Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions

International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075 (Online), Volume-14 Issue-12, November 2025 13 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org Abstract: Microgrids, pivotal in modern power systems, face unique protection challenges due to bidirectional power flows, dynamic topologies, and inverter-based resources (IBRs). This systematic review critically analyzes 55 peer-reviewed studies (2020-2024) to evaluate microgrid protection challenges, methods, and emerging solutions. We synthesize findings from IEEE Xplore, MDPI, Springer, Wiley, and Taylor & Francis databases using the PRISMA framework. Key challenges include bidirectional power flow (36% of studies), low fault currents (33%), and protection coordination failures (62%). Conventional methods like overcurrent and distance protection struggle with adaptability, while adaptive, communication-assisted, and intelligent strategies show promise but face complexity and cybersecurity risks. AI-driven methodologies achieve a fault-detection accuracy of 99.2%. However, they require substantial datasets and considerable computational resources. Resilience frameworks remain inadequately developed, with merely 10% of the literature addressing critical metrics such as reliability and recovery. This review underscores the imperative for hybrid solutions and the establishment of standardised resilience metrics. It also highlights the importance of validating findings in real-world contexts to ensure the practical application of theoretical progress. Future investigations should emphasise the importance of cybersecurity measures, the implementation of modular enhancements for legacy systems, and the development of explainable artificial intelligence to reconcile theoretical progress with practical application. Keywords: Adaptive Protection, Conventional Protection, Intelligent Protection, Microgrid, Systematic Review. Nomenclature: KPIs: Key Performance Indicators HIFs: High-Impedance Faults DERs: Distributed Energy Resources RES: Renewable Energy Sources DOCP: Directional overcurrent protection IBRs: Inverter-Based Resources CTs: Current Transformers DGs: Distributed Generators MTD: Moving Target Defence TCCs: Time-Current Curves PMUs: Phasor Measurement Units TCV: Time-Current-Voltage Manuscript received on 01 November 2025 | Revised Manuscript received on 10 November 2025 | Manuscript Accepted on 15 November 2025 | Manuscript published on 30 November 2025. *Correspondence Author(s) Dr. Houssem Ben Aribia*, Department of Electrical and Electronics Engineering, College of Engineering and Computer Science, Jazan University, Jizan, Saudi Arabia. Email ID: [email protected], ORCID ID: 0009-0007-9085-3689 Dr. Ferchichi Noureddine, National High Engineering School of Tunis, Tunisia. Email ID: [email protected], ORCID ID: 0009-0000-2726-7176 Dr. Slim Abid, Department of Electrical and Electronics Engineering, College of Engineering and Computer Science, Jazan University, Jizan, Saudi Arabia. Email ID: [email protected], ORCID ID: 0009-0002-0655-6088 © The Authors. Published by Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license http://creativecommons.org/licenses/by-nc-nd/4.0/ ML: Machine Learning AI: Artificial Intelligence ANNs: Artificial Neural Networks SVMs: Support Vector Machines MAS: Multi-Agent Systems PMUs: Phasor Measurement Units TW: Travelling Wave DSDRs: Dual-Setting Directional Reclosers FRT: Fault Ride-Through TCV: Time-Current-Voltage ENS: Energy Not Served I. INTRODUCTION Microgrids, including residential, commercial, and industrial variants, have revolutionized contemporary power systems by incorporating distributed energy resources (DERs), improving reliability, resilience, and sustainability. Unlike traditional centralized grids, these microgrids operate independently or in grid-connected modes, dynamically However, these unique operational characteristics create managing local generation, storage, and loads. significant protection challenges as conventional protection schemes struggle to handle bidirectional power flows, islanding transitions, and fluctuating short-circuit levels [1]. As microgrids expand, researchers must develop advanced protection strategies that ensure selectivity, reliability, and adaptability under varying grid conditions [2]. Over the past decade, researchers have proposed numerous microgrid protection methods, including adaptive protection, artificial intelligence (AI)-based approaches, and communication-assisted techniques [3], [4]. Despite this progress, no comprehensive study systematically compares the effectiveness, adaptability, and implementation complexity of these methods. In this systematic review, we critically examine the extant literature, categorise the principal challenges in protection, and evaluate the most viable solutions. Our methodical framework guarantees an impartial and transparent assessment of research outcomes, thereby assisting engineers and policymakers in making well-informed choices regarding prospective microgrid protection methodologies [5]. This systematic review aims to answer the following key questions: ▪Question 1: What are the main challenges in microgrid protection, and how do they differ from conventional power system protection? This question aims to identify and classify challenges in microgrid protection and to analyse the influence of renewable energy sources on fault detection, selectivity, and protection system coordination. ▪Question 2: What are the most commonly used microgrid protection methods? How do they Houssem Ben Aribia, Ferchichi Noureddine, Slim Abid Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions 14 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org compare in performance, adaptability, and implementation complexity? How do they improve fault detection and system resilience? This question aims to compare and evaluate traditional and modern protection approaches. ▪ Question 3: What are the recent advances in intelligent microgrid protection systems? This question explores the role of AI, machine learning, and communication-based approaches in improving microgrid protection. These three questions form the basis of the work, and every decision made during its development will aim to answer them successfully. This review paper organizes its analysis into five distinct sections: The first section introduces the paper. The second section demonstrates the meticulous, systematic review method used to develop the review, ensuring the credibility and thoroughness of our research. The third section shows the details of our analysis's results. It discusses the implications of the key findings for microgrid protection challenges, renewable energy integration, protection methods, and advances in intelligent protection. The fourth section summarizes the conclusions and suggests future research directions. II. SYSTEMATIC REVIEW METHOD A. Information Sources This review gathered literature from five well-known databases: ▪ IEEE Xplore ▪ MDPI ▪ Taylor & Francis ▪ Springer ▪ Wiley B. Search Strategy The specific search terms employed included "Microgrid," "Isolated grid," "Distributed energy resources," "Protection," "Fault protection," "Relay coordination," "Challenges," "Methods," and "Solutions." The query strings, which include combinations of key terms like "Microgrid," "Isolated grid," "Distributed energy resources," "Protection," "Fault protection," "Relay coordination," "Challenges," "Methods," and "Solutions," were designed to narrow down the search results to the most relevant papers. A filter was applied to the initial search results, reducing the number of papers to a manageable level. The number of documents presented without this restriction is 2241. We considered the following filters: ▪ This review used only peer-reviewed journal papers and rigorously verified and credible research while emphasizing microgrid protection studies. This targeted approach ensures that the review remains relevant and comprehensive, exploring both theoretical and applied aspects of microgrid protection through modeling, simulation, and practical case studies. ▪ This review used only papers published between 2020 and 2024, ensuring that the information in this study is up-to-date. By focusing on studies published over the past five years, the journal captures the latest advances and contemporary methodologies, reflecting the current state of research and technological progress. ▪ This review used only papers in English, a language considered the most common for scientific research. By focusing on English, we aimed to ensure the broadest accessibility and comprehensibility, as it is the predominant language of scientific communication, keeping our audience informed and knowledgeable. The different tools employed to organize and evaluate the papers were: - Mendeley Reference Manager: Eliminate duplicates, read, take notes, and organize papers throughout the process. - Microsoft Excel: Arrange and evaluate data. C. Selection Process i. Prisma Methodology This review employs the PRISMA 2020 Statement (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) [5] to guide its literature selection process, minimizing potential biases and improving transparency. This systematic approach consists of four stages: ▪ Identification ▪ Screening ▪ Eligibility & Inclusion ▪ Synthesis Figure 1 illustrates an overview of the PRISMA methodology. [Fig.1: Literature Review Process Based on PRISMA Methodology] ii. Identification Stage In the Identification stage, we retrieved 347 items using the search strategy defined in the information sources subsection. We introduced a coding system International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075 (Online), Volume-14 Issue-12, November 2025 15 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org for each item according to the database consulted. Table I presents the identified extracted items. Table I: The Coding System of the Extracted Items Data Base Coding System IEEE Xplore xxxx-IEEE MDPI xxxx-MDPI Taylor & Francis xxxx-Taylor Springer xxxx-Springer Wiley xxxx-Wiley We significantly reduced the risk of redundant analysis and bias by diligently removing duplicate entries. With the aid of Mendeley Reference Manager, we identified and eradicated 22 duplicate records, resulting in a precise total of 325 unique items for our research. Figure 2 presents a comprehensive overview of the item distribution across the databases, providing a clear picture of our research scope: 94 items from IEEE Xplore, 115 items from MDPI, 14 items from Taylor & Francis, 34 items from Springer, and 68 items from Wiley. [Fig.2: Statistics of the Papers Found in the Identification Stage] iii. Screening Stage In the Screening stage, we thoroughly reviewed the titles and abstracts to verify their relevance to the research objectives, using predefined inclusion and exclusion criteria. We carefully defined these criteria to ensure the selection of the most relevant and high-quality studies for protecting microgrids. ▪ Inclusion Criterion (IC) IC1: We included papers published between 2020 and 2024 in English-language journals focusing on protecting microgrids or power systems integrated with distributed generators. ▪ Exclusion Criteria (EC) EC1: We exclude studies published before 2020 and documents such as editorials and conference papers. Our focus is on original contributions that provide new empirical findings or methodologies. EC2: We exclude abstracts that show the study does not focus on a microgrid or power system with distributed generators. EC3: We exclude review papers, reaffirming our commitment to only consider primary sources, thereby ensuring the reliability of our research. [Fig.3: Screening Stage Process] Figure 3 shows the Screening stage process, which resulted in the exclusion of 82 items (25% of the database's total) and the inclusion of 243 items (75% of the database's total). The included items appear across the databases as follows: ▪ 75 items from IEEE Xplore ▪ 82 items from MDPI ▪ 9 items from Taylor & Francis ▪ 23 items from Springer ▪ 54 items from Wiley iv.Eligibility and Inclusion Stage In the Eligibility and Inclusion stage, we assessed the full-text versions of the selected papers using predefined Key Performance Indicators (KPIs) to ensure relevance, quality, and contribution to our review objectives. We established a verification matrix, as summarized in Table II, to evaluate each study based on: ▪ The discussion of microgrid protection challenges. ▪ The impact of renewable energy. ▪ The protection methods. ▪ The advancements in intelligent protection systems. A set of criteria guided us selection process. We Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions 16 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org prioritized studies that comprehensively identified protection challenges, classified protection techniques, analyzed performance metrics, and assessed adaptability in microgrid conditions. We also favoured papers that investigated the impact of renewable energy integration on protection reliability and selectivity. Furthermore, we evaluated studies on AI-based and communication-based protection methods for their contributions to system resilience. To ensure the highest methodological rigour, we considered citation count and the level of experimental validation. Each paper was assigned a total score, and only those that met the minimum threshold of 20 points out of 24 (85%) were included in our final dataset, ensuring the inclusion of highly relevant, high-quality studies. Table II: Verification Matrix Category Key Performance Indicators (KPIs) Description Scoring Criteria Challenges in Microgrid Protection CIS: Challenge Identification Score Discusses microgrid-specific protection challenges 0 = No 1 = Brief Mention 2 = Detailed Discussion CCP: Comparison with Conventional Protection Compares microgrid protection with conventional power system protection 0 = No 1 = General Mention 2 = In-depth Analysis Impact of Renewable Energy on Protection RIC: Renewable Integration Coverage Evaluates the impact of renewable energy on microgrid protection 0 = No 1 = Brief Mention 2 = Detailed Impact Assessment RSA: Reliability & Selectivity Assessment Analyzes how renewable energy affects protection system reliability and selectivity 0 = No 1 = Qualitative 2 = Quantitative (simulations/experiments) Evaluation of Protection Methods MCS: Method Classification Score Categorizes protection methods 0 = No 1 = Some methods 2 = Comprehensive classification PMD: Performance Metrics Discussion Evaluates methods based on detection speed, sensitivity, and false alarm rate. 0 = No 1 = Basic discussion 2 = Detailed numerical comparison ACA: Adaptability and Complexity Analysis Assesses the adaptability of methods under different operating conditions 0 = No 1 = Basic mention 2 = Case study/simulation Advances in Intelligent Protection AIS: AI & ML Integration Score Discusses AI, ML, or deep learning for microgrid protection 0 = No 1 = Mentioned 2 = Algorithm presented/tested CBP: Communication-Based Protection Covers communication-based or adaptive protection schemes 0 = No 1 = Mentioned 2 = Analyzed in detail RI: Resilience Improvement Shows how intelligent methods improve resilience during faults 0 = No 1 = Theoretical discussion 2 = Experimental/simulated proof General Paper Quality Indicators Experimentation Level (EL) Level of validation 0 = Theoretical only 1 = Simulation-based 2 = Real-world validation Citation Count (CC) Number of citations 0 = <10 1 = 10–50 2 = >50 We evaluated the 243 items from the Screening stage using the Table I criteria, resulting in 55 papers being included in this review. We used an MS Excel sheet to assess the documents and included those scoring 85% or higher (20 points out of 24). Figure 4 illustrates the Eligibility and Inclusion stage results, which led to the exclusion of 188 items (77% of the database) and the inclusion of 55 items (23% of the database). The scoring distribution based on KPIs indicates that most included papers scored between 17 and 20 points. The included items with a score of 85% or higher (20 points out of 24) are distributed across the databases as follows: ▪ 37 items from IEEE Xplore ▪ 9 items from MDPI ▪ 0 items from Taylor & Francis ▪ 1 item from Springer ▪ 8 items from Wiley International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075 (Online), Volume-14 Issue-12, November 2025 17 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org [Fig.4: Eligibility and Inclusion Stage] v. Synthesis Stage This stage aims to classify and interpret research contributions, and to identify significant trends and topics in microgrid protection. We combined synthesis methods with flowcharts for each research question to provide rigorous, reproducible answers. This method is consistent with the PRISMA systematic review guidelines, a framework known for its transparency and active synthesis, which reassures the reader of the reliability of our study. Figure 5 presents a flowchart outlining the systematic breakdown of how each question was synthesised. Figure 5 presents the Synthesis method used for questions 1 (Q1), 2 (Q2), and 3 (Q3). [Fig.5: Synthesis Method] III. RESULTS AND DISCUSSIONS A. Challenges in Microgrid Protection and Differences from Conventional Systems i. Novel Taxonomy of Challenges The growing penetration of distributed energy resources (DERs) drives the rapid development of microgrids, which, in turn, introduce protection challenges that differ significantly from those in conventional power systems. In this review, we address the question, "What are the main challenges in microgrid protection, and how do they differ from conventional power system protection?" by synthesising insights from 55 papers ([6]-[60]). To identify dominant challenges, we implemented a bibliometric analysis. Table III presents a quantitative and thematic breakdown of challenges in microgrid protection and their differences from conventional grids. Table III: Quantitative and Thematic Breakdown of Challenges in Microgrid Challenge Frequency All Papers Addressing the Challenge Bidirectional power flow 20 out of 55 papers 36% [6], [10], [11], [14], [15], [17], [22], [24], [25], [30], [31], [40], [43], [48], [49], [50], [54], [57], [58], [59] Low/limited fault currents 18 out of 55 papers 33% [7], [10], [12], [13], [14], [20], [25], [27], [29], [30], [31], [36], [46], [49], [54], [55], [56], [60] Fault current variability (grid-connected - islanded) 17 out of 55 papers 31% [6], [12], [15], [22], [26], [28], [34], [38], [40], [43], [44], [47], [50], [51], [52], [55], [59] Communication dependency 20 out of 55 papers 36% [7], [8], [13], [25], [26], [29], [30], [31], [32], [33], [36], [37], [43], [44], [46], [48], [53], [54], [55], [57] High-impedance fault (HIF) detection 9 out of 55 papers 16% [13], [14], [15], [18], [23], [28], [40], [41], [56] Sensitivity to noise 5 out of 55 papers 9% [7], [13], [29], [41], [54] Voltage/frequency instability 6 out of 55 papers 11% [16], [26], [41], [49], [50], [53] Inverter-based resource (IBR) limitations 17 out of 55 papers 31% [7], [10], [12], [13], [19], [25], [27], [28], [30], [31], [44], [46], [49], [55], [56], [57], [60] Protection blinding Miscoordination 34 out of 55 papers 62% [6], [8], [10], [11], [15], [16], [17], [19], [21], [22], [23], [24], [25], [27], [28], [30], [31], [33], [34], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [53], [57], [58], [59], [60] ii. Bidirectional Power Flow Bidirectional power flow in microgrids complicates fault detection and relay coordination. Unlike conventional systems with unidirectional power flow, microgrids render traditional directional protection schemes ineffective and increase the risk of sympathetic tripping, as recloser-fuse coordination often fails under reverse-power-flow conditions. iii. Variable and Low Fault Current Levels Inverter-based microgrids limit fault currents to 1.2–2 p.u., far below the 5–10 p.u. range. typically generated by synchronous generators in conventional grids. This lower current range prevents traditional overcurrent relays from functioning reliably, particularly in islanded mode, and leaves high-impedance faults (HIFs) nearly undetectable. While the fluctuating nature of renewable energy sources (RES) reduces the sensitivity of conventional protection methods, potentially delaying fault clearance and raising misoperation risks, localised generation simultaneously strengthens resilience. For example, RES in islanded mode can supply backup power during grid disturbances, sustaining critical loads. Achieving this advantage, however, requires deploying advanced protection strategies that rapidly isolate faults and shorten outage durations. Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions 18 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org iv. Dynamic Topology and Operating Modes Microgrids frequently switch between grid-connected and islanded modes, causing significant variations in fault current magnitudes and network configurations. In islanded mode, fault currents can drop to just 2–3 times the rated current, far lower than those observed when connected to the primary grid. These shifting operational states demand adaptive protection schemes that dynamically adjust relay settings in real time, unlike conventional systems, which rely on static topologies and fixed configurations. v. Inverter-Based Microgrids Limitations Inverter-based microgrids generate non-sinusoidal fault currents with harmonic distortions and controlled phase angles, complicating phasor estimation and relay coordination. Distance relays, for example, frequently misoperate when exposed to the atypical fault behaviours of inverter-based microgrids. Unlike synchronous machines, these microgrids cannot generate stable sinusoidal waveforms during faults. Furthermore, harmonics produced by inverters disrupt relay fault-detection algorithms, forcing engineers to integrate advanced filtering methods to improve accuracy. vi.High-Impedance Faults (HIFs) and Sensitivity Issues High-impedance faults produce low-magnitude currents that overlap with load currents, making fault detection in microgrids challenging. Under high renewable energy penetration, this "protection blindness" becomes more pronounced, as traditional overcurrent protection relies on the high fault currents typical of conventional systems. vii.Communication and Synchronization Requirements Advanced protection schemes rely on high-bandwidth communication networks for real-time coordination. This reliance exposes microgrids to risks such as delays, synchronization issues, and cyber-attacks like false-data injection that compromise relay operations, unlike the simpler, decentralized protection found in conventional systems. viii. Protection Coordination Challenges The intermittent output of RES and variable fault currents disrupts coordination among primary relays, backup devices, reclosers, and fuses. In microgrids, RES back-feed currents can trigger sympathetic tripping, disconnect healthy feeders and complicate fixed coordination strategies that work well in static, radial conventional networks. ix. Grounding and Re-Synchronization Issues During islanded operation, microgrids lose the primary grid’s grounding reference, which complicates ground fault detection. Additionally, re-synchronization during grid reconnection introduces voltage and frequency deviations that force dynamic adjustments in relay settings to maintain system stability. x. Cyber-Physical Vulnerabilities Many studies emphasize that the integration of RES increases the reliance on sophisticated control strategies and robust communication networks. While these systems enable adaptive protection by continuously updating relay settings, they also introduce vulnerabilities related to communication delays and potential cyber threats, and expose microgrids to cyber-attacks such as false-data injection (FDI), which can disrupt relay coordination. These vulnerabilities pose significant risks to protection reliability and system stability, conventional systems, with simpler decentralized protection, face fewer such threats due to predictable fault behavior. xi. Weather-Dependent Fault Current Variability Renewable energy sources (RES) create intermittent fault currents because solar irradiance and wind speeds vary unpredictably. These weather-dependent variations complicate the coordination of protective relays, forcing engineers to adopt stochastic modelling to ensure reliable system operation. In contrast, conventional power systems rely on stable synchronous generation, which inherently avoids such unpredictability. Figure 6 presents a comprehensive mind map outlining the key challenges in microgrid protection and highlighting how they differ from those in conventional power system protection. [Fig.6: Mind Map of Key Challenges in Microgrid Protection] Microgrid challenges are classified into four interconnected categories that reflect their technical, operational, economic, and regulatory dimensions. International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075 (Online), Volume-14 Issue-12, November 2025 19 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org Table IV: Microgrid Challenges Categories Category Sub-Challenges Key Papers Technical Bidirectional power flow 51 out of 55 papers 93% Low/inconsistent fault currents (IBR limitations) Relay coordination failures High-impedance fault (HIF) detection Voltage/frequency instability Operational Mode transitions (grid-connected ↔ islanded) 18 out of 55 papers 33% Dynamic topology changes DG penetration variability Communication latency/packet loss Economic High cost of differential protection 5 out of 55 papers 9% Communication infrastructure expenses Retrofitting legacy systems Regulatory Lack of microgrid-specific standards 3 out of 55 papers 5% Inverter compliance issues Cybersecurity mandates Tables III and IV show that most researchers focus primarily on technical challenges in modern power systems, with 93% of the papers exploring bidirectional issues. This substantial focus underscores engineers' need to revamp traditional systems to accommodate energy from distributed sources. The research also investigates issues such as low and inconsistent fault currents from inverter-based sources, relay coordination problems, difficulties in detecting high-impedance faults, and voltage and frequency stability issues. About 33% of the studies examine operational challenges, such as the intricacies of switching between grid-connected and islanded modes, changes in network layouts, variations in distributed generation, and communication delays or losses that can disrupt system control. Only 9% of the research addresses economic challenges, such as the high cost of differential protection, suggesting that cost issues and outdated system updates are not the primary focus. Finally, just 5% of the papers address regulatory challenges, highlighting the need to establish specific standards, improve inverter compliance, and strengthen cybersecurity to underpin new grid technologies. B. Linking Challenges to Real-World Failures While many studies rely on simulations, it's rare for a small subset of authors to bridge theoretical challenges with practical outcomes successfully. This exceptional approach validates theoretical models and underscores the urgent need to address these issues in real-world applications. With only 2% of studies (1 out of 55) directly correlating these challenges with documented real-world incidents, the significant gap between research and practical incident analysis becomes even more pronounced. The Ukrainian Grid Attack (2015) serves as a stark reminder of the potential devastation of a synchronized and coordinated cyberattack. This incident compromised three Ukrainian regional electric power distribution companies, leading to power outages that affected approximately 225,000 customers for several hours. The exacerbation of cascading outages due to communication failures in adaptive protection [9] underscores the gravity of the situation. U.S. Wind/Solar Cyberattacks (2019): A denial-of-service attack left grid operators temporarily blinded to several wind and solar farm generation sites in the U.S. Spoofed relay settings delayed fault clearing [9]. Case studies bridge theoretical research and practical implementation. Only 13% of studies (7/55) validate findings with real-world data. C. Mapping Challenges to Microgrid Archetypes The literature differentiates microgrid protection issues based on system architecture. Papers that explore centralized versus distributed configurations or compare grid-connected with islanded modes reveal that challenges vary significantly with system design. For instance, the unique challenges posed by low fault currents in inverter-based islanded microgrids and the more pressing issues created by communication delays in large, distributed networks highlight the field's complexity. Mapping these distinctions enables engineers to customize protection strategies for specific microgrid archetypes (Table V), ensuring solutions balance effectiveness and cost-efficiency. Table V: Microgrid Archetypes Archetype Key Challenges Key Papers Grid-Conne cted ▪ Islanding detection and prevention ▪ Bidirectional power flow complicates fault current contributions ▪ Coordination between microgrid and central grid protection systems ▪ Dynamic network topology requiring adaptive settings Impact of cybersecurity vulnerabilities in communication-based schemes 33 out of 55 papers 60% Islanded (IBR-Domi nated) ▪ Reduced fault current levels and lack of external support ▪ Frequency and voltage regulation challenges ▪ Limited backup protection and inertia ▪ Adaptive protection schemes required for isolated operation Maintaining stability without a grid reference 16 out of 55 papers 29% AC Microgrid ▪ Inverter-based resource behaviour reduces fault current levels ▪ Sensitivity issues with traditional overcurrent relays ▪ Coordination with legacy protection systems ▪ Variable fault contributions from renewable sources Necessity for adaptive and fast-acting protection schemes 6 out of 55 papers 11% DC Microgrid ▪ Lack of natural current zero crossings, complicating arc fault detection ▪ Fast transient fault detection and isolation requirements ▪ Limited availability of standard protection devices ▪ Overvoltage and short-circuit protection challenges Rapid response needs for fault isolation 1 out of 55 papers 2% Hybrid Microgrid ▪ Coordinating protection between AC and DC subsystems ▪ Bridging different voltage levels and fault characteristics ▪ Inconsistent fault propagation across domains ▪ Complex system integration and adaptive setting challenges Communication delays between the AC and DC protection layers 2 out of 55 papers 4% Multi-Micr ogrid Clusters ▪ Complex inter-microgrid protection coordination ▪ Cascading fault propagation risks ▪ Communication and latency challenges across different microgrids ▪ Multi-layered protection settings requiring synchronization Ensuring consistency in adaptive protection schemes across a distributed network 3 out of 55 papers 5% D. Resilience Scoring Framework Resilience metrics are vital for assessing and enhancing Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions 20 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org microgrid reliability in the face of uncertainties such as component failures, extreme weather, or cyberattacks. Researchers and practitioners commonly emphasize the following key resilience metrics and concepts in the literature: i. Reliability and Availability Metrics ▪ Loss of Load Probability (LOLP): is a practical metric that quantifies the probability of the available supply failing to meet the load demand during a specific period. This metric is not just a theoretical concept but a tool for assessing and improving the reliability of a microgrid in real-world scenarios. ▪ Expected Energy Not Served (EENS): estimates that the energy system fails to deliver critical loads during outages. ▪ The System Average Interruption Frequency Index (SAIFI) and Duration Index (SAIDI): These indices accurately assess the frequency and duration of power interruptions in the context of microgrids, making them highly relevant and applicable to energy systems and microgrid technology. ii. Recovery and Restoration Metrics ▪ Mean Time to Recovery (MTTR): Measures the average time it takes for the microgrid to recover after a disruptive event. ▪ Time to Resilience (TR): Metric that may include restoration time and the time required to re-establish full operational functionality, including synchronization with the primary grid if needed. iii. Robustness and Flexibility ▪ Contingency Analysis (N-1, N-2, etc.): The microgrid can sustain operation when one or more components fail. ▪ Reserve Margin: Extra capacity to meet demand during unexpected outages or load spikes. ▪ Diversity of Energy Sources: Mix and redundancy of generation resources can indicate resilience. iv. Operational Resilience Metrics ▪ Self-Healing Capabilities: Measures how effectively a microgrid can automatically reconfigure or isolate faults to prevent cascading failures. ▪ Cyber-Physical Resilience Indicators: Metrics assessing the physical infrastructure and its cybersecurity. v. Economic and Performance-Based Metrics ▪ Cost of Resilience: Evaluate the economic trade-offs involved in incorporating resilience measures. ▪ Performance Degradation Under Stress: Monitors how system performance degrades under stress conditions and how quickly it can return to optimal levels. Only 6 (11%) of the 55 papers directly or indirectly address the crucial topic of resilience. This research is paramount in our field, as it provides valuable insights into the current resilience of energy systems. Paper [19] focuses on self-healing capabilities and contingency handling as key resilience features. It validates these through dynamic reconfiguration and fault recovery in grid-connected and islanded modes. However, it does not address economic trade-offs, cyber-physical resilience, or formal reliability metrics (LOLP, SAIDI). The resilience framework is primarily technical, emphasizing protection logic, inverter stability, and automated reconfiguration. Paper [32] addresses resilience through reliability metrics (PSuccess, LOutage), self-healing via agent negotiation and fault isolation, and contingency handling for multiple faults. Paper [53] addresses robustness (via contingency handling and VSM optimization) and operational resilience (through priority-based load shedding). However, it lacks an explicit discussion of traditional resilience metrics such as LOLP, SAIDI, MTTR, and cyber-physical indicators. This could limit the research's applicability in real-world settings. The focus remains on technical performance (detection accuracy, voltage stability) rather than comprehensive resilience frameworks. Paper [28] mentions "resilience" in the abstract and conclusion, linking the proposed strategy to improved grid resilience. The focus is on mitigating protection blindness via adaptive settings and fault-current limitation, thereby indirectly supporting resilience through improved fault management. Paper [36] focuses on the design of protection schemes and low-cost communication for fault detection in inverter-dominated microgrids. In contrast, it enhances operational reliability and indirectly supports resilience (e.g., fast fault isolation and communication redundancy). The resilience-related terms mentioned ("reliability," "self-healing") are qualitative and not quantified. Paper [45] addresses protection system optimization (adaptive relay coordination) to enhance reliability and speed. While it indirectly touches on robustness (via DG/topology variations) and operational adaptability, none of the resilience metrics are explicitly analyzed. E. Protection Strategies in Microgrid i. Novel Taxonomy of Strategies Researchers have investigated a wide range of protection strategies to address microgrids' unique challenges. This review addresses the question, " What are the most commonly used microgrid protection methods? How do they compare in performance, adaptability, and implementation complexity, and how do they improve fault detection and system resilience?", " What are the recent advances in intelligent microgrid protection systems?" by synthesizing insights from 55 papers ([6]-[60]). We implemented a bibliometric analysis to identify dominant protection strategies. Table VI presents a quantitative and thematic breakdown of microgrid protection strategies. International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075 (Online), Volume-14 Issue-12, November 2025 21 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org Table VI: Quantitative and Thematic Breakdown of Microgrid Protection Strategies Protection Strategies Frequency All Papers Addressing Protection Strategies Communication-Based Protection 11 out of 55 papers 20% [8]-[14]-[30]-[35]-[39]- [44]-[47]-[48]-[56] Differential Protection 6 out of 55 papers 11% [9]-[23]-[24]-[32] Inverter-Based Protection 7 out of 55 papers 13% [16]-[18]-[19]-[25]-[34]- [36]-[39] Adaptive Protection 14 out of 55 papers 25% [11]-[28]-[30]-[32]-[35]- [38]-[41]-[45]-[58] Directional Overcurrent Protection 5 out of 55 papers 9% [24]-[32]-[40] Distance (Impedance) Protection 4 out of 55 papers 7% [32]-[52]-[53]-[54] Overcurrent (OC) Protection 6 out of 55 papers 11% [17]-[21]-[37] Recloser and Fuse Protection 2 out of 55 papers 4% [17]-[29] Voltage-Based Protection 1 out of 55 papers 2% Frequency-Based Protection 2 out of 55 papers 4% [22] Intelligent Protection 7 out of 55 papers 13% [55] Travelling Wave-Based Protection 7 out of 55 papers 13% [18]-[19]-[30]-[49]-[54] Hybrid and Novel Schemes 5 out of 55 papers 9% [20]-[26]-[40]-[46] We classify microgrid protection strategies into six categories to provide a comprehensive understanding of how to tailor these strategies to address the dynamic challenges posed by microgrids, as discussed in the previous section. Table VII presents data from a taxonomy that provides a structured framework highlighting the evolution from conventional approaches to emerging, adaptive, and integrated solutions. This taxonomy plays a crucial role in this review paper by organizing existing research into clear, mutually exclusive categories and identifying gaps and opportunities for future work. Table VII: Microgrid Protection Categories Category Techniques Key Papers Conventional Protection Overcurrent (OC) Protection Distance (Impedance) Protection Differential Protection Directional Overcurrent Protection Recloser and Fuse Protection 19 out of 55 papers 35% Adaptive Protection Adaptive Protection Voltage-Based Protection 14 out of 55 papers 25% Communicatio n-Assisted Protection Communication-Based Protection 11 out of 55 papers 20% Inverter/DER-S pecific Protection Inverter-Based protection 7 out of 55 papers 13% Intelligent & Data-Driven Methods Intelligent Protection Frequency-Based Protection Travelling Wave-Based Protection 14 out of 55 papers 25% Hybrid/Integrat ed Systems Hybrid and Novel Schemes 5 out of 55 papers 9% The bibliometric analysis shows that researchers emphasise a diversified approach to protection strategies. Conventional protection techniques, including overcurrent relays, distance protection, differential protection, directional overcurrent protection, and recloser and fuse protection, appear in 35% (19 papers) of the literature, demonstrating continued reliance on established methods. Researchers also focus on adaptive and voltage-based protection, which accounts for 25% (14 papers), as they develop dynamic systems that swiftly respond to changing grid conditions. However, researchers increasingly emphasize communication-assisted protection in the literature, highlighting this approach in 20% (11 papers). This trend underscores the increasing importance of integrating real-time data exchange to improve system reliability. The literature also shows that inverter/DER-specific protection accounts for 13% (7 papers) and addresses the challenges associated with renewable energy integration. Meanwhile, intelligent and data-driven methods, including intelligent protection, frequency-based protection, and travelling-wave-based protection, account for 25% (14 papers) of the research, as investigators leverage innovative technologies to enhance resilience. Finally, researchers are exploring hybrid or integrated systems, as evidenced by 9% (5 papers) that present hybrid and novel schemes that blend traditional and innovative approaches to achieve robust protection. ii. Conventional Methods Traditional schemes developed for radial, centrally generated grids rely on fixed settings and simpler coordination methods. iii. Overcurrent Protection (OCP) Traditional overcurrent relays are widely used in conventional systems because they are cost-effective and straightforward. However, several studies highlight that OCP is less effective in microgrids. The low fault current levels, especially in islanded operation, and the bidirectional power flow often led to miscoordination and false tripping. While OCP has low implementation complexity, its performance and adaptability are limited in microgrids. The adaptability of overcurrent protection (OCP) in microgrids, particularly its ability to handle bidirectional power flows and low fault currents inherent to inverter-based resources (IBRs), is a key aspect of this protection. Implementing OCP in microgrids is a complex task that involves balancing cost-effectiveness with the need for adaptive settings to handle dynamic operating conditions. The limitations of fixed relay settings pose a significant challenge for OCP, underscoring the need for more advanced, adaptable solutions in microgrids. ▪ False tripping due to bidirectional flows [11] proposes voltage-restrained relays (51V) to mitigate this. ▪ Limited sensitivity to high-impedance faults, addressed in [12] using Mahalanobis distance-based detection. iv. Differential Protection Differential relaying compares current measurements at both ends of a protected zone, providing high sensitivity and selectivity even under bidirectional conditions. This method excels at accurately isolating faults but typically requires robust communication infrastructure and synchronised measurement units, which increase costs and implementation complexity. Despite these challenges, Systematic Review of Microgrids Protection: Challenges, Methods, and Solutions 28 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org ▪ Dual-setting directional overcurrent relays (DOCRs) integrate smoothly with existing infrastructure, capping retrofitting costs at 15–20% [33]. These solutions represent a pragmatic compromise, enhancing protection performance without overwhelming infrastructure demands. xxii.Reliability and Resilience Reliability describes a system's capacity for fault-free operation under normal conditions, while resilience quantifies its ability to recover from disruptions. Conventional protection methods deliver high reliability in static grids but falter in DER-dominated microgrids, where they cannot adapt to inherent power fluctuations [39]. Communication-assisted schemes rapidly isolate faults but risk prolonged downtime (up to 62%) during network outages. Adaptive and intelligent methods counter these limitations by embedding self-healing algorithms that sustain 95% uptime even during cyberattacks. Hybrid systems further enhance resilience; harmonic injection, for example, decouples protection functions from continuous communication dependency. DER-specific techniques, such as virtual impedance approaches, add robustness by emulating synchronous generator responses during faults, thereby improving system recovery. xxiii. Scalability and Interoperability Scalability measures a method's ability to scale to larger, more complex systems, while interoperability ensures compatibility with legacy infrastructure. Conventional methods often exhibit poor scalability in DER-rich grids due to their fixed configurations [33]. In contrast, intelligent methods demonstrate strong scalability potential; federated learning, though underexplored in this field, could decentralize AI training and enhance adaptability across distributed microgrids. Hybrid systems further boost interoperability through modular frameworks that enable incremental upgrades and seamless integration with legacy systems [25]. Emerging 5G wireless protocols, while not yet widely studied in this context, could also scale communication-assisted schemes, particularly benefiting rural microgrid applications. xxiv. Cybersecurity Considerations Cybersecurity is critical, as protection schemes must be robust against a range of cyber threats. Communication-assisted protection methods are particularly prone to spoofing and data injection attacks, with studies reporting up to 12% of false trips [9]. Intelligent methods are also vulnerable to adversarial machine learning attacks, posing significant risks in environments where data integrity is paramount. Conventional methods, while low risk from a cyber perspective due to their analogue nature, are not adaptable to DER fluctuations. Integrating quantum-resistant encryption and Moving Target Defence (MTD) techniques is critical to future-proof adaptive and communication-assisted systems, a unique insight highlighted by recent research. xxv. Cost and Economic Feasibility Cost-effectiveness and economic feasibility are essential when considering large-scale microgrid deployment. Conventional overcurrent protection is noted for its low initial and operational costs but offers limited returns in DER-rich grids. Adaptive protection methods incur moderate initial costs; however, their high ROI in industrial applications can justify the high maintenance cost associated with AI components. While offering ultra-fast fault isolation, communication-assisted systems incur high initial and operational costs due to network maintenance, making them better suited to urban environments. Hybrid systems strike a balance between moderate expenses, making them the most economically viable option for mixed-topology networks. Cost-benefit analyses in the Paper support these insights [20] and operational expenditure studies in Paper [26]. xxvi. Real-World Validation Field validation is crucial for assessing the practical viability of protection strategies. Studies show that conventional methods validate in approximately 70% of cases, yet they often underperform in DER scenarios [39]. Advanced techniques such as adaptive, intelligent, and hybrid systems have undergone real-world testing in only 9–15% of cases—for instance, successful trials in Inner Mongolia wind farms [35]. Hybrid systems have shown 100% selectivity in CIGRE benchmark field tests [25]. A significant gap persists in standardising cross-study comparisons, underscoring the need for unified validation frameworks. xxvii. Future Prospects and Recommendations Several future directions can help bridge the gap between laboratory innovation and widespread microgrid deployment. There is a pressing need to integrate sustainability metrics into protection strategies, linking relay coordination directly to carbon reduction and improved energy efficiency (e.g., reduced Energy Not Served, ENS). Modular upgrades, such as retrofitting legacy relays with plug-and-play AI and communication modules, offer a practical pathway for enhancing existing systems [33]. However, developing Explainable AI is not just another step but a critical one in building industry trust through transparent decision-making processes. Additionally, establishing IEEE/IEC guidelines for AI model benchmarking and hybrid system interoperability will be vital in standardising protection solutions. Finally, cybersecurity must evolve by adopting quantum-resistant encryption and advanced Moving Target Defence techniques to safeguard microgrid operations against emerging threats. xxviii. Improvements in Fault Detection and System Resilience ▪ Collectively, these recent advances contribute to the following improvements: Faster and More Accurate Fault Detection: AI/ML and advanced signal processing play pivotal roles in achieving quicker, more accurate fault detection. These technologies enable intelligent protection systems to detect faults in sub-cycle times (less than 16 ms), a significant improvement over conventional method. ▪ Enhanced Adaptability: Adaptive schemes and hybrid approaches are instrumental in maintaining high sensitivity and selectivity. These approaches allow protection settings to International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075 (Online), Volume-14 Issue-12, November 2025 29 Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) © Copyright: All rights reserved. Retrieval Number: 100.1/ijitee.A118215011225 DOI: 10.35940/ijitee.A1182.14121125 Journal Website: www.ijitee.org be dynamically adjusted to the microgrid's current operating mode and DER configuration, ensuring Enhanced Adaptability even under variable conditions. ▪ Increased System Resilience: The ability to seamlessly transition between grid-connected and islanded modes is a key factor in enhancing microgrids' resilience. This feature, along with communication-based and decentralized architectures and fault ride-through capabilities provided by intelligent relays, helps prevent cascading failures and minimize power outages. ▪ Robustness to Communication Failures: Several proposed schemes reduce dependency on high-bandwidth communication by employing local measurement techniques or redundant communication channels, ensuring continued protection even when communication links are compromised. IV. CONCLUSION This systematic review synthesises advancements, challenges, and gaps in microgrid protection, drawing on 55 contemporary studies. The review highlights that bidirectional power flows, variable fault currents, and dynamic topologies render conventional protection methods inadequate. It also emphasizes that while adaptive schemes, communication-assisted strategies, and AI-driven techniques show promise, they introduce complexity, cybersecurity vulnerabilities, and scalability limitations. The review suggests hybrid systems, combining traditional and intelligent methods, could offer a pragmatic balance, but interoperability and cost barriers remain. A. Research Gaps and Future Directions ▪ Resilience Metrics: Only 10% of studies address resilience holistically. Future work must integrate standardized metrics (SAIDI, MTTR) with DER-specific contingencies and cyber-physical interactions. ▪ Real-World Validation: With only 13% of studies validating findings experimentally, the need for field trials in diverse microgrid archetypes (DC, hybrid) becomes even more critical. These trials are essential to assess scalability and reliability in practical settings. ▪ Cybersecurity: Communication-assisted and AI methods remain vulnerable to spoofing and adversarial attacks. Quantum-resistant encryption and Moving Target Defence (MTD) frameworks require urgent exploration. ▪ Sustainability Integration: Protection strategies must align with decarbonization goals. Optimizing relay coordination to minimize Energy Not Served (ENS) and enhance grid efficiency can make significant strides in sustainability. ▪ Legacy System Upgrades: Modular retrofitting of electromechanical relays with AI modules and 5G communication could enable cost-effective transitions to adaptive protection. ▪ Standardization: The absence of unified guidelines for AI benchmarking, hybrid system interoperability, and DER-grid synchronization underscores the need for IEEE/IEC-led initiatives. B. Areas for Improvement ▪ Adaptive Thresholds: Develop dynamic relay settings using real-time DER forecasting to mitigate protection blinding. ▪ Explainable AI: Enhance trust in intelligent methods through transparent decision-making models. ▪ Cost-Benefit Frameworks: Evaluate the economic viability of hybrid systems in rural versus urban microgrids. ▪ Decentralized Architectures: Reduce communication dependency via federated learning and edge computing for distributed networks. 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Saeed Uz Zaman, “Convolutional Neural Network‐Based Intelligent Protection Strategy for Microgrids,” IET Generation Trans & Dist, vol. 14, no. 7, pp. 1177–1185, Apr. 2020, DOI: http://doi.org/10.1049/iet-gtd.2018.7049. 60. P. Singh and A. K. Pradhan, “A Local measurement-based protection technique for distribution system with photovoltaic plants,” IET Renewable Power Gen, vol. 14, no. 6, pp. 996–1003, Apr. 2020, DOI: http://doi.org/10.1049/iet-rpg.2019.0996. AUTHOR’S PROFILE Dr. Houssem Ben Aribia earned his Bachelor's and Master's Degrees in Electrical Engineering from the National School of Engineers of Sfax, Tunisia. In 2008, he completed his PhD in Electrical Engineering at the same institution. From 2009 to 2012, he served as a researcher and assistant professor in the Electrical Engineering Department at the National School of Engineers of Sfax, Tunisia. Since 2012, he has been an associate professor in the Electrical and Electronics Engineering Department at the College of Engineering and Computer Science, Jazan University, in Jazan, Saudi Arabia. Dr. Ferchichi Noureddine holds a Bachelor’s and Master’s degree in Electrical Engineering from Moguilev College of Engineering, Belarus. In 1998, he earned a PhD in Electrical Machines and Drives from Minsk State Polytechnic Academy, Belarus. From 2000 to 2007, he served as a researcher and assistant professor in the Electrical Engineering Department at the National High Engineering School of Tunis, Tunisia. Since 2008, he has been an associate professor in the Electrical and Electronics Engineering Department at the College of Engineering and Computer Science, Jazan University, Jazan, Saudi Arabia. Dr. Slim Abid earned his Bachelor’s Degree and Master’s Degree in Electrical Engineering from the National School of Engineers of Sfax, Tunisia. In 2009, I completed a PhD in Electrical Engineering from the National School of Engineers of Sfax. From 2010 to 2013, he was a researcher and assistant professor in the Electrical Engineering Department – National School of Engineers of Sfax, Tunisia, and from 2014 to the present, he has been an assistant professor in the Electrical and Electronics Engineering Department, College of Engineering and Computer Science – Jazan University, Jazan, Saudi Arabia. Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of the Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)/ journal and/or the editor(s). The Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP) and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.