such as earth faults that are either grounded with resistance in neutral or firmly grounded in neutral, are often favored.These relays have flaws and are densely sized, highly sensitive, and stable for a variety of defects.

Directional Overcurrent Protection & Coordination
To ensure the safe functioning and dependability of the electric system, it is necessary to coordinate the protective devices in order to preserve the selectivity among the devices engaged in many failure possibilities [13].
When the electrical system is supplying many locations, a DOR may be adjusted to be more sensitive than a standard overcurrent relay.DOR has two components for configuration: overcurrent and direction element.The basis for overcurrent relay coordination is established through the time-current characteristic curve and the operation of the relay.In other words, the directional element simplifies time-coordination by limiting relay response to failures in a single direction.Figure (14) depicts the fundamental concept of sympathetic fault, in which a problem on a neighbouring feeder causes a short circuit in the DG unit connected to the fundamental feeder through the substation bus.In the case of a substantial DG contribution, relay R1 may trip before relay R2 acts to remove the fault.Due to its inability to detect a reversal in shortcoming current course (invert issue), nondirectional overcurrent transfers may be employed for feeder protection.Most distribution utilities have used non-directional overcurrent relays for safety for a long time since their radial networks are single-fed, in contrast to the newer multisource distribution systems that have bidirectional current flow [15].It is common practise to use reverse overcurrent assurance transfers, in which transfers R1, R2, and R3 have their respective setting and coordination curves inverted.When there is a shortcoming current in line 3, the working span of transfer R2 is expanded to such an extent that it is longer than that of hand-off R3 by basically the time stretch whose end depends on things like the time it takes for the circuit breaker to open and the time it takes for the measuring element to return to its original position after being moved.In the case of electromechanical relays, overshoot must also be taken into account.In a similar vein, R2 and R1 relays are timed to respond to a maximum fault on their respective lines.

Smart Grid
The primary aim of the smart grid is to establish a network that possesses exceptional stability, inherent self-repair capabilities, autonomous regulation, responsiveness to demand, efficiency and state-of-the-art technology, enabling the seamless integration of a significant proportion of renewable energy sources.Figure 4 serves as an illustrative instance of a smart grid architecture, while the Smart Grid Resource Centre, operated by the Electric Power Research Institute (EPRI), offers a comprehensive overview of this concept at a higher level.In order to lessen negative effects on the environment, strengthen markets, boost dependability and service, save costs, and increase efficiency According to Wikipedia, "a Smart Grid is a power grid in which information and communications technology are used for all stages of the power system, from generation to distribution to end use."[58].
Consequently, the initiative would leverage cutting-edge information and communication technology to execute dynamic, real-time coordination of DOCRs.

Mitigation Methods
There are positive effects on the network as a whole, but there are also new difficulties [17] and bad effects on the protective overcurrent relays (OCRs) that come into play when DGs are added.The network is experiencing new circumstances, the most significant of which are a rise in cut off during issue circumstances and the bidirectional burden stream in spiral lines.Inaccurate tripping of the protection system's main and secondary relays, as well as a lack of coordination between them, are all possible outcomes.
The effect of DG infiltration on the transmission and dissemination organizations may be reduced using a number of suggested solutions, including those listed below: 1) Unplug DGs as soon as a problem is found [18]; 2) Capacity constraints of already deployed DGs [19]; 3) Alterations to the protection system, such as the addition of circuit breakers for network sectioning, reconfiguration, or the deployment of distance relays and/or directional overcurrent protective relays (DOCRs) [20]; 4) The use of fault current limiters (FCLs) to save the original relay configurations and to restore them in the event of a fault [21]; fifthly, inverter-based DGs with a fault-ride-through control approach [22]; 6) Synchronous DGs with fault current controlled by a field discharge circuit based on a solid-state switch [23]; 7) Differential evolution algorithm (APS) [24] adaptable safeguarding methods.8)Harris Hawk Optimization [30]; The existing overcurrent coordination schemes may not effectively adapt to these dynamic changes, potentially leading to issues for example, deficient issue recognition, delayed shortcoming clearing times, and unnecessary tripping of healthy sections of the grid.Moreover, the presence of multiple DG sources and EV charging stations introduces uncertainties and fluctuations that further complicate the coordination process.
To address these challenges, there is a pressing need for an innovative and adaptive overcurrent coordination scheme that can enhance the sensitivity and dependability of transfer tasks with regards to a shrewd framework with DGs and EV charging stations.This scheme should intelligently optimize relay settings to accommodate varying load conditions, bidirectional power flow, and the dynamic presence of DGs and EVs.Moreover, the scheme must also account for potential fault scenarios and seamlessly adjust relay coordination to ensure prompt fault detection and isolation, thereby enhancing the overall stability and performance of the smart grid.
The proposed research aims to develop an adaptive overcurrent coordination scheme utilizing the Harris Hawk Optimization algorithm in this context.By leveraging this optimization technique, the study seeks to intelligently determine relay settings that can adapt to the evolving grid conditions, improve fault detection sensitivity, and maintain efficient faultclearing times.The research addresses the technical intricacies of relay coordination and contributes to the overall unwavering quality and viability of brilliant lattices with the combination of DGs and EV charging stations.

Literature survey
The integration of distributed generations (DGs) and electric vehicle (EV) charging stations within smart grids has prompted significant research into enhancing relay coordination schemes to accommodate the evolving dynamics of these systems.This literature survey explores key studies and advancements in the field, focusing on the development of adaptive overcurrent coordination schemes, the application of optimization techniques such as the Harris Hawk Optimization algorithm, and the specific challenges posed by DGs and EV charging stations.
The foundation of modern power distribution systems relies on effective relay coordination to ensure fault detection, isolation, and system stability.Traditional coordination approaches often struggle to address the bidirectional power flow, fluctuating loads, and varying generation sources introduced by DGs and EVs.Researchers [25] have highlighted the need for adaptive coordination strategies to maintain reliable and responsive fault management.
Optimization algorithms have gained prominence for their ability to fine-tune relay settings in complex and dynamic power systems.The Harris Hawk Optimization algorithm [26] has been recognized for its efficiency and effectiveness in solving multi-objective problems, making it a promising candidate for enhancing relay coordination schemes in smart grids.
Adaptive coordination strategies aim to dynamically adjust relay settings to accommodate changing network conditions.Previous work in [27] has introduced adaptive schemes that utilize real-time measurements and predictive models to optimize relay settings, demonstrating improved sensitivity and fault detection capabilities.However, these studies often do not address the specific challenges introduced by DGs and EV charging stations.
The integration of DGs and EV charging stations introduces complexities such as bidirectional power flow, variable generation profiles, and sudden load fluctuations.
Research by [28] has highlighted the importance of considering these challenges in relay coordination, emphasizing the need for schemes that can adapt to these dynamics.
Maintaining grid resilience and stability in the presence of DGs and EVs is a critical concern.Researchers [29] have explored the effect of conveyed age on network elements and steadiness, underlining the significance of vigorous hand-off coordination to guarantee issue detection and rapid system recovery.
Apart from Harris Hawk Optimization, other optimization algorithms like Genetic Algorithms and Particle Swarm Optimization have been applied to relay coordination in distribution systems [30].These studies demonstrate the potential of optimization techniques in adapting relay settings to enhance fault sensitivity and selectivity.
Programmed internet-based re-change of hand-off settings is at the heart of the adaptive protection method suggested in [31], allowing the relays to be optimally adjusted for changing network operating circumstances caused by dispatch or natural factors.These shifts are the result of shifting inputs and outputs at generators and transmission nodes, which in turn affects the distribution of load current and fault current.
The coordination problem of Directional Overcurrent Relays (DOCRs) has been approached through a diverse array of optimization techniques and bio-inspired algorithms, each aiming to find optimal relay setting parameters.Notably, various population-based optimization methods were applied in [32], employing a mixed integer nonlinear programming (MINLP) framework.Bio-motivated algorithms, as demonstrated in [33], tackled the DOCR coordination challenge by concocting a straight definition.
Additionally, a range of particle swarm optimization (PSO) adaptations were harnessed in [34] to discern optimal DOCR values, showcasing the versatility of PSO variations.An alternative differential algorithm version was introduced in [35], highlighting the enhanced performance of modified differential evolution algorithms in solving the DOCR coordination problem.Furthermore, in [36], the complexities of DOCR coordination were tackled with the help of algorithms inspired by nature, such as the grey wolf optimizer (GWO), the teaching learningbased optimisation (TLBO), the biography-based optimisation (BBO), the back-tracking algorithm (BTA), the improved firefly algorithm (IFA), and the modified electromagnetic field optimisation (MEFO).In [13], an adaptation of an optimisation method for instructional purposes was developed.Employing an analytical approach, [37] outlined a method to resolve the DOCR coordination problem.Furthermore, [38] utilized an improved group search algorithm to determine relay setting parameters.
In [39], the author provides a detailed analysis of the strengths and weaknesses of several metaheuristic algorithms for DOCR issue solving.Multiple embedded crossover PSO algorithm was introduced in [40] to tackle the DOCR problem effectively.
The existing literature underscores the significance of adaptive overcurrent coordination schemes in smart grids with DGs and EV charging stations.The incorporation of optimization techniques like the Harris Hawk Optimization algorithm offers a promising avenue to address the challenges posed by bidirectional power flow, load variations, and intermittent generation sources.The proposed research aims to build upon these foundations by developing a comprehensive adaptive overcurrent coordination scheme, thereby contributing to the advancement of reliable and efficient power appropriation frameworks in the context of modern smart grids.
With Utilization of the Harris Hawk Optimization algorithm to fine-tune the relay settings iteratively, optimizing for improved sensitivity, selectivity, and fault response.Investigate the scheme's robustness against uncertainties, variations in DG output, and sudden load changes.Conduct sensitivity analyses to assess the impact of parameter changes on the scheme's performance.By following this methodology, the proposed Adaptive Overcurrent Coordination Scheme leveraging Harris Hawk Optimization can be systematically will be developed, validated, and assessed for its effectiveness in improving relay sensitivity and fault response in a smart grid with DGs and EV charging stations.

Figure 1 .
Figure 1.DG contribution to fault incident at adjacent feeder Relays that utilise the phase connection between voltage and current to identify the fault's location are called directional overcurrent relays [16].

Figure 2 .
Figure 2.Directional Overcurrent Protection 5 Impact of DG on Relay coordination in Distribution system