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Review

A Review of Software and Hardware Tools for Microgrid Protection Testbeds

Department of Electrical and Computer Engineering, Laval University, Quebec City, QC G1V 0A6, Canada
*
Author to whom correspondence should be addressed.
Energies 2025, 18(16), 4417; https://doi.org/10.3390/en18164417
Submission received: 9 July 2025 / Revised: 23 July 2025 / Accepted: 14 August 2025 / Published: 19 August 2025
(This article belongs to the Special Issue Studies of Microgrids for Electrified Transportation)

Abstract

This paper provides a comprehensive review of the various software and hardware tools used in microgrid protection studies, including experimental setup requirements. While these tools have broad applications in power system research, this review specifically focuses on their utilization in microgrid protection, encompassing aspects, such as design, testing, simulation, analysis, and evaluation. The paper covers a wide range of tools, including protection simulation software and hardware components. Each category of tools is meticulously analyzed for its unique contribution to microgrid protection, highlighting their capabilities in different scenarios ranging from simulation features to hardware-in-the-loop (HIL) capabilities. This review aims to serve as a comprehensive guide for professionals and researchers in microgrid protection, providing insights into the selection and application of design and research tools based on their case studies.

1. Introduction

In the evolving landscape of microgrid technologies, the need for advanced protection strategies is paramount. The microgrid system situation is simulated and examined using a collection of hardware and software tools for power system analysis. The simulated output is used to analyze and determine the necessary protection setting for each protective device through a communication architecture [1,2,3,4]. This paper surveys the array of software and hardware tools used in microgrid protection studies. These tools, though applicable across various power systems, are particularly vital in addressing the unique challenges of microgrids in grid-connected or islanded mode [5].
Recent microgrid protection testbeds face significant scaling challenges, as distributed energy resource (DER) penetration levels exceed 50% of the total generation capacity, creating unprecedented dynamic operating conditions that strain conventional protection testing methodologies. High DER penetration introduces bidirectional power flows, voltage regulation complexities, and rapid power output fluctuations that require protection systems to operate across vastly expanded parameter spaces compared to traditional unidirectional power systems. Coordinating hardware components with diverse software stacks continues to be a complex challenge, especially when integrating legacy protection relays, which utilize different communication protocols, with modern digital simulation platforms that require precise microsecond-level timing. Cyber-physical security testbeds require simultaneous modeling of both power system dynamics and cybersecurity attack vectors, necessitating integration between power system simulation tools and cybersecurity platforms. Large-scale challenges extend to computational requirements, where modeling thousands of DER units with individual protection functions exceeds the real-time processing capabilities of current HIL platforms, leading researchers to explore distributed simulation architectures and approximate modeling techniques. Furthermore, the lack of standardized validation metrics across different testing platforms creates interoperability challenges, highlighting the urgent need for internationally recognized testing protocols that ensure consistent protection system performance evaluation regardless of the specific toolchain employed [6,7].
This survey primarily focuses on protection tools applicable to industrial-type microgrids within distribution and transmission network systems. Industrial microgrids present unique protection challenges due to their complexity, higher power ratings, and critical operational requirements, making them an important area for dedicated protection research. The protection tools and test methodologies discussed herein are applicable across various power ratings encountered in industrial applications, making them relevant for a wide range of industrial microgrids regardless of size. Additionally, residential and commercial microgrids involve different protection considerations, such as arc flash studies, which require specialized approaches. Furthermore, the test setups detailed in this paper enable a comprehensive evaluation of all critical equipment commonly deployed in industrial microgrids, including generators, transformers, inverter-based resources (IBRs), busbars, cables, and associated protection devices. This focused approach provides design engineers with specific guidance for industrial microgrid protection system development and testing. Our focus is on how they contribute to the design, testing, simulation, analysis, and evaluation of microgrid protection systems. The complexity of microgrid protection requires a toolkit that can adapt to varied scenarios and challenges. We explore several software tools like MATLAB, HYPERSIM, PSCAD, and EMTP, which are known for their simulation capabilities. In tandem, hardware tools, such as real-time simulators (OPAL-RT, RTDS), protective relays, data loggers, and cybersecurity measures, are discussed, emphasizing their crucial roles in practical implementations and testing environments.
Industrial microgrid protection presents unique challenges that distinguish it from residential or commercial applications, particularly in high-power environments exceeding 1 MW capacity [8]. Manufacturing facilities operating at multiple voltage levels (480 V, 4.16 kV, 13.8 kV) require sophisticated coordination schemes to ensure selective fault clearing while maintaining critical process continuity, with recent advances in metaheuristic optimization approaches showing promise for complex coordination problems [9]. For instance, in steel manufacturing plants, protection systems must coordinate with large motor starting currents that can reach 6–8 times nominal values, necessitating specialized tools like ETAP for time-current coordination studies. Data centers, representing a rapidly growing industrial microgrid application, demand sub-cycle fault detection and isolation capabilities to prevent cascading failures across redundant power paths [10], pushing the limits of conventional protection testing platforms and necessitating advanced HIL systems with microsecond-level time resolution, as these facilities increasingly adopt microgrid architectures to enhance power reliability and reduce operational costs. Additionally, the highly oscillating load characteristics in data centers necessitate proper protection system design to avoid maloperation and misoperation under fault conditions.
Furthermore, hardware and software are vital for real-time cyber-physical system (CPS) testbeds for cybersecurity [11,12,13,14,15]. This paper also examines the practical applications of these tools in microgrid protection studies. It highlights the significance of integrating both software and hardware components to create robust and reliable protection systems. The discussion includes how these tools are employed in scenarios like hardware prototyping, real-time evaluations, and vendor adaptability, providing insights into their versatility and effectiveness. Ultimately, this survey aims to serve as a comprehensive guide for researchers and professionals in microgrid protection
The paper categorizes the tools into two main types: software and hardware. Under software tools, we compare protection simulation software like MATLAB, HYPERSIM, PSCAD, and EMTP, which are essential for transient analysis, protection simulation, and design. We also cover protection testing software, such as Microwork Triangle Test Suite and Wireshark, which are crucial for communication analysis and trip testing. These software tools play a pivotal role in simulating and testing various microgrid protection scenarios. In the hardware category, our focus is on data loggers, digital signal processor (DSP)-based controllers, Field Programmable Gate Array (FPGA)-based controllers, routers, switches, network interface cards (NICs), and cybersecurity measures. These hardware components are vital for measuring, implementing protection algorithms, and testing microgrid protection systems.The application of these tools is examined across various scenarios, such as hardware prototyping, real-time evaluations, including Hardware-in-the-Loop (HIL) and Power Hardware-in-the-Loop (PHIL), and vendor adaptability studies [16,17,18]. These scenarios demonstrate the practical applications of the tools in diverse situations, from the development stage to real-world implementation and adaptation to different vendors’ systems [19]. Table 1 provides a concise summary of the various software and hardware tools essential for the design and testing of protection systems in microgrids. As an example, for implementing a vendor adaptability testbed, utilizing operational protection software, such as EasyPower, is necessary, while for HIL/PHIL tests, depending on the test setup, it is optional.
The integration of artificial intelligence and digital twin technologies is revolutionizing microgrid protection system testing and validation. AI-driven protection algorithms, implemented through integrated platforms and power system simulation tools, enable adaptive protection settings that respond dynamically to changing system conditions, such as varying renewable generation profiles. Machine learning models trained on historical fault data can predict protection system performance under unprecedented operating conditions, reducing the need for extensive physical testing. Digital Twin Technology (DTT) develops a highly detailed virtual model of microgrid systems that allows for real-time performance monitoring, predictive fault detection, and enhanced optimization of energy management strategies. It has the potential to give an efficient simulation model with the ability to handle the complexity, providing an exact virtual model of the physical entity of the power system [20,21,22].
AI-driven diagnostic platforms integrate machine learning algorithms directly into protection system testing workflows, automatically identifying optimal protection settings and predicting system vulnerabilities. These emerging tools democratize access to advanced protection testing capabilities, particularly benefiting research institutions and developing regions that may lack resources for extensive physical testing infrastructure [23]. Cloud-based real-time co-simulation environments represent a paradigm shift in microgrid protection testing, enabling distributed research collaboration and scalable computational resources. These platforms support real-time co-simulation, allowing simultaneous testing of protection coordination schemes across multiple time zones. Cloud-based real-time co-simulation allows for comprehensive testing of microgrid protection schemes in a realistic environment, including the interaction with physical components and communication networks. Co-simulation involves the integration of different simulation tools and models to represent various aspects of the microgrid, such as power systems, communication networks, and protection devices [24].

2. Software Tools

The simulation software category, prominently featuring tools like MATLAB and EMTP, stands out for its capabilities in transient analysis and protection simulation, as summarized in Figure 1. MATLAB, known for its user-friendly interface and extensive library, is particularly effective in algorithm development and testing. EMTP, on the other hand, offers a protection toolbox, making it invaluable for detailed protection analysis [25]. Another significant category is protection testing software, which includes tools like the Microwork Triangle Test Suite and Wireshark. These tools are indispensable for conducting detailed communication analysis and testing the functionality of protection schemes.
The Microwork Triangle Test Suite, for instance, provides a comprehensive environment for relay testing, including scenario simulation and report generation. Wireshark, a network protocol analyzer, is instrumental in examining and troubleshooting communication issues in microgrid protection systems.
The synergy of these software tools, each with its unique strengths, is essential for the holistic study and development of microgrid protection systems. They enable researchers and professionals to simulate various scenarios, test and refine protection algorithms, and ensure the overall reliability and efficiency of the protection schemes. This section of the paper delves deeper into each of these tools, exploring their functionalities, applications, and contributions to advancing microgrid protection studies. The classification of the protection software is depicted in Figure 1.

2.1. Simulation Software

Simulation software is essential for modeling and simulating electrical networks, enabling the prediction and analysis of system behavior under various fault conditions. It is crucial for understanding how systems react to disturbances, allowing for the development of appropriate protection strategies. Table 2 presents a detailed comparison of various simulation software tools used for protection in microgrids.
It features different aspects, such as analysis capability, COMTRADE file support, and protection coordination. Each software tool is evaluated across these parameters, offering insights into their strengths and suitability for specific tasks in microgrid protection studies. In the realm of microgrids, a focused and specialized approach to simulation and analysis is imperative due to their unique operational characteristics and challenges. Unlike traditional power systems, microgrids are dynamic, decentralized networks that incorporate a variety of IBRs. These elements necessitate a more intricate and precise study, especially in aspects like transient analysis and power electronic simulation [26]. Transient analysis is crucial in microgrids to understand the rapid, short-duration changes typically caused by switching operations or fault conditions. Similarly, power electronic simulation is essential due to the prevalent use of power electronic devices in IBR-dominated microgrids, which calls for detailed analysis to optimize performance and reliability [27,28].
Furthermore, the capability to simulate current transformer (CT) and power transformer saturation and provide direct real-time simulation links plays a vital role in the practical applications. CT and power transformer saturation simulations are key to accurately modeling the non-linear behavior of these components under fault conditions, which is critical in a microgrid due to its sensitivity to such disturbances. Direct real-time simulation links allow for the integration of physical hardware within the simulation environment, enabling HIL testing that is invaluable for real-world applicability and testing of microgrid control strategies.
Protection coordination, the availability of vendor relay models’ library, and the simulation of fast transients and traveling waves are equally important. These aspects ensure that protective devices operate correctly in unison, respecting the unique load-flow and fault scenarios in microgrids, and accurately represent high-frequency transient phenomena that could adversely affect sensitive microgrid components. Considering those specific characteristics of microgrid protection, a comparison and survey on simulation software tools used for protection in microgrids is presented in Table 2.
A key aspect highlighted in the table is the ability of these tools to support COMTRADE files, which is crucial for interoperability and standardization in data exchange.
The table also examines the capability of each tool to simulate current transformer and power transformer saturation, a vital feature for realistic modeling of protection systems. The application focus of each tool is identified, ranging from general power systems to specific areas like transient behavior, electromagnetic transients, and real-time simulation.
This differentiation helps in selecting the appropriate tool based on the specific requirements of a microgrid protection study. The table also explores the integration of these tools with real-time simulation systems, which is essential for HIL testing, providing a practical approach to protection system validation. Protection coordination capabilities are compared, highlighting how each software assists in configuring and setting protective devices for effective fault management.
The comparative analysis highlights notable limitations across all evaluated power system simulation platforms. While PSCAD and MATLAB/Simulink exhibit the strongest overall capabilities, including comprehensive transient analysis and power electronics simulation, they lack integrated protection coordination tools and depend on external solutions for real-time operation. ETAP and DIgSILENT PowerFactory excel in protection coordination but are limited in power electronics modeling, which is increasingly vital for modern grids with renewable energy integration. Specialized tools like Hypersim and PSS/CAPE demonstrate strengths in real-time simulation and protection analysis, respectively, but their scope is limited, lacking features such as COMTRADE support or transient analysis. Additionally, platform-specific usability challenges include EMTP’s need for extensive training and MATLAB/Simulink’s computational demands in large-scale simulations.
Table 2. Simulation software tools used for microgrid protection testbeds: a survey, and comparison.
Table 2. Simulation software tools used for microgrid protection testbeds: a survey, and comparison.
Feature/AspectETAP [29]PSCAD [30]DIgSILENT PowerFactory [31]EMTP [32]Hypersim [33]PSS/CAPE [34]Cyme [35]MATLAB/
Simulink [36]
Transient
Analysis
YesYesYesYesLimited (Real-time)NoLimited
(Distribution Focus)
Yes
Power Electronic SimulationNoYesNoYesYesNoNoYes
COMTRADE Files SupportYesYesYesYesNoYesYesNo (conversation required)
CT/Power
Transformer
Saturation
Simulation
NoYesYesYesYesYesYesYes
Direct Real-Time Simulation linkNoNo, using RTlab for OPALT-RTNoNo, using RTlab for OPALT-RTYesNoNoUsing RTlab for OPALT-RT or using Speedgoat or Typhoon
Protection Coordination ToolboxYesNoYesYesYesYesYesLimited (Possible with third-party Toolbox)
Vendor Relay Models’ LibraryYes
(complete)
Yes (possible with Fotran programming)Yes
(complete)
Limited (some SEL and ABB
relays)
-YesLimited (few vendors)No
Fast Transient and Travelling Wave-Yes-Yes-No-Yes
Microcontroller Programming Interface (for prototyping)NoNoNoNoLimited (applicable on OPAL FPGA board)NoNoYes (Via Embedded Coder License)
Modifiability of Relay Models--NoYes-No-No
Data Mining and AI Tools (for data analysis in the protection algorithm)Limited (Basic analytics)Limited (Basic analytics)Limited (Basic analytics)Limited (Basic analytics)Limited (Basic analytics)Limited (Basic analytics)Limited (Basic analytics)Yes (Data analytics, AI)
Popularity Based on Past 3 years IEEE Journal Papers (in the field of protection in microgrids)[37,38,39][40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56][57,58,59,60][55,61,62][63][64] [39,40,44,45,49,52,55,57,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80]
Significantly, Table 2 emphasizes the recent usage of these tools in academic and research papers over the last three years in the IEEE journals. This information is particularly valuable as it reflects the current trends and preferences in the field of microgrid protection research. It indicates the growing reliance on specific tools, underscoring their effectiveness and relevance in contemporary studies.
Analyzing the last row of Table 2 from your paper is presented in Figure 2, which indicates the recent usage of software tools in microgrid protection research. PSCAD has been extensively used in recent microgrid protection research, with over 17 papers utilizing it in the last three years.
This indicates its strong relevance and effectiveness in the field. MATLAB/Simulink also shows significant usage with around 25 references, highlighting its widespread application in recent research. DIgSILENT PowerFactory and EMTP have been referenced in a moderate number of papers, indicating their utility in certain areas of microgrid protection. Hypersim and PSS/CAPE have fewer references in the recent literature, suggesting more specialized or limited use cases in current research.
Cyme’s appearance in the literature is minimal, which might reflect its specific application scenarios or emerging status in microgrid protection research. The predominance of certain tools like PSCAD and MATLAB/Simulink in recent literature underscores their adaptability and comprehensive features that align well with current research needs in microgrid protection. It is important to recognize that some of the mentioned software collaborate in various aspects of protection studies. For instance, EMTP requires the MATLAB run-time version to plot coordination curves, such as overcurrent time curves. Additionally, MATLAB necessitates integration with RT-Lab to connect to OPAL-RT machines for real-time simulation.

2.2. Communication Testing Software

Smart substations rely on a multi-layered communication architecture governed by several interrelated standards. At its core, IEC 61850 defines three essential protocols: Manufacturing Message Specification (MMS) for client-server communications between IEDs and SCADA systems; Generic Object-Oriented Substation Event (GOOSE) for high-speed, publisher-subscriber event messaging; and Sampled Measured Values (SMV) for efficient exchange of measured data over the process bus. These communications are synchronized through IEEE 1588’s Precision Time Protocol (PTP), which achieves microsecond-level timing accuracy critical for phasor measurements.
For wide-area communications, substations employ either IEEE C37.118 or IEC 61850-90-5 for synchrophasor data exchange, while telecontrol functions leverage IEC 60870-5-104 or DNP3 (IEEE 1815) protocols. Legacy protection relay communications are maintained through IEC 60870-5-103, which provides standardized data exchange for protective relays and associated equipment [81,82,83,84,85]. Network reliability is ensured through IEC 62439’s redundancy protocols—notably Parallel Redundancy Protocol (PRP) and High-availability Seamless Redundancy (HSR)—which provide zero-delay recovery from network failures through packet duplication strategies [86,87].
Communication testing software analyzes and tests protection links, and communication protocols, ensuring reliable data exchange within the protection system. This is critical for the coordinated operation of protective devices and system monitoring. Microwork Triangle Test Suite is a famous software in this field that is used for testing network communications in protective systems [88]. Additionally, IED Monitor and Wireshark are network protocol analyzers, while IED Monitor focuses on intelligent electronic devices [89].
Industry practice and experimental evidence indicate that Wireshark, IEDexplorer and Microwork Triangle software set, including 61850 Test Suite Pro and Communication Protocol Test Harness, are among the most frequently employed communication software tools in this domain. Wireshark provides essential network protocol analysis and troubleshooting capabilities to monitor and verify data exchanges between protection devices. 61850 Test Suite Pro is a set of tools for IEC 61850, covering testing, troubleshooting, GOOSE analysis (GOOSE Tracker, GOOSE Publisher), SCL file validation (SCL Navigator), and IED simulation. Communication Protocol Test Harness performs conformance tests. IEDexplorer is an open-source tool for testing IEC 61850 devices [90,91]. It can inspect and write variable values, send commands, download files, and capture MMS and GOOSE packets.
However, implementing sophisticated communication systems in microgrids comes with inherent costs and complexities, robust communication is essential due to their decentralized nature and the integration of various renewable energy sources, which require precise coordination for stability. Communication software in the process of design, testing, and experimental evaluation ensures that the intricate web of data exchange between components is reliable and secure. This is vital not only in microgrid protection but also for managing DERs and load balancing.

2.3. Operational Protection Software

Operational protection software ensures proper coordination, configuration, and setting of protective devices for effective fault management. Table 3 presents a comprehensive comparison of operational software tools used in power system protection, with a focus that applies not only to microgrids but also to broader power system applications, specifically focusing on the software abilities of various manufacturer’s protection relays.
The table is structured to compare different manufacturers, like ABB, Siemens, GE Multilin, Schneider Electric, SEL (Schweitzer Engineering Labs), Eaton (Cooper Power Systems), and OMICRON. Each row in the table is dedicated to a specific manufacturer, listing their relevant protection relays and the accompanying operation software tools. For instance, ABB’s Relion series uses PCM600 and REF615 Connectivity Package, while Siemens’ SIPROTEC series utilizes DIGSI PAC World. These tools are primarily used for configuration, monitoring, and maintenance of the relays.
The table also details the specific software abilities of each manufacturer’s tools. These abilities include features like configuration management, monitoring, and setting of protective devices. Siemens’ DIGSI stands out with its advanced IEC 61850 engineering tools, offering comprehensive bay-oriented configuration capabilities that provide unparalleled integration flexibility.
ABB’s PCM600 demonstrates superior substation automation integration through its Plant Structure Navigator, enabling sophisticated hierarchical system management. GE’s EnerVista introduces the Symetrix Configuration tool, emphasizing simplified logic programming and advanced fault analysis capabilities. Schneider’s Easergy Studio distinguishes itself with customizable control pages and a user-friendly interface optimized for quick engineering tasks. SEL’s AcSELerato QuickSet offers highly specialized device optimization tools specifically tailored for SEL relay platforms, while providing advanced logic programming unique to their ecosystem. OMICRON Test Universe focuses on comprehensive testing and verification methodologies. Among its key features is the Test Plan, which allows users to create structured testing workflows tailored to specific projects. This functionality facilitates the organization of test sequences, ensuring that all necessary tests are executed in a systematic manner.
These specialized tools reflect the industry’s increasing [94] demand for flexible, manufacturer-specific solutions that balance technical complexity with intuitive engineering interfaces, ultimately driving more efficient protection system design and implementation. This information is critical for professionals choosing the right tools for specific microgrid protection applications. Importantly, the table provides a concise yet comprehensive comparison, enabling readers to quickly understand the unique features and capabilities of each manufacturer’s tools in the context of microgrid protection. This serves as a valuable resource for those involved in the design, implementation, and maintenance of microgrid protection systems.

2.4. SCADA Software

These tools integrate various hardware and software components of protection and SCADA systems, facilitating efficient and effective operation. This software is vital for creating a unified system from diverse components. For instance, ABB COM500 manages power system data for integrated system operations [115]. Additionally, Micro SCADA provides SCADA capabilities, essential for real-time monitoring and control, and Subnet which offers solutions for substation automation and integration. COPA-DATA Zenon is useful for HV substation automation and integration of protection and SCADA systems [116,117,118]. While these systems are pivotal in SCADA and protection integration in the design and test procedure, the financial and technical challenges associated with them are a common concern in the field, impacting microgrids and larger power grids similarly.

3. Hardware Tools

This section provides an overview of various hardware tools essential in power system protection in general with a specific focus on microgrid protection. It covers a range of devices and technologies, each playing a crucial role in ensuring the safety, reliability, and efficiency of power distribution systems.
The categories discussed include data loggers and measurement devices for recording electrical data, DSP/FPGA-based controllers for central processing and decision-making, and network infrastructure components like routers and switches. Cybersecurity measures such as firewalls are highlighted, emphasizing their importance in safeguarding against cyber threats. Protective relays, a key element in any protection scheme, are detailed along with real-time simulators for testing and evaluation. The text also discusses trip relays and circuit breakers for circuit protection, fault recorders for data analysis during faults, and protection test equipment for validating protective device settings. Additionally, it highlights PMUs for real-time monitoring and communication devices essential for data transmission across the grid. Each category includes specific examples of equipment and technologies, illustrating their application in the field of power system protection.

3.1. Data Logger and Measurement Devices

These devices are used to capture and record electrical data essential for monitoring system performance and post-event analysis in protection schemes. SEL-735 power quality and revenue meter records fault data for grid analysis [104]. Additionally, GE Multilin SR series are used for monitoring and diagnostics of electrical systems. Microgrids often experience more harmonics, primarily due to the widespread use of power electronic converters [119]. In the context of data logger and measurement devices in microgrid protection, this increased harmonic presence necessitates a few specific considerations in choosing a device with the proper features.

3.2. DSP/FPGA-Based Controllers

DSP/FPGA-based controllers are used to serve as the central processing unit for the protection system, implementing protection algorithms, handling data, and making critical decisions. They are essential for the intelligent operation of modern protection systems. Two famous examples that have been used for protection purposes are Raspberry Pi, which is commonly used for custom control applications, and Texas Instruments DSPs, which offer a range of DSPs renowned for their high performance, speed, and reliability, making them ideal for data-intensive applications in industrial settings [120,121]. Figure 3 and Figure 4 illustrate a protection scheme used in a microgrid study, employing Texas Instruments DSPs for real-time simulation purposes.
While DSPs like Texas Instruments’ series are optimized for high-speed, data-heavy processing with deterministic timing, FPGAs offer a complementary approach with enhanced customization and parallel processing capabilities. The Xilinx Zynq UltraScale + MPSoC, for instance, combines ARM processors with FPGA fabric, enabling the implementation of complex control algorithms in hardware for real-time applications. Similarly, Intel’s Cyclone and Stratix FPGA families provide high-speed, deterministic processing suited for control tasks requiring tailored hardware architectures. Smaller devices such as Lattice MachXO and ECP5 are ideal for control and interface functions with power and size constraints. Unlike traditional DSPs, FPGAs excel in parallel processing and deterministic timing, making them highly suitable for complex, high-performance, low-latency applications where hardware customization is critical. Although not direct substitutes, FPGAs can be configured to replicate many of the control functions of DSP microcontrollers, offering versatile solutions tailored to specific system needs [123,124,125,126].
Ref. [122] demonstrates an experimental setup showcasing the application of the tools introduced in our research. The experimental validation of the method proposed in [122] was conducted using a HIL testbed. The controller was implemented on a C2000 Texas Instrument Launchpad featuring the F28379D microprocessor, while the grid model, power line, and DFIG-based wind turbine were simulated in real-time using a Speedgoat real-time simulator (RTS). Figure 3 illustrates the communication architecture between different components of the experimental testbed, showing the data exchange pathways between the microprocessor and the real-time simulator. Figure 4 presents the physical implementation of the experimental setup, demonstrating the hardware configuration used for validating the proposed adaptive auto-reclosing method. The HIL setup forms a closed-loop system where signals are continuously exchanged between the microprocessor controller and the real-time simulator, enabling comprehensive testing of various fault scenarios under controlled laboratory conditions.

3.3. Routers, Switches, or Network Interface Cards (NICs)

This equipment provides the necessary network infrastructure for communication within the protection system. They are crucial for ensuring that different components of the system can communicate effectively and reliably. The important notice about them is that the protection standard support must be taken into consideration while utilizing them. As an example, Cisco IE 3000 Switches or IE3K are a series of switches that support IEC 61850 and can be used for protection purposes [127]. In the microgrids, some other data networks may be interested in connecting to those switches, if the grid codes allow. In that case, the protection routers, switches, or NICs should be able to support them in performing a comprehensive protection study in the presence of other data flowing through the communication infrastructure.

3.4. Cybersecurity Measures (e.g., Firewalls)

These devices are used to protect the integrity and reliability of the protection system from cyber threats. As protection systems become more interconnected, cybersecurity is becoming increasingly crucial.
For firewalls, like other network devices, supporting protection-related standards are necessary. Cisco Firewall ISA3000 can be mentioned as a sample of an IEC 61850-support devices [128]. In microgrids with high penetration of other dataflows, like electrical market data, and by having other controls, including DER controllers, consideration of the cybersecurity measures is crucial.

3.5. Protective Relays

Modern microgrids rely on advanced protection relays to maintain stability and safety in complex power distribution scenarios. For protection studies, commercial protective relays are utilized to monitor the electrical system and trigger circuit breakers to isolate faults. They are a cornerstone of any protection scheme, providing the first line of defense against electrical faults. These relays incorporate multiple protection functions to address unique microgrid challenges, such as bidirectional power flow and islanding transitions.
Table 4. Major protection relays for microgrid applications.
Table 4. Major protection relays for microgrid applications.
ManufacturerPopular SeriesKey CharacteristicsProtection Function CapabilitiesCommunication ProtocolsCybersecurity
ABB [129,130,131,132]Relion series
(REF615, REF620, REF630)
High accuracy measurement (0.5%)-Fast operation time (<20 ms)-Wide operating temperature range (−40 °C to +70 °C)-Adaptive protection capabilityOvercurrent (50/51)
Directional overcurrent (67/67N)
Earth fault (50N/51N)
Voltage (27/59)
Frequency (81U/O/R)
Synchro-check (25)
IEC 61850-8-1 (MMS/GOOSE)
IEC 60870-5-103
DNP3.0 (L2 authenticated)
Modbus TCP (port 502)
IEC 62351, Secure boot
REG series
(REG615, REG630)
Generator protection focus-5 kHz sampling rate-Advanced harmonic analysis Multiple setting groupsStator earth fault (64S)-Loss of excitation (40)-Reverse power (32)-Power factor monitoring-Voltage/frequency (24/81)-Synchronization (25)IEC 61850-9-2LE (SV)
DNP3
Modbus RTU (RS485)
Firmware signing
Siemens [133,134,135]SIPROTEC 5 series (7SJ85, 7UT85, 7SA87)Modular design-32 samples/cycle sampling rate-Programmable logic-Dual-core processor architectureOvercurrent (50/51)
Directional overcurrent (67/67N)
Distance protection (21)
Differential (87)
Voltage (27/59)-Frequency (81U/O/R)
Load shedding (81LSH)
IEC 61850 Ed.2
Profinet IRT
DNP3 over TCP
Modbus RTU
MACsec, AAA model
SIPROTEC 4 series (7SJ61, 7SJ62)8 kHz sampling rate-Flexible I/O configuration-−25 °C to +55 °C temperature range-0.2% measurement accuracyOvercurrent (50/51)-Directional overcurrent (67/67N)-Earth fault (50N/51N)-Voltage (27/59)-Frequency (81U/O/R)-Auto-reclosure (79)IEC 61850
IEC 60870-5-103
Profibus DP
Role-based access
GE(General Electric) [136,137]Multilin 8 Series
(850, 845, 869)
64 samples/cycle sampling rate-Advanced fault waveform capture-1 ms time stamping accuracy-Redundant power supply optionOvercurrent (50/51)-Directional overcurrent (67/67N)-Voltage (27/59)-Frequency (81U/O/R)-Differential (87)-Power swing detection-Islanding detectionIEC 61850 Ed.2.1
DNP3.0 (secure)
IEC 60870-5-104
FIPS 140-2
Multilin UR Series
(F60, T60, L90)
128 samples/cycle sampling rate-Programmable FlexLogic-Integrated synchrophasor-1 µs time accuracy with PTPDistance (21)-Line differential (87L)-Current differential (87T)-Phase comparison-Rate-of-change of frequency (81R)-Out-of-step protection-Power quality monitoringIEC 61850
DNP3
Modbus
IEEE 1588
IEC 60870-5-104
TLS 1.2
Schneider Electric [138]MiCOM P series
(P14x, P24x, P34x)
48 samples/cycle-10 ns resolution time tagging-0.5% measurement accuracy-Multiple setting groupsOvercurrent (50/51)-Directional overcurrent (67/67N)-Earth fault (50N/51N)-Voltage (27/59)-Frequency (81U/O/R)-Frequency-based load sheddingIEC 61850 (GOOSE)
DNP3 LAN/WAN
Modbus TCP (TLS 1.2)
IPsec VPN
Easergy P5 series128 samples/cycle-0.1% measurement accuracy-Edge computing capability-Support for process busOvercurrent (50/51)-Directional overcurrent (67/67N)-Voltage (27/59)-Frequency (81U/O/R)-Adaptive protection-Advanced islanding detection-Low-frequency and V/F protectionIEC 61850 Ed. 2
DNP3
Modbus-HTTPS
NERC CIP compliant
SEL [139,140]SEL-700 series
(SEL-751, SEL-787, SEL-710)
8 kHz sampling rate-±0.1% frequency tracking-−40 °C to +85 °C temperature range-Capacitive voltage measurementOvercurrent (50/51)-Directional overcurrent (67/67N)-High-impedance fault detection-Load encroachment-Synchro-check (25)-Motor protectionIEC 61850
DNP3
Modbus
SEL protocols
Config signing
SEL-400 series
(SEL-421, SEL-411L, SEL-487E)
Time-domain protection-Dedicated traveling-wave fault location (TFL)-1 MHz sampling-Sub-cycle operationDistance (21)-Line differential (87L)-Transformer differential (87T)-Synchrophasor-based protection-Advanced power swing detection-IEC 61850
DNP3
IEEE C37.118
IEEE 1686-2013
ALSTOM/GE Grid [141]MiCOM Agile P40 seriesDual-core processor-48 samples/cycle (fundamental)-0.2% measurement accuracy-Multiple setting groupsOvercurrent (50/51)-Directional overcurrent (67/67N)-Earth fault (50N/51N)-Loss of mains detection-Rate-of-change of frequency (81R)-Vector shift-Directional earth fault (67N)IEC 61850
DNP3
Modbus
IEC 60870-5-103
Secure LDAP
MiCOM Agile P60 seriesDistributed generation protection-96 samples/cycle-Adaptive setting groups-Advanced fault recordingDirectional overcurrent (67/67N)-Voltage (27/59)-Frequency (81U/O/R) Directional power (32R/F)-Phase discontinuity monitoring-Generator protectionIEC 61850
DNP3
Courier
Modbus
Hardware security module
Table 4 presents a detailed comparison of various protection relays used in microgrids. It features different aspects such as protection function capabilities, communication protocols, and cybersecurity. Key protection elements include overcurrent (50/51) and directional overcurrent (67/67N) for selective fault isolation, voltage/frequency protection (27/59, 81U/O/R) to prevent instability during grid disturbances, and islanding detection (81R, vector shift) for seamless transition between grid-connected and standalone modes. Manufacturers like ABB, Siemens, and SEL optimize these functions with high-speed operation (<20 ms), adaptive setting groups, and sensitive fault detection (e.g., high-impedance faults at 0.5–4 A). Such capabilities ensure reliable operation in microgrids with renewable generation, energy storage, and variable loads. For example, the ABB RELION Series, particularly models like REL670 and REL650 are widely used for line protection, offering sophisticated features for fault detection and isolation [142]. Additionally, Siemens SIPROTEC 5 Series: The Siemens SIPROTEC 5 series, with models like 7UT85 and 7SJ85 are suitable for various applications, from transformer protection to distance protection, and are valued for their high accuracy and dependability [143]. Some protective relays are produced to address some of the challenges of the microgrids. For protection studies in the microgrids, especially the adaptability tests, it is recommended to keep those relays in the loop.
Regarding communication protocols, relays utilize standardized methods to coordinate protection schemes and real-time control. IEC 61850, particularly GOOSE and Sampled Values (SV), is essential for high-speed peer-to-peer messaging in substation automation. DNP3 and Modbus facilitate data exchange with SCADA systems. Siemens’ SIPROTEC 5 series support Profinet IRT for deterministic industrial networking, while SEL relays employ Mirrored Bits technology for signaling. Legacy protocols like IEC 60870-5-103 remain relevant to ensure backward compatibility. These protocols enable functionalities, such as centralized fault analysis, adaptive protection adjustments, and synchronization with PMUs, forming the backbone of resilient microgrid communication architectures [85].

3.6. Real-Time Simulators

They enable dynamic testing and evaluation of protection strategies under real-time conditions. They are essential for validating protection schemes and ensuring they perform as expected in real-world scenarios. For instance, the OPAL-RT Real-Time Simulator provides dynamic simulation capabilities for power systems [11,144]. RT-Lab software is needed to link it with MATLAB/Simulink. A protection setup in a microgrid study that utilizes OPAL-RT for real-time simulations is depicted in Figure 5, Figure 6 and Figure 7 [23,145]. This research employs a comprehensive real-time simulation framework to validate the proposed protection scheme. The experimental testbed integrates OPAL-RT real-time simulators with RT-Lab and MATLAB to create a hardware-in-loop environment. IEDexplorer automation software facilitates GOOSE message exchange between overcurrent relays. The protection algorithm was implemented using Simulink and RT-Lab on an OPAL-RT machine, while MATLAB modeled the microgrid’s operational statuses on a desktop computer. Network current data was transmitted via GOOSE messaging from the first OPAL-RT machine to the protection relay (simulated on a second OPAL-RT machine). Any relay operations, such as trip commands, were communicated back through GOOSE messaging to adjust the microgrid status accordingly.
Speedgoat is another real-time machine used in the literature for microgrid protection studies [146]. Speedgoat does not need interconnections and can connect directly to MATLAB/Simulink [122]. Figure 2 and Figure 3 illustrates a protection scheme used in a microgrid study, employing SpeedGoat for real-time simulation purposes. Additionally, the RTDS Technologies simulator is valued for its ability to simulate very detailed and fast transient, making it a preferred choice for research and development in power system protection generally, and specifically in microgrids [147].
The methodology employed for connecting the power amplifier to the RTS is a critical aspect of the PHIL setup and can significantly influence the accuracy of the protection studies. The optimal connection strategy is application dependent. For instance, when investigating travelling wave-based protection schemes, the power amplifier must be capable of generating and accurately reproducing high-frequency transient signals in the nanosecond range, mirroring the output characteristics of a Capacitor Voltage Transformer (CVT) in a real substation. Furthermore, given the high-frequency nature of these signals, careful consideration must be given to the physical connection between the power amplifier and the hardware under test, including the use of shielded cables and appropriate grounding techniques, to minimize electromagnetic interference and ensure the integrity of the injected signals, similar to the shielded wiring employed between CVTs and relays in actual substations.

3.7. Trip Relays and Circuit Breakers

They can be used in experimental setups that are put together for protection studies in PHIL testbeds. Some specific circuit breakers are designed for the distribution grids and microgrids. Having them in the PHIL tests can be beneficial not only for vendor adoptability tests but also for trip timing and transient analysis in protection testbeds. One of them is ABB SACE Emax 2, an air circuit breaker that delivers optimized performance. Additionally, Schneider Electric’s Masterpact Series, known for its performance in power distribution and microgrids [148,149]. While the trip relays are not widely used in microgrids, their behavior is important in the trip timing in protection studies.

3.8. Protection Test Equipment

These devices can be used to test and validate the settings of protective devices by injecting the recorded waveforms as the relay’s input. They have been used for protection operation procedures for routine tests for maintenance purposes as well as for protection research for experimental testbeds. A famous one to mention is the Omicron CMC series, which are the test sets for protective relays [109]. Those are the general devices that can be used for power system protection, including microgrids.

3.9. PMUs (Phasor Measurement Units)

PMUs are critical for real-time monitoring of power systems, providing high-fidelity data on electrical parameters like voltage and current phasors. This information is crucial for grid stability analysis, fault detection, and enhancing overall system reliability. For instance, the SEL-421 protection system features integrated phasor measurement capabilities for microgrid stability analysis [139]. Additionally, GE Multilin PMUs are known for their precision and reliability in phasor measurement and are used extensively for microgrid analysis [150].

3.10. Fiber Optic Communication Devices

In transmission system protection, communication devices, like PDH (Plesiochronous Digital Hierarchy), SDH (Synchronous Digital Hierarchy), and fiber optic connections, are crucial for the high-speed and reliable transmission of data across the grid. These technologies are essential for the coordination of protection systems, especially over large distances and in complex network configurations. However, in microgrids, considering the expenses, utilizing active fiber devices, like PDH\SDH, is not common because the short distances in microgrids implementing the fiber optic network are affordable in some cases. As an example of the commonly used fiber optic active devices, the Huawei OptiX RTN series offers a range of PDH/SDH microwave transmission systems, suitable for robust and reliable communication in power systems [151]. Additionally, Nokia SDH/MSTP systems are known for their advanced SDH and multi-service transport platforms, providing secure and high-capacity communication solutions [152].

3.11. Emulators

Emulators for renewable energy sources like wind farms and solar photovoltaic (PV) systems are sophisticated test instruments designed to simulate the complex and dynamic electrical characteristics of renewable energy generation. These sophisticated devices, such as those developed by Chroma, ITech, and other leading manufacturers, can precisely generate the non-linear current-voltage (I–V) curves that simulate PV panel performance, wind turbines, and other renewable energy sources under diverse environmental and operational conditions. These instruments are capable of modeling complex scenarios, including variable solar irradiance, temperature fluctuations, partial shading, and grid interconnection challenges, enabling engineers to conduct comprehensive testing of power conversion systems, inverters, and energy storage technologies [153].
Wind farm emulators can generate dynamic and stochastic power curves that mimic the intermittent and variable output of wind turbines, including factors like wind speed variations, turbine efficiency, and power curve characteristics. These tools are essential for protection studies of renewable resources its interference with other protection functions in the field under diverse and challenging operational conditions.
The selection of appropriate internal modeling approaches (component-level vs. dynamic equivalent) should be guided by the specific protection phenomena being investigated, with component-level models typically necessary when studying protection schemes sensitive to individual converter behaviors, while dynamic equivalent models are often sufficient for system-level protection coordination studies.

3.12. PCS Test Equipment

The Power Conversion System (PCS) is examined to ensure grid safety and reliability, with several critical protection characteristics. Low Voltage Ride Through (LVRT) testing validates the system’s ability to continue operating during power system disturbances. Specifically checking the performance when grid voltage drops to various levels without switching to islanded mode is crucial. Anti-islanding protection tests are important, requiring the PCS to disconnect from the grid during potential islanding scenarios or smoothly transition to islanded mode while generating stable AC voltage. Additionally, protection characteristic tests evaluate the PCS’s response to various grid conditions, such as overload scenarios in both grid and islanded modes. These tests typically utilize a comprehensive test setup including a grid simulator, battery simulator, load banks, and precision measuring instruments [154,155]. Figure 8 illustrates the components and connections involved in a solar and battery energy storage system (BESS) power conversion system. The diagram demonstrates how these various components work together to manage and convert the solar power generated.

4. Conclusions

In conclusion, this paper has provided a comprehensive review of both software and hardware tools utilized in microgrid protection studies, including the experimental setup requirements for protection design, testing, and evaluation. It has highlighted the critical role these tools play in the design, simulation, analysis, and testing of protection systems. The detailed examination of simulation software, testing tools, and hardware components underlines their individual and collective importance in enhancing the reliability and efficiency of microgrids. The testbed scenarios and applications discussed illustrate the practicality and adaptability of these tools in real-world research needs.

Author Contributions

Conceptualization, S.S., M.A. and I.K.; methodology, S.S. and M.A.; validation, M.A., S.S., I.K. and H.G.; investigation, M.A., S.S., I.K. and H.G.; data curation, S.S., M.A. and I.K.; writing—original draft preparation, S.S. and M.A.; writing—review and editing, M.A. and S.S.; visualization, S.S., M.A. and H.G.; supervision, S.S. and I.K.; project administration, I.K.; funding acquisition, I.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Canada National Sciences and Engineering Research Council through the Laval University under Grant No: ALLRP567550-21.

Data Availability Statement

The data generated and analyzed on this paper are available from the corresponding author on request.

Conflicts of Interest

Dr. Sanati currently collaborates with GE Vernova. The remaining authors have no conflicts of interest to report.

Nomenclature

Power Systems and Communications
BESSBattery Energy Storage System
DERDistributed Energy Resources
DFIGDoubly-Fed Induction Generator
DSPDigital Signal Processor
FFPGAField Programmable Gate Array
IBRInverter-Based Resources
IEDIntelligent Electronic Device
NICNetwork Interface Card
PCSPower Conversion System
PMUPhasor Measurement Unit
RTNRadio Transmission Network
RTSReal-Time Simulator
RTDSReal Time Digital Simulator
COMTRADECommon Format for Transient Data Exchange
CPSCyber-Physical System
HILHardware-in-the-Loop
HSRHigh-Availability Seamless Redundancy
LVRTLow Voltage Ride Through
PHILPower Hardware-in-the-Loop
PRPParallel Redundancy Protocol
PTPPrecision Time Protocol
SCADASupervisory Control and Data Acquisition
SCLSubstation Configuration Language
SCDSubstation Configuration Description
TFLTraveling-Wave Fault Location
Communication Protocols in Power Systems
DNP3Distributed Network Protocol 3
GOOSEGeneric Object-Oriented Substation Event
MMSManufacturing Message Specification
SMVSampled Measured Values
SVSampled Values
IEC Standards for Communication (International Electrotechnical Commission)
IEC 60870-5-103Telecontrol equipment and systems-Companion standard for basic telecontrol tasks
IEC 60870-5-104Network access for IEC 60870-5-101 using standard transport profiles
IEC 61850Communication protocols used in substation automation
IEC 61850-8-1Specific Communication Service Mapping (SCSM)-Mappings to MMS
IEC 61850-9-2LEProcess bus communication profile for transmission of sampled values
IEC 61850-90-5Use of IEC 61850 to transmit synchrophasor information according to IEEE C37.118
IEC 62351Power systems management and associated information exchange-Data and communications security
IEC 62439Industrial communication networks-High availability automation networks
IEC 60870-5-103Telecontrol equipment and systems-Companion standard for basic telecontrol tasks
IEEE Standards for Communication (Institute of Electrical and Electronics Engineers)
IEEE 1588Precision Time Protocol (PTP)
IEEE 1686-2013Standard for Intelligent Electronic Devices Cyber Security Capabilities
IEEE 1815Standard for Electric Power Systems Communications-Distributed Network Protocol (DNP3)
IEEE C37.118Standard for Synchrophasor Measurements for Power Systems
General Communication Protocols
PDHPlesiochronous Digital Hierarchy
SDHSynchronous Digital Hierarchy
TCPTransmission Control Protocol
MSTPMulti-Service Transport Platform

References

  1. Vegunta, S.C.; Higginson, M.J.; Kenarangui, Y.E.; Li, G.T.; Zabel, D.W.; Tasdighi, M.; Shadman, A. AC Microgrid Protection System Design Challenges—A Practical Experience. Energies 2021, 14, 2016. [Google Scholar] [CrossRef]
  2. PSRCC. Microgrid Protection Systems, PES-TR71; IEEE Power & Energy Society (PES) Power System Relaying and Control Committee (PSRCC), Working Group C30: New York, NY, USA, 2019; pp. 1–58. [Google Scholar]
  3. Kim, J.-S.; So, S.M.; Kim, J.-T.; Cho, J.-W.; Park, H.-J.; Jufri, F.H.; Jung, J. Microgrids platform: A design and implementation of common platform for seamless microgrids operation. Electr. Power Syst. Res. 2019, 167, 21–38. [Google Scholar] [CrossRef]
  4. Hemmati, M.; Palahalli, M.H.; Gajani, G.S.; Gruosso, G. Impact and Vulnerability Analysis of IEC61850 in Smartgrids Using Multiple HIL Real-Time Testbeds. IEEE Access 2022, 10, 103275–103285. [Google Scholar] [CrossRef]
  5. Paspatis, A.; Kontou, A.; Kotsampopoulos, P.; Lagos, D.; Vassilakis, A.; Hatziargyriou, N. Advanced hardware-in-the-loop testing chain for investigating interactions between smart grid components during transients. Electr. Power Syst. Res. 2024, 228, 109990. [Google Scholar] [CrossRef]
  6. Kumar, K.; Kumar, P.; Kar, S. A review of microgrid protection for addressing challenges and solutions. Renew. Energy Focus 2024, 49, 100572. [Google Scholar] [CrossRef]
  7. Alasali, F.; El-Naily, N.; Holderbaum, W.; Mustafa, H.Y.; AlMajali, A.; Itradat, A. A hybrid physical and co-simulation modern adaptive power protection testbed for testing the resilience of smart grids under cyber-physical threats. Energy Rep. 2024, 12, 1655–1672. [Google Scholar] [CrossRef]
  8. Alasali, F.; Saad, S.M.; Saidi, A.S.; Itradat, A.; Holderbaum, W.; El-Naily, N.; Elkuwafi, F.F. Powering up microgrids: A comprehensive review of innovative and intelligent protection approaches for enhanced reliability. Energy Rep. 2023, 10, 1899–1924. [Google Scholar] [CrossRef]
  9. Santos-Ramos, J.E.; Saldarriaga-Zuluaga, S.D.; López-Lezama, J.M.; Muñoz-Galeano, N.; Villa-Acevedo, W.M. Microgrid Protection Coordination Considering Clustering and Metaheuristic Optimization. Energies 2024, 17, 210. [Google Scholar] [CrossRef]
  10. Sheehan, S.; Rakow, A. Evolving a Data Center Into a Microgrid: Industry perspectives and lessons learned. IEEE Electrif. Mag. 2023, 11, 16–25. [Google Scholar] [CrossRef]
  11. Poudel, S.; Ni, Z.; Malla, N. Real-time cyber physical system testbed for power system security and control. Int. J. Electr. Power Energy Syst. 2017, 90, 124–133. [Google Scholar] [CrossRef]
  12. Wang, Z.; Qi, D.; Mei, J.; Li, Z.; Wan, K.; Zhang, J. Real-time controller hardware-in-the-loop co-simulation testbed for cooperative control strategy for cyber-physical power system. Glob. Energy Interconnect. 2021, 4, 214–224. [Google Scholar] [CrossRef]
  13. Zamzam, A.S.; Wang, J. Hierarchical Data-Driven Protection for Microgrids with 100% Renewables. In Proceedings of the 2023 IEEE Energy Conversion Congress and Exposition (ECCE), Nashville, TN, USA, 29 October–2 November 2023; pp. 1506–1513. [Google Scholar]
  14. Riquelme-Dominguez, J.M.; Gonzalez-Longatt, F.; Melo, A.F.S.; Rueda, J.L.; Palensky, P. Cyber-Physical Testbed Co-Simulation Real-Time: Normal and Abnormal System Frequency Response. IEEE Trans. Ind. Appl. 2024, 60, 2643–2652. [Google Scholar] [CrossRef]
  15. Pham, L.N.H.; Wagle, R.; Tricarico, G.; Melo, A.F.S.; Rosero-Morillo, V.; Shukla, A.; Gonzalez-Longatt, F. Real-Time Cyber-Physical Power System Testbed for Optimal Power Flow Study Using Co-Simulation Framework. IEEE Access 2024, 12, 150914–150929. [Google Scholar] [CrossRef]
  16. Wang, J.; Pratt, A.; Prabakar, K.; Miller, B.; Symko-Davies, M. Development of an integrated platform for hardware-in-the-loop evaluation of microgrids prior to site commissioning. Appl. Energy 2021, 290, 116755. [Google Scholar] [CrossRef]
  17. Jayawardana, I.; Ho, C.N.M.; Zhang, Y. A Comprehensive Study and Validation of a Power-HIL Testbed for Evaluating Grid-Connected EV Chargers. IEEE J. Emerg. Sel. Top. Power Electron. 2022, 10, 2395–2410. [Google Scholar] [CrossRef]
  18. Sancio, R.; Jung, J.H.; Pugliese, S.; Langwasser, M.; Liserre, M. Advanced Zero-Sequence Current Suppression in P-HIL Testbed With Integration of Feed-Forward Compensation and LADRC. IEEE Access 2024, 12, 85400–85410. [Google Scholar] [CrossRef]
  19. Hagan, T.; Senaratne, D.; Meier, R.; Cotilla-Sanchez, E.; Kim, J. Implementing Power System Protection Algorithms in a Digital Hardware-in-the-Loop Substation. IEEE Open Access J. Power Energy 2023, 10, 270–282. [Google Scholar] [CrossRef]
  20. Sahoo, B.; Panda, S.; Rout, P.K.; Bajaj, M.; Blazek, V. Digital twin enabled smart microgrid system for complete automation: An overview. Results Eng. 2025, 25, 104010. [Google Scholar] [CrossRef]
  21. Bassey, K.; Opoku-Boateng, J.; Antwi, B.; Ntiakoh, A.; Juliet, A. Digital twin technology for renewable energy microgrids. Eng. Sci. Technol. J. 2024, 5, 2248–2272. [Google Scholar] [CrossRef]
  22. Kumari, N.; Sharma, A.; Tran, B.; Chilamkurti, N.; Alahakoon, D. A Comprehensive Review of Digital Twin Technology for Grid-Connected Microgrid Systems: State of the Art, Potential and Challenges Faced. Energies 2023, 16, 5525. [Google Scholar] [CrossRef]
  23. Sanati, S.; Mosayebi, A.; Kamwa, I. Advanced Rapid Directional Over-Current Protection for DC Microgrids Using K-Means Clustering. IEEE Trans. Power Deliv. 2024, 39, 1088–1099. [Google Scholar] [CrossRef]
  24. Ali, O.; Mohammed, O.A. Real-Time Co-Simulation Implementation for Voltage and Frequency Regulation in Standalone AC Microgrid with Communication Network Performance Analysis across Traffic Variations. Energies 2024, 17, 4872. [Google Scholar] [CrossRef]
  25. Prabakar, K. Chapter 8—Testing and evaluation methods for protection systems. In Power System Protection in Future Smart Grids; Ustun, T.S., Ed.; Academic Press: New York, NY, USA, 2024; pp. 167–188. [Google Scholar]
  26. Arabahmadi, M.; Khaligh, H.; Moghani, A.; Mosallanejad, A. Design and Modelling of a Modified Controller for D-STATCOM Considering Parametric Uncertainties and Unmodeled Dynamics. In Proceedings of the 2024 32nd International Conference on Electrical Engineering (ICEE), Tehran, Iran, 2024, 14–16 May 2024; pp. 1–6. [Google Scholar]
  27. Alvarez, G.; Doss, P.; Korede, I.; Brookins, L.; Grimes, J.; Wang, B. Hardware-in-the-Loop (HIL) Validation for DER Protection Model Executed in Dominion Energy Training Program. In Proceedings of the 2024 IEEE 52nd Photovoltaic Specialist Conference (PVSC), Seattle, WA, USA, 9–14 June 2024; pp. 811–816. [Google Scholar]
  28. Chen, Y.; Zamzam, A.; Chakraborty, S.; Wang, J. Decentralized Microgrid Protection Through Relative Fault Direction Classification. In Proceedings of the 2024 IEEE Power & Energy Society General Meeting (PESGM), Seattle, WA, USA, 21–25 July 2024; pp. 1–5. [Google Scholar]
  29. ETAP. ETAP—Power System Analysis Software; ETAP. Available online: https://etap.com/ (accessed on 7 December 2024).
  30. PSCAD. PSCAD—Power System Simulation Software; PSCAD. Available online: https://www.pscad.com/ (accessed on 7 December 2024).
  31. DIgSILENT. PowerFactory—Power System Analysis Software; DIgSILENT. Available online: https://www.digsilent.de/en/powerfactory.html (accessed on 5 December 2024).
  32. EMTP. EMTP—Electromagnetic Transients Program; EMTP. Available online: https://emtp.com/ (accessed on 6 December 2024).
  33. OPAL-RT. HYPERSIM—Real-Time Simulator for Power Systems; OPAL-RT Technologies. Available online: https://www.opal-rt.com/systems-hypersim/ (accessed on 7 December 2024).
  34. Siemens. Advanced Protection Assessment—Grid Resilience. Siemens. Available online: https://www.siemens.com/global/en/products/energy/grid-software/maintain/grid-resilience/advanced-protection-assessment.html (accessed on 7 December 2024).
  35. CYME. CYME—Power Systems Analysis Software; CYME. Available online: https://www.eaton.com/us/en-us/digital/brightlayer/brightlayer-utilities-suite/cyme-power-engineering-software-solutions.html (accessed on 22 May 2025).
  36. MathWorks. MATLAB and Simulink for Technical Computing; MathWorks. Available online: https://www.mathworks.com/ (accessed on 1 December 2024).
  37. Alasali, F.; Saidi, A.S.; El-Naily, N.; Alnaser, S.W.; Holderbaum, W.; Saad, S.M.; Gamaleldin, M. Advanced Coordination Method for Overcurrent Protection Relays Using New Hybrid and Dynamic Tripping Characteristics for Microgrid. IEEE Access 2022, 10, 127377–127396. [Google Scholar] [CrossRef]
  38. Najafabadi, S.R.K.; Fani, B.; Sadeghkhani, I. Optimal Determination of Photovoltaic Penetration Level Considering Protection Coordination. IEEE Syst. J. 2022, 16, 2121–2124. [Google Scholar] [CrossRef]
  39. El-Hamrawy, A.H.; Ebrahiem, A.A.M.; Megahed, A.I. Improved Adaptive Protection Scheme Based Combined Centralized/Decentralized Communications for Power Systems Equipped With Distributed Generation. IEEE Access 2022, 10, 97061–97074. [Google Scholar] [CrossRef]
  40. Bhargav, R.; Gupta, C.P.; Bhalja, B.R. Unified Impedance-Based Relaying Scheme for the Protection of Hybrid AC/DC Microgrid. IEEE Trans. Smart Grid 2022, 13, 913–927. [Google Scholar] [CrossRef]
  41. Elsamahy, M. Reducing Microgrids Integration Complexity in Distribution Networks Considering Bidirectional Power Flow in SFCLs. IEEE Access 2022, 10, 80365–80378. [Google Scholar] [CrossRef]
  42. Farshadi, A.; Eydi, B.K.; Nafisi, H.; Askarian-Abyaneh, H.; Beiranvand, A. Rate of Change of Direct-Axis Current Component Protection Scheme for Inverter-Based Islanded Microgrids. IEEE Access 2023, 11, 46926–46937. [Google Scholar] [CrossRef]
  43. Memon, A.A.; Kauhaniemi, K. Protection of the Future Harbor Area AC Microgrids Containing Renewable Energy Sources and Batteries. IEEE Access 2023, 11, 57448–57469. [Google Scholar] [CrossRef]
  44. Srivastava, C.; Tripathy, M. Novel Adaptive Fault Detection Strategy in DC Microgrid Utilizing Statistical-Based Method. IEEE Trans. Ind. Inform. 2023, 19, 6917–6929. [Google Scholar] [CrossRef]
  45. Zhou, C.; Zou, G.; Zhang, S.; Zheng, M.; Tian, J.; Du, T. Mathematical Morphology-Based Fault Data Self-Synchronization Method for Differential Protection in Distribution Networks. IEEE Trans. Smart Grid 2023, 14, 2607–2620. [Google Scholar] [CrossRef]
  46. Liu, X.; Li, G.; Zheng, T.; Yang, X.; Guerrero, J.M. Thyristor-Pair- and Damping-Submodule-Based Protection Against Valve-Side Single-Phase-to-Ground Faults in MMC-MTDC Systems. IEEE Trans. Power Deliv. 2022, 37, 3257–3269. [Google Scholar] [CrossRef]
  47. Wang, Z.; Mu, L.; Fang, C. Renewable Microgrid Protection Strategy Coordinating with Current-based Fault Control. J. Mod. Power Syst. Clean Energy 2022, 10, 1679–1689. [Google Scholar] [CrossRef]
  48. Nougain, V.; Mishra, S.; Nag, S.S.; Lekić, A. Fault Location Algorithm for Multi-Terminal Radial Medium Voltage DC Microgrid. IEEE Trans. Power Deliv. 2023, 38, 4476–4488. [Google Scholar] [CrossRef]
  49. Zhou, C.; Zou, G.; Zang, L.; Du, X. Current Differential Protection for Active Distribution Networks Based on Improved Fault Data Self-Synchronization Method. IEEE Trans. Smart Grid 2022, 13, 166–178. [Google Scholar] [CrossRef]
  50. Gani, M.B.; Brahma, S. A Closed-Form Mathematical Model and Method for Fast Fault Location on a Low Voltage DC Feeder Using Single-Ended Measurements. IEEE Open Access J. Power Energy 2022, 9, 523–536. [Google Scholar] [CrossRef]
  51. Merritt, N.R.; Chakraborty, C.; Bajpai, P. An E-STATCOM Based Solution for Smoothing Photovoltaic and Wind Power Fluctuations In a Microgrid Under Unbalanced Conditions. IEEE Trans. Power Syst. 2022, 37, 1482–1494. [Google Scholar] [CrossRef]
  52. Ropp, M.E.; Reno, M.J.; Biswal, M. Detection and Prevention of Unintentional Formation of Loops in Self-Healing Power Systems and Microgrids. IEEE Trans. Power Deliv. 2023, 38, 2682–2691. [Google Scholar] [CrossRef]
  53. Momesso, A.E.C.; Kume, G.Y.; Faria, W.R.; Pereira, B.R.; Asada, E.N. Automatic Recloser Adjustment for Power Distribution Systems. IEEE Trans. Power Deliv. 2022, 37, 3958–3967. [Google Scholar] [CrossRef]
  54. Anudeep, B.; Nayak, P.K. Differential Power Based Selective Phase Tripping for Fault-resilient Microgrid. J. Mod. Power Syst. Clean Energy 2022, 10, 459–470. [Google Scholar] [CrossRef]
  55. Jnaneswar, K.; Rana, A.S.; Thomas, M.S. DCVD-VMD Enabled Traveling Wave-Based Fault Location in Nonhomogenous AC Microgrids. IEEE Syst. J. 2023, 17, 2411–2421. [Google Scholar] [CrossRef]
  56. Yin, Y.; Fu, Y.; Zhang, Z.; Zamani, A. Protection of Microgrid Interconnection Lines Using Distance Relay With Residual Voltage Compensations. IEEE Trans. Power Deliv. 2022, 37, 486–495. [Google Scholar] [CrossRef]
  57. Yousaf, M.; Muttaqi, K.M.; Sutanto, D. An Investigative Analysis of the Protection Performance of Unbalanced Distribution Networks With Higher Concentration of Distributed Energy Resources. IEEE Trans. Ind. Appl. 2022, 58, 1771–1782. [Google Scholar] [CrossRef]
  58. Firouzabadi, T.D.; Zarchi, D.A.; Mazid, M.; Safdarkhani, H.; Nafisi, H. Overarching Preventive Sympathetic Tripping Approach in Active Distribution Networks Without Telecommunication Platforms and Additional Protective Devices. IEEE Access 2022, 10, 28411–28421. [Google Scholar] [CrossRef]
  59. Bayati, N.; Baghaee, H.R.; Hajizadeh, A.; Soltani, M. Localized Protection of Radial DC Microgrids With High Penetration of Constant Power Loads. IEEE Syst. J. 2021, 15, 4145–4156. [Google Scholar] [CrossRef]
  60. Guan, L.; Chen, H.; Lin, L. A Multi-Agent-Based Self-Healing Framework Considering Fault Tolerance and Automatic Restoration for Distribution Networks. IEEE Access 2021, 9, 21522–21531. [Google Scholar] [CrossRef]
  61. Said, A.; Hashima, S.; Fouda, M.M.; Saad, M.H. Deep Learning-Based Fault Classification and Location for Underground Power Cable of Nuclear Facilities. IEEE Access 2022, 10, 70126–70142. [Google Scholar] [CrossRef]
  62. Penaloza, J.D.R.; Borghetti, A.; Napolitano, F.; Tossani, F.; Nucci, C.A. A New Transient-Based Earth Fault Protection System for Unearthed Meshed Distribution Networks. IEEE Trans. Power Deliv. 2021, 36, 2585–2594. [Google Scholar] [CrossRef]
  63. Delavari, A.; Brunelle, P.; Mugombozi, C.F. Real-Time Modeling and Testing of Distance Protection Relay Based on IEC 61850 Protocol. Can. J. Electr. Comput. Eng. 2020, 43, 157–162. [Google Scholar] [CrossRef]
  64. Gu, J.C.; Hsu, L.C.; Wang, J.M.; Yang, M.T. A Dynamic Load-Shedding Technology Based on IEC 61850 in Microgrid. IEEE Trans. Ind. Appl. 2023, 59, 7382–7391. [Google Scholar] [CrossRef]
  65. Gadde, P.; Brahma, S.; Patel, T. Real-Time Hardware-in-The-Loop Implementation of Protection and Self-Healing of Microgrids. IEEE Trans. Ind. Appl. 2023, 59, 403–411. [Google Scholar] [CrossRef]
  66. Saxena, A.; Sharma, N.K.; Samantaray, S.R. An Enhanced Differential Protection Scheme for LVDC Microgrid. IEEE J. Emerg. Sel. Top. Power Electron. 2022, 10, 2114–2125. [Google Scholar] [CrossRef]
  67. Prince, S.K.; Affijulla, S.; Panda, G. Protection of DC Microgrids Based on Complex Power During Faults in On/Off-Grid Scenarios. IEEE Trans. Ind. Appl. 2023, 59, 244–254. [Google Scholar] [CrossRef]
  68. Rao, G.K.; Jena, P. Unit Protection of Tapped Line DC Microgrid. IEEE J. Emerg. Sel. Top. Power Electron. 2022, 10, 4680–4689. [Google Scholar] [CrossRef]
  69. Sharma, N.K.; Samantaray, S.R.; Bhende, C.N. VMD-Enabled Current-Based Fast Fault Detection Scheme for DC Microgrid. IEEE Syst. J. 2022, 16, 933–944. [Google Scholar] [CrossRef]
  70. Rao, G.K.; Jena, P. A Novel Fault Identification and Localization Scheme for Bipolar DC Microgrid. IEEE Trans. Ind. Inform. 2023, 19, 11752–11764. [Google Scholar] [CrossRef]
  71. Mumtaz, F.; Imran, K.; Bukhari, S.B.A.; Mehmood, K.K.; Abusorrah, A.; Shah, M.A.; Kazmi, S.A.A. A Kalman Filter-Based Protection Strategy for Microgrids. IEEE Access 2022, 10, 73243–73256. [Google Scholar] [CrossRef]
  72. Samal, S.; Samantaray, S.R.; Sharma, N.K. Data-Mining Model-Based Enhanced Differential Relaying Scheme for Microgrids. IEEE Syst. J. 2023, 17, 3623–3634. [Google Scholar] [CrossRef]
  73. Aboelezz, A.M.; El-Saadawi, M.M.; Eladl, A.A.; Sedhom, B.E. IEC 61850 Communication-Based Pilot Distance Protective IED for Fault Detection and Location in DC Zonal Shipboard Microgrid. IEEE Trans. Ind. Appl. 2023, 59, 5559–5569. [Google Scholar] [CrossRef]
  74. Bakkar, M.; Bogarra, S.; Córcoles, F.; Iglesias, J.; Hanaineh, W.A. Multi-Layer Smart Fault Protection for Secure Smart Grids. IEEE Trans. Smart Grid 2023, 14, 3125–3135. [Google Scholar] [CrossRef]
  75. Srivastava, A.; Parida, S.K. A Robust Fault Detection and Location Prediction Module Using Support Vector Machine and Gaussian Process Regression for AC Microgrid. IEEE Trans. Ind. Appl. 2022, 58, 930–939. [Google Scholar] [CrossRef]
  76. Bayati, N.; Baghaee, H.R.; Hajizadeh, A.; Soltani, M.; Lin, Z.; Savaghebi, M. Local Fault Location in Meshed DC Microgrids Based On Parameter Estimation Technique. IEEE Syst. J. 2022, 16, 1606–1615. [Google Scholar] [CrossRef]
  77. Gao, J.; Li, X.; Xin, M.; Yu, Y.; Xu, C. An Adaptive Protection Scheme for Power Systems Considering the Effects of HVDC Interfaced Distributed Generations. IEEE Access 2022, 10, 10210–10218. [Google Scholar] [CrossRef]
  78. Jarrahi, M.A.; Samet, H.; Ghanbari, T. Fault Detection in DC Microgrid: A Transient Monitoring Function-Based Method. IEEE Trans. Ind. Electron. 2023, 70, 6284–6294. [Google Scholar] [CrossRef]
  79. Čuljak, M.; Pandžić, H.; Havelka, J. Mathematical Morphology-Based Fault Detection in Radial DC Microgrids Considering Fault Current From VSC. IEEE Trans. Smart Grid 2023, 14, 2545–2557. [Google Scholar] [CrossRef]
  80. Altaf, M.W.; Arif, M.T.; Saha, S.; Islam, S.N.; Haque, M.E.; Oo, A.M.T. Effective ROCOF-Based Islanding Detection Technique for Different Types of Microgrid. IEEE Trans. Ind. Appl. 2022, 58, 1809–1821. [Google Scholar] [CrossRef]
  81. IEEE Std C37.118.1-2011; IEEE Standard for Synchrophasor Measurements for Power Systems. Revision of IEEE Std C37.118-2005. Institute of Electrical and Electronics Engineers: New York, NY, USA, 2011.
  82. IEC TR 61850-90-5:2012; Communication Networks and Systems for Power Utility Automation-Part 90-5: Use of IEC 61850 to Transmit Synchrophasor Information According to IEEE C37.118, 1st ed. International Electrotechnical Commission: Geneva, Switzerland, 2012.
  83. IEC 60870-5-104:2006; Telecontrol Equipment and Systems-Part 5-104: Transmission Protocols-Network Access for IEC 60870-5-101 Using Standard Transport Profiles, 2nd ed. International Electrotechnical Commission: Geneva, Switzerland, 2006.
  84. IEEE Std. 1815-2012; IEEE Standard for Electric Power Systems Communications-Distributed Network Protocol (DNP3). Institute of Electrical and Electronics Engineers: New York, NY, USA, 2012.
  85. IEC 60870-5-103:1997; Telecontrol Equipment and Systems-Part 5-103: Transmission Protocols-Companion Standard for the Informative Interface of Protection Equipment, 1st ed. International Electrotechnical Commission: Geneva, Switzerland, 1997.
  86. IEC 62439-1:2010+AMD1:2012+AMD2:2016 CSV; Industrial Communication Networks-High Availability Automation Networks-Part 1: General Concepts and Calculation Methods, 1st ed. International Electrotechnical Commission: Geneva, Switzerland, 2010.
  87. Gaspar, J.; Cruz, T.; Lam, C.T.; Simões, P. Smart Substation Communications and Cybersecurity: A Comprehensive Survey. IEEE Commun. Surv. Tutor. 2023, 25, 2456–2493. [Google Scholar] [CrossRef]
  88. Triangle Microwave Works. Triangle Microwave Works, w.t.c. Available online: https://www.trianglemicroworks.com/ (accessed on 22 November 2024).
  89. Wireshark. Available online: www.wireshark.org (accessed on 22 November 2024).
  90. Hemmati, M.; Palahalli, H.; Gruosso, G.; Grillo, S. Interoperability analysis of IEC61850 protocol using an emulated IED in a HIL microgrid testbed. In Proceedings of the 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Aachen, Germany, 25–28 October 2021; pp. 152–157. [Google Scholar]
  91. IEDexplorer. IEC 61850 Configuration and Testing Tool. SourceForge. Available online: https://sourceforge.net/projects/iedexplorer/ (accessed on 26 May 2025).
  92. ABB. Protection and Control IED Manager PCM600. ABB Group. 2025. Available online: https://new.abb.com/medium-voltage/digital-substations/software-products/protection-and-control-ied-manager-pcm600 (accessed on 8 January 2025).
  93. Rodríguez, E.N.; Baltazar, D.S. Design and configuration of the protection schemes of an electrical substation based on IEC61850. In Proceedings of the 2024 IEEE PES Generation, Transmission and Distribution Latin America Conference and Industrial Exposition (GTDLA), Ixtapa, Mexico, 11–13 November 2024; pp. 1–7. [Google Scholar]
  94. Claveria, J.; Kalam, A. GOOSE Protocol: IED’s Smart Solution for Victoria University Zone Substation (VUZS) Simulator Based on IEC61850 Standard. In Proceedings of the 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), Kota Kinabalu, Malaysia, 7–10 October 2018; pp. 730–735. [Google Scholar]
  95. Kotulla, M.; Vrzala, M.; Gono, R. Measuring of Fault Distance Using the Fault Locator Function of Protection Relay. In Proceedings of the 2019 20th International Scientific Conference on Electric Power Engineering (EPE), Kouty nad Desnou, Czech Republic, 15–17 May 2019; pp. 1–5. [Google Scholar]
  96. Siemens. DIGSI 5 Engineering Software; Siemens: Plano, Texas, USA, 2025; Available online: https://www.siemens.com/us/en/products/energy/energy-automation-and-smart-grid/protection-relays-and-control/engineering-tools-for-protection/engineering-software-digsi-5.html (accessed on 1 January 2025).
  97. Cárdenas, C.P.P.; González, E.A.G.; Palomeque, F.A.Q. Transformer Differential Protection. In Proceedings of the 2023 International Conference for Advancement in Technology (ICONAT), Goa, India, 24–26 January 2023; pp. 1–6. [Google Scholar]
  98. Alkhalili, H.; Loebel, J.; Jaeger, J. Distance Protection Test on Siemens SIPROTEC Digital Twin with MATLAB Simulink Test Grid. In Proceedings of the PESS 2023, Power and Energy Student Summit, Bielefeld, Germany, 15–17 November 2023; pp. 100–105. [Google Scholar]
  99. GE Vernova. Multilin Software Catalog; GE Vernova: Toronto, ON, Canada, 2025; Available online: https://www.gevernova.com/grid-solutions/multilin/catalog/software.htm (accessed on 1 January 2025).
  100. Chamundeswari, D.; Srikanth, K. Over Current and Over Voltage Protection and Working of LED Operation in D60 Using Enervista Ursetup Software. In Proceedings of the 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), Bangalore, India, 18–19 May 2018; pp. 1597–1602. [Google Scholar]
  101. Pruthvi, P.; Bhuvaneswari, H.B.; Sudheendran, L. Analysis of utility communication protocol IEC 61850 for substation automation systems. In Proceedings of the National Conference on Challenges in Research & Technology in the Coming Decades (CRT 2013), Ujire, India, 27–28 September 2013; pp. 1–8. [Google Scholar]
  102. Schneider Electric. Easergy Studio. 2025. Available online: https://www.se.com/uk/en/product-range/61035-easergy-studio/#overview (accessed on 2 January 2025).
  103. Solórzano, D.F.C.; Chuñir, J.A.G.; Palomeque, F.A.Q. Didactic Integration For The Monitoring Of Electric Power Systems Using Power Monitoring Expert With Modbus TCP/IP And IEC 61850 Communication. In Proceedings of the 2023 5th Global Power, Energy and Communication Conference (GPECOM), Cappadocia, Turkiye, 14–16 June 2023; pp. 244–249. [Google Scholar]
  104. Schweitzer Engineering Laboratories. SEL-735. Available online: https://selinc.com/products/735/ (accessed on 22 November 2024).
  105. Monemi, S.; Boghzian, A. A Protection Scheme in RTDS Model of an IEEE 16-Bus System. In Proceedings of the 2023 IEEE Conference on Technologies for Sustainability (SusTech), Portland, OR, USA, 19–22 April 2023; pp. 144–150. [Google Scholar]
  106. Moldovan, D.; Ayyanar, R. DNP3 Implementation in a High DER Penetration Distribution System. In Proceedings of the 2024 IEEE Kansas Power and Energy Conference (KPEC), Manhattan, KS, USA, 25–26 April 2024; pp. 1–5. [Google Scholar]
  107. Monemi, S.; Dulay, J.P.; Kelble, D. Power System Protection in RTDS. In Proceedings of the 2020 IEEE Conference on Technologies for Sustainability (SusTech), Santa Ana, CA, USA, 23–25 April 2020; pp. 1–6. [Google Scholar]
  108. Monemi, S.; Corregidor, R.; Dunn, S.; Koepke, S.; Weber, S. Protection Relays in a Model of IEEE n-Bus System using Real Time Digital Simulation. In Proceedings of the 2022 IEEE Conference on Technologies for Sustainability (SusTech), Corona, CA, USA, 21–23 April 2022; pp. 92–99. [Google Scholar]
  109. OMICRON. CMC 356—Multi-Function Primary Test Set. Available online: https://www.omicronenergy.com/en/products/cmc-356/ (accessed on 22 November 2024).
  110. Alvarez, C.H.F.; Veintimilla, C.M.P.; Palomeque, F.A.Q. Differential Protection Analisys For Detection Of Ground Faults On the Generator Stator. In Proceedings of the 2022 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), Ixtapa, Mexico, 9–11 November 2022; pp. 1–6. [Google Scholar]
  111. Liu, E.; Nair, N.K.C. Line-to-Ground Arc Flash Fault Detection Using Distance Protection Scheme for Wildfire. In Proceedings of the 2024 IEEE PES Innovative Smart Grid Technologies—Asia (ISGT Asia), Bengaluru, India, 10–13 November 2024; pp. 1–5. [Google Scholar]
  112. Stefko, R.; Conka, Z.; Pavlik, M.; Bucko, S.; Medved, D.; Kolcun, M. Operation of directional overcurrent protection in Microgrids. In Proceedings of the 2023 23rd International Scientific Conference on Electric Power Engineering (EPE), Brno, Czech Republic, 24–26 May 2023; pp. 1–4. [Google Scholar]
  113. Simić, N.; Strezoski, L.; Milićević, R. Relay Protection in Microgrids: Settings and Sensitivity in Presence of IBDERs. In Proceedings of the 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Novi Sad, Serbia, 10–12 October 2022; pp. 1–5. [Google Scholar]
  114. Hadbah, A.; Ustun, T.S.; Kalam, A. Using IEDScout software for managing multivendor IEC61850 IEDs in substation automation systems. In Proceedings of the 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm), Venice, Italy, 3–6 November 2014; pp. 67–72. [Google Scholar]
  115. ABB. Control Rooms. Available online: https://docs.nxlog.co/integrate/abb-microscada-pro-sys600.html (accessed on 22 May 2025).
  116. MICROSCADA Pro. ABB. 2012. Available online: https://library.e.abb.com/public/31875efdad0f0be8852579ca00487ea3/ABB_tn.MICROSCADApro.3.23.2012.lo.pdf (accessed on 5 May 2025).
  117. Subnet. Subnet Solutions. Available online: https://subnet.com/ (accessed on 22 November 2024).
  118. Energy & Infrastructure. COPA-DATA. Available online: https://www.copadata.com/en/industries/energy-infrastructure/ (accessed on 22 November 2024).
  119. SR750. GE Grid Solutions. Available online: https://www.gevernova.com/grid-solutions/automation/protection-control-metering/sr-family-legacy (accessed on 22 May 2025).
  120. Raspberry Pi. Raspberry Pi Foundation. Available online: https://www.raspberrypi.org. (accessed on 22 November 2024).
  121. Digital Signal Processors (DSPs): Overview. Texas Instruments. Available online: https://www.ti.com/product-category/microcontrollers-processors/digital-signal-processors/overview.html (accessed on 22 November 2024).
  122. Sanati, S.; Azzouz, M.; Awad, A.S.A. Adaptive Auto-Reclosing and Active Fault Detection of Lines Emanating from Wind Farms in Microgrids. IEEE Trans. Energy Convers. 2023, 39, 389–399. [Google Scholar] [CrossRef]
  123. Xilinx Zynq UltraScale+ MPSoC Product Pag. Available online: https://www.xilinx.com/products/silicon-devices/soc/zynq-ultrascale-mpsoc.html (accessed on 10 May 2025).
  124. Intel FPGA Solutions for Power and Energy. Available online: https://www.intel.com/content/www/us/en/energy/fpga-power-energy.html (accessed on 10 May 2025).
  125. Lattice Semiconductor MachXO and ECP5 FPGA Families. Available online: https://www.latticesemi.com/Products/FPGAandCPLD/MachXO3D (accessed on 10 May 2025).
  126. Texas Instruments C2000 Real-Time Control MCUs. Available online: https://www.ti.com/product-category/microcontrollers-processors/c2000-real-time-mcus/overview.html (accessed on 10 May 2025).
  127. Industrial Ethernet 3000 Series Switches. Cisco. Available online: https://www.cisco.com/c/en/us/support/switches/industrial-ethernet-3000-series-switches/series.html (accessed on 22 November 2024).
  128. Industrial Security Appliance (ISA). Cisco. Available online: https://www.cisco.com/c/en/us/products/security/industrial-security-appliance-isa/index.html. (accessed on 22 November 2024).
  129. ABB. REF615 Manual. ABB. Available online: https://library.e.abb.com/public/f49c47babe06a298c1257b2f0054c256/REF615_appl_756378_ENk.pdf (accessed on 3 May 2025).
  130. ABB. REF620 Manual. ABB. Available online: https://library.e.abb.com/public/3b8e5f754bc0595bc1257b9f00173a57/REF620_appl_757651_ENa.pdf (accessed on 3 May 2025).
  131. ABB. REF630 Manual. ABB. Available online: https://library.e.abb.com/public/cb44f4cf8aba4ef3902a2a6581f6fe11/REF630_appl_756510_ENf.pdf (accessed on 3 May 2025).
  132. ABB. RELION® 630 SERIES Generator Protection and Control REG630 Application Manual, Document ID: 1MRS757582, Issued: 2019-02-25. ABB. Available online: https://library.e.abb.com/public/55c042aed164433ab96df282353959b1/REG630_appl_757582_ENc.pdf (accessed on 22 May 2025).
  133. SIEMENS. Overcurrent and Feeder Protection—SIPROTEC 7SJ85 Manual; SIEMENS: Mumbai, Maharashtra, 2024. [Google Scholar]
  134. SIMENS. Multi-Functional Protective Relay with Bay Controller 7SJ61 V4.9 Manual; Siprotec 4 Series, C53000-G1140-C210-5; SIEMENS: Mumbai, Maharashtra, 2012. [Google Scholar]
  135. SIEMENS. SIPROTEC 5 7UT82/85/86/87 Transformer Differential Protection—Manual; SIEMENS: Mumbai, Maharashtra, 2025. [Google Scholar]
  136. GE Grid Solutions. Multilin. GE. Available online: https://www.gevernova.com/grid-solutions/automation/protection-control-metering/multilin-8-series (accessed on 20 May 2025).
  137. GE Vernova. Grid Solutions, P60 Agile P161/P162/P163; Grid-GA-L3-P16X-0770-2017; GE Vernova: Cambridge, MA, USA, 2017; Available online: https://www.gevernova.com/grid-solutions/sites/default/files/resources/products/brochures/grid-ga-l3-p16x-0770-2017_02-en.pdf (accessed on 18 May 2025).
  138. Schneider Electric. Generator Protection Relay “P34x_EN_M_J96, Technical Manual”; Schneider Electric: Mumbai, MA, USA, 2023; Available online: https://www.se.com/us/en/download/document/P34x_EN_M_J96/ (accessed on 18 May 2025).
  139. S & C Electric Company. Product 421. SEL. Available online: https://selinc.com/products/421/ (accessed on 3 May 2025).
  140. Schweitzer Engineering Laboratories. I. SEL-751 Data Sheet, Date Code 20241231; Schweitzer Engineering Laboratories: Pullman, WA, USA, 2024. [Google Scholar]
  141. ALSTOM. GEGrid Solutions, MiCOM P40 AgileP141, P142, P143, P145, Technical Manual Feeder Management IED; Publication Reference: P14x-TM-EN-3.2; ALSTOM: Mumbai, MA, USA, 2021. [Google Scholar]
  142. Relion Protection and Control. ABB. Available online: https://library.e.abb.com/public/3c51f878cc617834c1257cdd0055ebb3/1MRG014097_en_Relion_670-650_series_Hardware_650_1.3_IEC_and_ANSI.pdf (accessed on 22 May 2025).
  143. Siemens. SIPROTEC 5. Available online: https://www.siemens.com/global/en/products/energy/energy-automation-and-smart-grid/protection-relays-and-control/siprotec-5.html (accessed on 22 May 2025).
  144. OPAL-RT Technologies. Available online: https://www.opal-rt.com (accessed on 22 November 2024).
  145. Monaro, P.P.D.R.M. Real-Time Simulation Laboratory, Spotlight on PHIL and Power Converters. RTDS Technologies: Seoul, Republic of Korea, 4 December 2024. [Google Scholar]
  146. Hardware-in-the-Loop (HIL) Testing Solutions. Speedgoat. Available online: https://www.speedgoat.com/solutions/testing-workflows/hardware-in-the-loop (accessed on 22 November 2024).
  147. RTDS Technologies. Available online: https://www.rtds.com (accessed on 22 November 2024).
  148. ABB. SACE Emax 2. Available online: https://new.abb.com/products/1SDA072013R1/sace-emax-2. (accessed on 22 November 2024).
  149. Schneider Electric. Masterpact MTZEDT. Available online: https://www.se.com/ca/en/product-range/65745-masterpact-mtz/#documents (accessed on 22 May 2025).
  150. PMU—Phasor Measurement Unit. GE Grid Solutions. Available online: https://www.gevernova.com/grid-solutions/automation/protection-control-metering/micom-agile-p847-legacy (accessed on 22 May 2025).
  151. Huawei. RTN 900. Available online: https://carrier.huawei.com/en/products/wireless-network/microwave/split-mount-microwave/rtn900-series (accessed on 22 May 2025).
  152. Nokia. Networks. Available online: https://www.nokia.com/networks/ (accessed on 22 November 2024).
  153. Grover, H.; Kamwa, I. Solar PV-Based Power Conversion System: A Real-Time Testing Facility. In Proceedings of the 2025 8th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech), Kolkata, India, 31 January–2 February 2025; pp. 1–6. [Google Scholar]
  154. Energy Storage System & Power Conversion System Test Solutions PCS/PV Inverter/Battery Pack. 2023. Available online: https://www.chromaate.com/eu/test_solutions/energy_storage_system_power_conversion_system_test_solution (accessed on 16 August 2025).
  155. Wang, J.; Zamzam, A.; Soumitra, K. Design Protection Schemes for 100% Renewable Microgrids; No. NREL/PR-5D00-84718; National Renewable Energy Lab (NREL): Golden, CO, USA, 2022. [Google Scholar]
Figure 1. Protection software classification.
Figure 1. Protection software classification.
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Figure 2. The recent usage of software tools in microgrid protection research.
Figure 2. The recent usage of software tools in microgrid protection research.
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Figure 3. A schematic diagram of the setup used in a microgrid protection study, employing Texas Instruments DSPs for real-time simulation purposes [122].
Figure 3. A schematic diagram of the setup used in a microgrid protection study, employing Texas Instruments DSPs for real-time simulation purposes [122].
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Figure 4. The experimental setup of a schematic diagram in Figure 3, used in a microgrid protection study employing Texas Instruments DSPs [122].
Figure 4. The experimental setup of a schematic diagram in Figure 3, used in a microgrid protection study employing Texas Instruments DSPs [122].
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Figure 5. The schematic diagram of a protection setup in a microgrid study that utilizes OPAL-RT for real-time simulation [23].
Figure 5. The schematic diagram of a protection setup in a microgrid study that utilizes OPAL-RT for real-time simulation [23].
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Figure 6. The experimental setup of the protection setup in Figure 5.
Figure 6. The experimental setup of the protection setup in Figure 5.
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Figure 7. The diagram of OPAL-RT PHIL test setup [145].
Figure 7. The diagram of OPAL-RT PHIL test setup [145].
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Figure 8. The overview of a solar/BESS power conversion system.
Figure 8. The overview of a solar/BESS power conversion system.
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Table 1. Protection design, and testing tools.
Table 1. Protection design, and testing tools.
Tool TypeTool CategoryUsageExamplesBasic TestbedHardware Prototyping TestbedReal-Time Evaluations (HIL) TestbedReal-Time Evaluations (PHIL) TestbedVendor Adaptability Testbed
SoftwareProtection Simulation SoftwareTransient analysis, protection simulation, and designMATLAB, HYPERSIM, PSCAD, EMTP, DIgSILENT PowerFactory
Communication Testing SoftwareCommunication analysis and trip testingMicrowork Triangle Test Suite, IED Monitor, Wireshark×
SCADA SoftwareIntegrating to SCADAABB COM500, Micro SCADA, Subnet, Zenon×××OptionalOptional
Operational Protection SoftwareProtection coordination, configuration, and settingSKM Power Tools, EasyPowerOptionalOptionalOptionalOptional
HardwareData Logger and Measurement Devices and Fault RecordersMeasurementFluke Power Loggers, Hioki Memory HiLoggers, SEL-735 Power Quality, and Revenue Meter, GE Multilin SR SeriesOptionalOptionalOptionalOptionalOptional
DSP/FPGA-based ControllerImplementing the protection algorithmsRaspberry Pi, Texas Instruments DSPs, Xilinx Zynq UltraScale + MPSoC, Lattice MachXO, ECP5×OptionalOptional
Routers, Switches, NICsCommunication implementationCisco Industrial Ethernet Switches, NETGEAR ProSAFE Switches×OptionalOptional
Cybersecurity MeasuresImmune the protection data and communication linksFortinet Firewalls, Cisco Firewalls×××OptionalOptional
Protective RelaysEvaluation, testing, and implementation of new algorithmsABB RELION Series, Siemens SIPROTEC 5 Series×××Optional
Real-Time SimulatorsHIL/PHIL testingOPAL-RT, RTDS Simulator××
Trip Relays and Circuit BreakersProtection HIL/PHIL testingSchneider Electric’s Masterpact Series, ABB SACE Emax 2×××OptionalOptional
Protection Test EquipmentReplaying Comtrade filesOmicron CMC series×××OptionalOptional
Phasor Measurement Units (PMUs)Wide-area protection, and measurementSEL-421 Protection System, GE Multilin PMUs×××OptionalOptional
Fiber Optic Communication DevicesProtection data transmissionHuawei OptiX RTN Series, Nokia SDH/MSTP Systems××OptionalOptionalOptional
EmulatorsWind Turbine or Solar PV testingITECH IT-N2100, AMETEK SAS, Chroma 62000 H-SOptionalOptional×
PCS Test SuitPCS testingChroma ATS8000, ModelingTech MT8020OptionalOptional×
Table 3. Operation software tools used for protection testbeds.
Table 3. Operation software tools used for protection testbeds.
Operation
Software Tools
PCM600 (ABB)DIGSI
(Siemens)
EnerVista (GE)Easergy
Studio (Schneider)
AcSELerator
QuickSet (SEL)
OMICRON Test
Universe
ManufactureABBSiemensGE MultilinSchneider ElectricSEL (Schweitzer Engineering Labs)OMICRON
Protection RelaysRelion seriesSIPROTEC seriesVarious modelsEasergy seriesVarious modelsN/A (Testing solutions)
Software main FunctionConfiguration, monitoring, and maintenance of relaysConfiguration and setting of SIPROTEC devicesConfiguration, management, and monitoring of relaysConfiguration and monitoring of Easergy relaysConfiguration and management of SEL relaysTesting and diagnostic tools for protection relays
Logic Programming MethodFunction Block Diagram (FBD)Continuous Function Chart (CFC)FlexLogic™Programmable Scheme Logic (PSL)SEL Logic ProgrammingTest Sequence Logic
Main Programming InterfaceFunction blocks with predefined logicCFC with flexible logic blocksEquation-based programmingGraphical logic gatesSEL-specific logic blocksTest sequence programming
Setting TemplatesLimited flexibilityHigh flexibilityModerate flexibilityModerate flexibilitySEL-specific templatesComprehensive test profiles
Advanced Analysis ToolsDisturbance Recorder ToolSIGRA Analysis ToolEnerVista Viewpoint MonitoringWaveform Analysis ToolAdvanced SEL AnalysisAdvanced Test Analysis
Project OrganizationSubstation-oriented structureBay-oriented structureDevice-oriented structureFunction-oriented structureDevice-centricTest scenario-based
File FormatPCM600 proprietary (.pcmi)DIGSI proprietary (.dex)URSettings (.urs)SCL/SCD filesSEL proprietaryCOMTRADE/Test profiles
References & Best Practice[92,93,94,95][93,96,97,98][94,99,100,101][102,103] [104,105,106,107,108][109,110,111,112,113,114]
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Arabahmadi, M.; Sanati, S.; Kamwa, I.; Grover, H. A Review of Software and Hardware Tools for Microgrid Protection Testbeds. Energies 2025, 18, 4417. https://doi.org/10.3390/en18164417

AMA Style

Arabahmadi M, Sanati S, Kamwa I, Grover H. A Review of Software and Hardware Tools for Microgrid Protection Testbeds. Energies. 2025; 18(16):4417. https://doi.org/10.3390/en18164417

Chicago/Turabian Style

Arabahmadi, Majid, Saeed Sanati, Innocent Kamwa, and Himanshu Grover. 2025. "A Review of Software and Hardware Tools for Microgrid Protection Testbeds" Energies 18, no. 16: 4417. https://doi.org/10.3390/en18164417

APA Style

Arabahmadi, M., Sanati, S., Kamwa, I., & Grover, H. (2025). A Review of Software and Hardware Tools for Microgrid Protection Testbeds. Energies, 18(16), 4417. https://doi.org/10.3390/en18164417

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