An Engineer’s Guide to Inverter-Based Resources in Power Systems

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Picture a solar farm running smoothly even as clouds sweep by; that stability starts with an inverter-based resource you can trust.


What Is an Inverter-Based Resource and  How  Does It Function in Power Systems


An inverter-based resource (IBR) converts direct current (DC) into alternating current (AC) and injects that electricity into the grid under tightly controlled conditions. Because the conversion relies on power‑electronic switches rather than a spinning generator, an IBR can respond to grid events in milliseconds, shape its output waveform, and even absorb power when required. Every photovoltaic array, battery energy storage rack, and modern wind turbine contains at least one IBR. 

Power Electronics 101


An IBR starts with a semiconductor bridge, usually insulated‑gate bipolar transistors (IGBTs) or silicon‑carbide MOSFETs, that chops DC into a series of voltage pulses. A digital signal processor times the switching so those pulses approximate a sinusoid after filtering. Because no mechanical inertia exists, the device can modulate magnitude, phase, and frequency nearly instantly. That flexibility allows synthetic inertia, fast voltage support, and ride‑through functions that conventional machines struggle to match.

Control Layers That Matter


Every IBR ships with a multi‑layer controller. The inner loop regulates current to keep hardware within limits. The outer loop follows grid‑code set‑points such as active‑power reference, reactive‑power schedule, or frequency‑response profile. Supervisory software handles communication, fault diagnostics, and cybersecurity. When grid codes evolve, engineers can update firmware instead of overhauling hardware, an advantage that appeals to utilities watching standards tighten each year.

Grid‑Side Interaction


At the point of common coupling, the IBR measures grid voltage and frequency, then synchronizes its output using a phase‑locked loop. Harmonic filters smooth the waveform, while protection logic trips if voltage departs acceptable bands. Because IBRs lack synchronous inertia, they rely on advanced algorithms—such as virtual synchronous machine or grid‑forming modes—to help stabilize weak networks. Correct parameter tuning turns an IBR from a passive follower into an active grid supporter.



Why Engineers Are Focused on Inverter-Based Resources in Modern Grids


Utility‑scale renewables now account for a growing share of capacity, and almost all new plants interface through inverter‑based resources. Traditional synchronous generators are retiring, so grid planners need alternative voltage control, frequency regulation, and fault management. IBRs offer sub‑cycle response, firmware‑upgradable functions, and smaller footprints that fit inside dense urban substations. Their software‑defined nature lets asset owners roll out enhancements long after commissioning, which shortens project timelines and improves overall return on capital.

Types of  Inverter-Based Resources and Where They Are Used in Engineering


  • Photovoltaic string inverter: Converts panel output to grid‑ready AC for residential and commercial rooftops.
  • Central solar inverter: Aggregates multiple DC combiner boxes at utility‑scale plants for megawatt‑level output.
  • Battery energy storage system converter: Manages bidirectional power flow for frequency support, peak shaving, and black‑start service.
  • Type‑3 wind turbine converter (DFIG crowbar): Controls rotor currents to extract energy across variable wind speeds while meeting fault ride‑through requirements.
  • Full‑converter wind turbine (Type‑4): Decouples generator speed from grid frequency, allowing maximum energy capture on large offshore platforms.
  • Modular multilevel HVDC converter station: Moves bulk power over hundreds of miles with precise reactive‑power tuning at each terminal.
  • Static synchronous compensator (STATCOM) within FACTS family: Provides dynamic voltage regulation in weak grids and industrial plants.
These represent more than just conversion hardware, they embody precision control and adaptability across a wide range of engineering needs. From residential rooftops to utility-scale renewable sites and high-voltage transmission corridors, each type supports critical functions like frequency control, reactive power support, and fault ride-through. Their versatility and scalability continue to make them a foundational component in modern grid design and validation workflows.

“Because no mechanical inertia exists, the device can modulate magnitude, phase, and frequency nearly instantly.”

The Role of Inverter-Based Resources in Renewable Integration and Grid Stability


Wind and solar output fluctuates with weather, yet frequency and voltage must stay inside tight limits. An inverter-based resource can dispatch fast frequency response within two to three cycles, hold voltage through reactive injection, and supply synthetic inertia by momentarily releasing stored energy from DC‑link capacitors or connected batteries. During faults, advanced grid‑forming modes ride through voltage dips, preventing cascading trips. As a result, transmission operators view IBRs not as a problem but as an asset for stability, provided their controls are tuned and validated.


Why Simulation Fidelity Matters for Testing Inverter‑Based Resources in Real Time


A control‑level bug inside a 5 MW battery inverter can propagate across the grid far faster than human operators can react. Real‑time electromagnetic transient (EMT) simulation running the exact firmware lets engineers observe sub‑millisecond behavior under corner‑case faults. Lower‑fidelity tools may mask oscillations or misrepresent phase‑locked‑loop dynamics, giving a false sense of security. High‑fidelity hardware‑in‑the‑loop (HIL) setups capture pulse‑width modulation effects, device saturation, and communication latencies—insights essential when compliance fines or safety margins ride on every line of code.

Simulating inverter-based resources introduces several technical constraints that must be addressed early in the testing workflow. Intellectual property protection remains a top priority, as OEMs often require secure environments to share compiled control code without exposing source logic. Electromagnetic transient (EMT) models demand sub-microsecond resolution to accurately capture high-frequency switching behaviors, creating substantial computational loads in large-scale test scenarios. Control parameter variation across projects complicates modeling, requiring tuning flexibility without constant rebuilds. Additionally, evolving grid codes introduce new validation criteria that must be incorporated quickly to remain compliant. Reliable hardware interfaces are also essential—signal fidelity, I/O compatibility, and timing precision must align with field conditions to ensure testing results hold true at commissioning. Each of these factors directly impacts the reliability, scalability, and cost-efficiency of inverter-based resource validation.




Key Challenges Engineers Face When Simulating Inverter-Based Resources


Simulating inverter-based resources introduces several technical constraints that must be addressed early in the testing workflow. Intellectual property protection remains a top priority, as OEMs often require secure environments to share compiled control code without exposing source logic. Electromagnetic transient (EMT) models demand sub-microsecond resolution to accurately capture high-frequency switching behaviors, creating substantial computational loads in large-scale test scenarios. Control parameter variation across projects complicates modeling, requiring tuning flexibility without constant rebuilds. Additionally, grid codes introduce new validation criteria that must be incorporated quickly to remain compliant. Reliable hardware interfaces are also essential—signal fidelity, I/O compatibility, and timing precision must align with field conditions to ensure testing results hold true at commissioning. Each of these factors directly impacts the reliability, scalability, and cost-efficiency of inverter-based resource validation.

“This shared confidence accelerates project approvals, shortens grid‑interconnection queues, and pushes innovation forward with quantified reliability.”

How  OPAL‑RT Supports Testing and Validation of Inverter-Based Resources at Scale


OPAL‑RT’s Blackbox Interface lets you load the genuine controller binaries supplied by the original manufacturer while keeping source code hidden from view, safeguarding intellectual property on all sides. The platform executes EMT models on multi‑core CPUs and FPGAs in the same chassis, so nanosecond‑accurate switching coexists with full‑network load‑flow studies. Built‑in APIs tie to MATLAB / Simulink, Python, and FMI, which means parameter sweeps or automation scripts fit straight into lab workflows. Utilities appreciate the ability to replicate site‑specific faults without extra hardware, while OEMs value the shorter certification cycles and smaller capital outlay. This shared confidence accelerates project approvals, shortens grid‑interconnection queues, and pushes innovation forward with quantified reliability.

Engineers and innovators around the globe rely on real‑time simulation to cut risk and unlock new value. OPAL‑RT brings decades of domain expertise plus open, scalable hardware‑in‑the‑loop solutions so you can design, test, and validate inverter-based resources with precision. From controller prototyping to cloud‑hosted batch studies, our platforms keep your projects on schedule and your stakeholders assured.

Common Questions About Inverter-Based Resources

It is any device that converts DC into AC through power electronics and feeds controllable energy into an electrical grid, such as a solar inverter or battery converter.



They provide sub‑cycle frequency support, fast reactive power, and synthetic inertia algorithms that respond quicker than mechanical generators.



No. HVDC stations, electric‑vehicle fast chargers, and STATCOM devices also fall under the category because they use inverters for grid connection.



High‑resolution EMT and HIL testing expose switching harmonics, control‑loop interactions, and fault behavior that coarser models can miss, preventing costly surprises in the field.



Yes. The Blackbox Interface runs compiled binaries behind secure wrappers, letting you validate performance while keeping proprietary algorithms confidential.







 

Top 25 Power System Simulation Tools for 2025

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High-performance power system simulation tools shorten validation cycles and strengthen reliability across energy infrastructures. Many organizations look to these resources to minimize unexpected outages, stay ahead of emerging grid complexities, and support new technologies such as renewables and advanced control systems. Engineers often face immense pressure to deliver designs on tight schedules, so these specialized platforms provide ways to accelerate modeling, analysis, and testing. Stakeholders from investors to system operators benefit from fast, accurate feasibility checks that reduce capital risk and inform data-driven decisions.

Strategic adoption of these solutions encourages efficient project rollouts and cost-effective operations, especially when high-fidelity accuracy is required. Many businesses also need a scalable approach to handle future expansions, advanced distributed generation, and more robust contingency plans. Selecting an optimal simulator is therefore an important step that can uncover untapped potential and strengthen competitive advantage. Each tool offers unique features, but all share a similar goal of supporting robust analysis and improved design confidence.

1) HYPERSIM

Detailed real-time simulations are a critical component of this platform, which offers multi-core processing for large and small systems alike. Flexible modeling supports complex testing scenarios, including renewable integration and advanced converter designs. Comprehensive debugging and analysis tools permit deeper exploration of model performance under varied operating conditions, ideal for accelerating control system validation. High-fidelity capabilities give engineers a solid foundation for risk assessment. OPAL-RT offers HYPERSIM, a state-of-the-art, extensively field-tested real-time simulation software platform designed for power systems and power electronics, widely used for transient real-time simulation, protection studies, and power system electromagnetic transient analysis.

The ability to replicate conditions with hardware-in-the-loop helps teams mitigate potential issues before large-scale deployment. Through these steps, testing and validation cycles can shrink, leading to lower total investment costs for new projects. System operators also appreciate the potential for safe experimentation with new strategies that might otherwise carry operational hazards. This approach consistently delivers better outcomes and fosters stronger stakeholder buy-in.

2) ePHASORSIM

A specialized real-time simulation software platform dedicated to large-scale phasor-domain power system simulation. It offers detailed transient stability, wide-area grid analysis, and advanced monitoring features, making it suitable for transmission planning and operator training. Engineers often benefit from accelerated validation cycles, as complex scenarios can be modeled quickly to optimize resource planning. OPAL-RT provides ePHASORSIM to help reduce costly surprises in system expansions while increasing confidence in protection schemes.

The platform’s ability to simulate wide-area disturbances in near real-time drives better decision-making across multiple regions. Project teams appreciate how detailed phasor models reveal high-level system interactions without compromising speed. Automated workflows bring extra clarity to reliability studies, improving the odds of successful implementations. The resulting insights inspire data-driven improvements that can strengthen return on investment and grid integrity.

3) RT-LAB

This core software platform supports multiple real-time simulation systems, including eMEGASIM, ePHASORSIM, and eFPGASIM. The flexible environment enables multi-domain power system simulation, control prototyping, and seamless model integration for users seeking a unified development and testing experience. Configurable interfaces handle different model complexities, from rapid prototyping to hardware-in-the-loop validation, accelerating the rollout of innovative solutions. The reliability of RT-LAB helps engineering teams keep projects on schedule while preserving thoroughness in design.

Comprehensive library support reduces time spent building models from scratch, creating a streamlined workflow for power electronics, protection, and large-scale stability studies. Consistent data management across simulation domains eliminates guesswork, promoting consistency within multidisciplinary teams. Tailored reporting and performance metrics ensure transparency for stakeholders who need clear evidence of outcomes. Many appreciate that this software platform fosters adaptability, which becomes increasingly vital in complex power networks.

4) Power Electronics Add-On (eHS) for NI VeriStand

An FPGA-based simulation tool for hardware-in-the-loop (HIL) testing of controllers, suited for power electronics and electric transportation projects. This add-on offers high-fidelity power electronics modeling to complement power system simulations, allowing accurate representation of switching components. Real-time capabilities enhance test coverage for converters, drives, and other intricate subsystems essential to electrification initiatives. Users can achieve reduced development costs by catching potential faults early, ensuring safer deployment of emerging technologies.

The compact design of the FPGA-based solver optimizes system latency, delivering precise waveforms that reflect realistic operating conditions. Engineers often leverage these capabilities to refine controller algorithms before committing to large-scale prototypes. OPAL-RT offers this solution to those who need to accelerate integration between power system and power electronics testing. Collectively, it paves the way for smoother compliance checks, helping organizations reach technical milestones under tight timelines.

5) Real-Time Digital Simulator Hardware Platforms

OPAL-RT provides a range of hardware platforms such as OP5600 V2, OP5650, OP5700, and OP7000 series, supporting real-time power system simulations and HIL testing. These scalable systems accommodate varied project scopes, from single-cabinet solutions to enterprise-level rack configurations. High-performance CPUs and FPGA-based processing ensure accurate transient analysis and precision for protective relays, power converters, and other network elements. Diverse connectivity options make it simpler to integrate the simulator into existing workflows, a priority for teams juggling multiple hardware interfaces.

The modular nature of each hardware platform enables expansions or upgrades without large redesign efforts, preserving cost efficiencies. Advanced cooling and robust design features support stable operation, ideal for lengthy test campaigns under high computational loads. Engineers can rely on consistent performance to streamline validation processes, improving alignment between prototypes and final deployments. This combination of flexibility and power underpins greater confidence in real-time testing outcomes for utilities, OEMs, and research institutions alike.

6) PSS®E

A strong reputation for transmission planning features sets this tool apart, making it a popular choice for organizations aiming to plan expansions. Load flow and short-circuit analyses occur within a consistent environment, allowing for easy data sharing among collaborators. Various add-on modules deliver specialized capabilities, such as contingency analysis or voltage stability assessments. Detailed modeling of network components simplifies the process of identifying reliability issues before implementation.

Large utilities value this solution for its efficient scenario handling, which helps structure resource planning on both immediate and long-term horizons. Faster scenario planning means cost controls remain at the forefront, a priority for executive leadership. Automated processes reduce manual input, limiting error risks and supporting consistent modeling practices across the organization. This leads to smoother alignment among various teams working toward a shared objective.

7) PowerWorld

High-performance interactive simulations define this platform’s approach, allowing visual representations of complex networks. Customizable displays and an intuitive drag-and-drop interface foster faster analysis and broader acceptance among stakeholders. Extensive libraries of equipment models, including generator and load profiles, support accurate replication of operational realities. Time-domain and transient stability modules deliver robust insights for critical event testing.

Teams typically benefit from shortened learning curves and faster time-to-value, which can accelerate design cycles. Visual clarity also helps non-technical stakeholders grasp system intricacies, easing communication about proposed changes. This open exchange of ideas often uncovers opportunities for better allocation of resources and optimized expansions. In many cases, quick identification of feasible solutions leads to enhanced scalability without compromising reliability.

8) PSCAD

Advanced electromagnetic transient simulations give users detailed views of complex events that occur on microsecond timescales. Engineers can integrate controls and power electronics into these models to investigate issues like converter instability or harmonics. Rapid iterative testing helps highlight design flaws early, reducing both development costs and the chance of mission-critical failures. Built-in library components streamline model creation, cutting down on repetitive tasks.

Faster issue resolution reduces downtime in design cycles, a notable advantage when time-to-market is important. Project managers appreciate how it clarifies risk factors, improving project predictability and fostering clear communication with investors. More accurate digital prototypes enable confident planning for expansions or new product launches. This approach frequently results in less guesswork and more robust solutions over a project’s lifespan.

9) NEPLAN

Modular architecture enables users to customize the platform for distribution, transmission, and industrial networks. Advanced planning functions extend to reliability calculations and asset management, which is essential when aiming to reduce operational uncertainties. Built-in optimization tools guide strategies for cost savings while maintaining stability. Detailed harmonic analysis allows for better assessment of equipment compatibility and power quality.

Fewer interruptions in the planning process create direct pathways for better returns on infrastructure investments. Quick detection of potential capacity shortfalls supports more strategic resource allocation, a prime concern for large-scale operations. Grid expansions with minimal complications instill confidence across project teams and expedite overall timelines. Systematic data management further boosts efficiency by maintaining consistency in modeling approaches.


10) CYME

Comprehensive distribution-focused capabilities allow users to evaluate feeder reliability, voltage regulation, and protection coordination in a single environment. Load flow, short-circuit, and arc-flash assessments are integrated into the tool for a well-rounded approach. Detailed device libraries ensure accurate representation of real equipment parameters, a key factor in precise simulations. Scalable modules address anything from microgrid analyses to large utility expansions.

Reduced duplication of effort helps bring down costs, allowing project leads to focus on more nuanced design improvements. Automated reporting fosters clear communication with upper management and external partners. The focus on distribution-level studies enables closer scrutiny of power quality concerns, adding value to the overall user experience. This organized approach can preserve resources and reinforce stakeholder confidence in final outcomes.

11) ERACS

Reliability-centered design stands at the forefront with capabilities in load flow, fault level calculations, and stability analysis. Protective device coordination assists in preventing faults or misoperations that can cause costly downtimes. The platform also offers easy-to-follow schematic interfaces, encouraging faster setup of complex network diagrams. Interfaces for data import from various sources reduce manual data entry tasks.

Clarity in results speeds up the approvals process for new technologies or expansions, which can bolster project momentum. This agility often translates to stronger cost management when deploying capital-intensive upgrades. Automated comparison of multiple scenarios fosters broader insight into potential system vulnerabilities. Those insights empower better decisions that can lead to measurably safer operations and long-term resilience.

12) MATPOWER

An open-source framework provides transparent algorithms for load flow, optimal power flow, and other essential analyses. Researchers and engineers can adapt the code to match specialized needs, offering a high level of flexibility. Quick prototyping of new methodologies becomes possible without heavy licensing costs. The user community contributes to ongoing enhancements, ensuring a wealth of available examples and resources.

This flexibility paves the way for swift innovation, minimizing overhead for initial feasibility testing. Teams can refocus on the bigger picture of optimization and system reliability, rather than wrestling with overly restrictive workflows. The cost benefits make it practical for emerging businesses or academic collaborations exploring cutting-edge solutions. Overall, it supports accelerated research and real-world application testing on a budget-friendly scale.

13) Pandapower

Python-based scripting aligns well with modern data science workflows, linking easily to broader analytics ecosystems. A modular design enables quick customization for specific distribution or transmission modeling tasks. Detailed libraries address widely recognized component models, ensuring realistic simulations. Built-in optimization features streamline load flow analysis, short-circuit calculations, and more advanced tests.

Smoother integrations with machine learning frameworks expand possibilities for predictive maintenance and anomaly detection. This synergy can accelerate the path to market for new ideas, boosting overall productivity. Transparent coding structures help reduce miscommunication among project teams. Adaptable parameter settings also support iterative improvements, providing a strong foundation for ongoing performance gains.

 

“High-performance power system simulation tools shorten validation cycles and strengthen reliability across energy infrastructures.”


14) eMEGASIM

High-speed real-time simulations unify hardware and software testing, offering precise replication of various network scenarios. Scalable architecture works with multi-core processors and FPGA-based technology for accurate modeling of power electronics. Engineers can execute hardware-in-the-loop setups, verifying designs under realistic stresses before deployment. Detailed data acquisition and logging functions facilitate advanced analysis of system transient events.

Quicker validation of control algorithms often leads to swifter product rollouts and lower capital risk. Teams cut down on repeated lab tests, optimizing resources for high-impact tasks. This approach also opens the door to integrated research on grid stability, storage integration, and distributed generation. The outcome is often more reliable solutions that meet market requirements with less overhead.

15) PYPOWER

A lightweight Python tool built around open-source principles makes this option suitable for smaller-scale power flow analyses. Straightforward scripting supports both educational settings and quick feasibility checks in professional environments. Minimal overhead allows integration into larger Python projects, where simulation might only be one component. The design promotes clarity and ease of modification.

In projects that focus on cost-effectiveness, simplicity often wins, and PYPOWER delivers on that front. Lower maintenance demands also mean less friction for teams dealing with multiple software platforms. This tool’s adaptability encourages iterative improvements without complex licensing constraints. That flexibility helps maintain forward momentum for smaller or specialized organizations working within tight budgets.

16) POWSYBL

An open-source framework focused on large-scale power systems, it supports multi-voltage level modeling. The integrated approach helps unify different grid components under a single coherent platform, easing collaboration. Plug-in architecture offers room for expansions and custom workflows, a useful feature for research institutes and utilities. Built-in contingency analysis and security assessment functionality address pressing reliability needs.

Easier data exchange among different departments helps projects move from concept to approval more smoothly. Fewer data silos mean fewer delays, enabling resource allocation that supports growth ambitions. Reliability analyses carried out in a more transparent manner can attract positive attention from stakeholders. This foundation underpins faster progression toward cost-effective solutions that address new market demands.

17) PSAT

Known for its open-source approach to load flow, time-domain simulations, and small-signal stability, this tool caters to academic and research-oriented users. The interface can adapt to different operating systems and data formats, easing integration challenges. Symbolic manipulation features allow deeper exploration of system equations for advanced control design. The model library helps users quickly build typical system elements without starting from scratch.

Clear insights into system behavior translate to informed project decisions that can steer resource allocation wisely. Timely simulation results help shorten planning phases while maintaining reliable design standards. The community-driven nature of this platform adds a wealth of user experiences to draw upon. Those shared learnings accelerate breakthroughs that might shape next-generation solutions in the energy sector.

18) PyPSA

Full integration with Python data science libraries enhances capabilities for automated workflows, multi-objective optimizations, and scenario management. Open data sources can easily link into the framework, supporting large-scale capacity expansion modeling. The modular design helps expand from fundamental load flow calculations to more advanced tasks such as sector coupling. Support for renewable components and storage systems aligns well with modern grid demands.

Automated workflows can trim labor-intensive tasks, freeing teams to concentrate on strategic planning. Efficient scenario testing helps reveal new revenue streams or system performance improvements. This adaptability often reduces the risk associated with experimental grid configurations. Steady collaboration with a global developer community fosters reliable updates and collective learning.

19) GridLAB-D

A focus on distribution networks shapes the robust load forecasting, voltage regulation, and smart metering options included. Agent-based modeling allows complex behavioral patterns to be simulated, capturing elements like consumer demand response. Time-series data inputs provide hour-by-hour or minute-by-minute granularity, leading to accurate operational insights. The code’s open nature encourages experimentation in advanced grid modernization scenarios.

These granular simulations can showcase cost-saving opportunities in distributed generation or demand response programs. The detailed results often appeal to utility planners who need clarity on consumption trends. Saving on infrastructure upgrades or improving existing assets can produce measurable returns for shareholders. A transparent environment for testing new concepts often leads to more stable outcomes over the long term.

20) OpenDSS

An open-source engine dedicated to distribution system analysis, it excels in detailed harmonic evaluation, load profiling, and transformer modeling. Flexible scripting options permit tailored workflow integration and batch processing for large data sets. Results can be integrated with external visualization tools, offering deeper insights for advanced planning. The software’s approach supports single-phase, three-phase, and multi-phase distribution circuits.

This multi-phase versatility helps keep capital expenditures in check by informing targeted infrastructure upgrades. Automated processes reduce time spent on manual data manipulation, which yields cost savings and faster decisions. Better visibility into power quality concerns also enhances investor trust, facilitating expansions with fewer uncertainties. Consistent performance across varied distribution cases fosters confidence in forward progress.

21) PSpice

A specialized circuit simulator geared toward electronic components, it efficiently handles transient, DC, and AC analyses. Sophisticated waveforms and extensive device libraries provide accuracy in modeling semiconductors and related parts. Engaging visual outputs help engineers interpret results more quickly, supporting streamlined design workflows. Key features such as parametric sweeps and Monte Carlo simulations offer valuable optimization insights.

This focus on electronic device modeling leads to improved reliability in board-level and system-level designs. Teams can tweak parameters rapidly and observe immediate outcomes, saving precious development hours. Detailed insights pave the way for risk reduction in prototypes, often translating into leaner investments for new products. Stakeholders stand to benefit from early detection of design flaws before large-scale production.

22) Multisim

Circuit simulation capabilities enable detailed analysis of analog, digital, and power systems. Interactive testing in a controlled virtual environment offers a clear understanding of potential design pitfalls. Toolbars and intuitive controls reduce complexity for engineers who may be new to advanced simulation. The combination of straightforward user experience and robust features addresses a broad range of project needs.

Accelerated prototyping leads to faster rollouts that can meet strict market demands. Early resolution of design errors helps preserve budgets and maintain confidence among project sponsors. Thorough waveforms and measurement instruments guide developers toward optimal settings with minimal trial-and-error. This efficiency ultimately affects profitability by keeping rework times to a minimum.

23) eFPGASIM (eHS)

An FPGA-based approach delivers ultra-fast real-time simulations for complex power electronic systems. Precise resolution of switching events lets users study converter behavior and advanced control schemes with high fidelity. Flexible tool integration ensures synergy with broader hardware-in-the-loop setups, cutting down on development overhead. Efficient debugging workflows simplify the process of validating new designs in accelerated timeframes.

The measurable impact often shows up as significantly reduced project risk and fewer late-stage revisions. This translates directly into financial benefits, especially for businesses focusing on large-scale conversions or product lines. Rapid iteration fosters creative solutions that address new market opportunities quickly. The dependable real-time accuracy positions organizations for ongoing success in advanced power electronics implementations.

24) ETAP

A comprehensive interface and advanced modeling capabilities help users map out intricate power networks with clarity. Accurate load flow and transient stability analyses offer support for mission-critical operations, which is useful when aiming for shorter development cycles and safer electrical infrastructure. Data validation features and scenario comparisons equip users to identify cost-effective measures for system upgrades. Many appreciate the library of reliable protective device models that streamline coordination studies.

Greater accuracy in these analyses saves time and labor, contributing to measurable gains in project ROI. Engineers often gain the confidence to move forward with solutions that carry less risk, which can influence more informed stakeholder alignment. Reliable automation of tasks also means less manual effort and fewer data-entry mistakes. This leads to faster approvals and higher decision quality under tight deadlines.

25) DIgSILENT

Extensive capabilities for load flow, fault analysis, and harmonic assessments provide a thorough approach to power system evaluation. Dynamic modeling and simulation modules allow engineers to simulate complex interactions, which ensures accurate understanding of system behaviors. The interface supports large-scale projects, making it suitable for organizations seeking advanced workflows. Clear customization options also help project teams tailor models to specific needs without major disruptions.

Time-savings from automated reporting and intuitive scenario switching contributes to efficient resource management. Implementing more consistent modeling across teams can lower operational costs while increasing collaboration. The tool’s advanced stability features reduce guesswork, improving both system reliability and investor confidence. Projects often move faster when everyone trusts the simulations guiding their decisions.

Key Features to Consider When Selecting a Tool


Selecting the right simulator can save significant resources, especially for teams that must balance precision, speed to market, and budget constraints. Decision-makers often weigh customization needs, data handling, and real-time capability to gauge whether the tool will grow with future requirements. Clear reporting functionalities matter for presenting findings to management in a way that speeds up approvals. Software compatibility with other platforms or programming languages is another factor that can streamline integration.

  • Comprehensive model libraries: Benefit from quick and accurate system representation.
  • Advanced analysis modules: Streamline tasks like fault calculations or optimization.
  • User-friendly interfaces: Encourage collaboration and reduce learning curves.
  • Scalable architecture: Handle varying system sizes and project needs.
  • Real-time capabilities: Enable hardware-in-the-loop and faster control validation.
  • Customization flexibility: Adapt parameters for specific design considerations.

Thorough assessment of these elements typically maximizes the long-term return on investment. In many organizations, it also helps align multidisciplinary teams, which is critical for large-scale initiatives. Focusing on the features that truly impact outcomes often leads to solutions that combine cost-effectiveness with technical rigor. This multifaceted approach supports both immediate and future business goals.

 

“Faster issue resolution reduces downtime in design cycles, a notable advantage when time-to-market is important.”


Applications of Power System Simulation Tools


Many rely on these tools for everything from basic load flow and short-circuit studies to advanced stability and transient analyses. Real-time hardware-in-the-loop setups expand test coverage by replicating real conditions in a safe environment. Cost-benefit assessments also become more precise when detailed simulations illuminate potential pitfalls and highlight optimal configurations. Integrating distributed energy resources, microgrids, and energy storage solutions into existing grids is another significant use case.

Strategic planning at the utility level benefits from thorough reliability analyses, resource scheduling, and contingency planning. Large industrial operations leverage these platforms for better control over internal power distribution and improved power quality. Some sectors incorporate them into research and development cycles to refine advanced control algorithms before deployment. The continuous evolution of power systems elevates the need for robust software that supports iterative improvement and informed risk management.


Tips for Effective Utilization of Simulation Tools


Efficiency and accuracy can skyrocket when teams adopt best practices for setting up, running, and interpreting results. Proper data management and consistent use of standardized modeling approaches remove barriers to collaboration. Regular software updates and ongoing training also keep personnel aligned with features and capabilities. These pointers often lead to stronger returns, fewer delays, and improved stakeholder trust.

  • Start with smaller test cases: Validate your setup before scaling up.
  • Use version control: Track changes in models to avoid confusion.
  • Leverage scripting: Automate repetitive tasks and reduce manual errors.
  • Compare scenarios: Gather a range of inputs to see variations in system performance.
  • Validate with real data: Align simulations with measurements to improve accuracy.

Cross-functional coordination may be the difference between confident approvals and extended project bottlenecks. Investing time in thorough reviews of simulation results keeps everyone on the same page, preventing costly missteps. Staying organized from the outset also simplifies expansions or upgrades further along. This structured method of utilization frequently translates into better cost controls and more favorable outcomes.

Power system simulation tools serve a pivotal role in modern project development, from handling critical fault analyses to shaping advanced grid expansions. Accurate representation of complex phenomena leads to informed budgeting decisions and shorter review cycles. Many users find that the right simulator not only reduces technical risks but also sets the stage for scalable growth. Executives appreciate the clarity these solutions bring, especially when facing high-stakes investments.

The range of specialized platforms offers flexibility to suit different budgets, operational scales, and technical requirements. Open-source frameworks empower smaller teams or academic researchers, while commercial suites often provide more integrated features for large enterprise deployments. In all cases, well-chosen tools open doors to efficient development, reduced downtime, and strong returns. Careful consideration of key features is an important step toward a future powered by safe, dependable, and profitable systems.

Engineers and innovators around the world are turning to real-time simulation to accelerate development, reduce risk, and push the boundaries of what’s possible. At OPAL-RT, we bring decades of expertise and a passion for innovation to deliver the most open, scalable, and high-performance simulation solutions in the industry. From Hardware-in-the-Loop testing to AI-enabled cloud simulation, our platforms empower you to design, test, and validate with confidence. Discover how OPAL-RT can help bring your boldest ideas to real-time.

Frequently Asked Questions


Many platforms include built-in optimization algorithms that reveal efficient configurations or scheduling approaches. Project teams can focus on improvements that deliver quick payback, which saves money and supports better returns for investors.


Open-source platforms often boast active user communities that enhance reliability by sharing updates and fixing issues promptly. Many engineers trust these solutions for feasibility studies, research initiatives, or smaller-scale commercial applications.

Simulation speed, FPGA integration, and accurate solver algorithms rank high for hardware-in-the-loop scenarios. This ensures that physical devices receive authentic system feedback during testing without delays or approximations.


Several advanced tools leverage Python or similar languages to integrate with AI libraries and big data infrastructure. This allows high-volume data processing, predictive modeling, and automated scenario assessments for a deeper level of insight.


Robust libraries support accurate replication of real equipment and network configurations. This improves the fidelity of results and enables more confident decision-making for expansions, grid upgrades, or new technology deployments.






5 Power System Simulation Tools for 2025

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Power systems rely on robust software simulations for accurate forecasting and mitigation of costly technical issues. Models created through specialized platforms help you predict load behaviors, optimize grid planning, and reduce downtime risk. Stakeholders within utilities, research institutes, and manufacturing settings look for ways to save time, reduce operational burdens, and maintain quality control. Modern simulation technologies bring efficiency, scale, and flexibility, especially with the move toward decentralized energy sources.

Platforms continue to expand features such as cloud readiness and automated workflows, allowing power engineers to get more value from data and analytics. Detailed modeling of transmission and distribution networks has become a practical priority, and many leaders focus on reliability. Grid operators see benefits in system reliability studies that factor in renewable sources and emerging demands. A structured approach to software selection helps ensure that all performance goals and budgets are addressed effectively.

What Are Power System Simulation Tools?




Power system simulation tools refer to specialized programs that model electrical networks under different scenarios, allowing accurate analysis of voltages, currents, and power flows across a range of operating conditions. These solutions go beyond basic circuit calculations by incorporating real-time data, advanced computational algorithms, and customized study cases for areas such as grid resilience and renewable integration. The goal is to replicate actual system performance without the expense or risk tied to real hardware experimentation. Engineers often use this approach to test new components, refine grid expansion plans, and validate safety parameters, especially when working with high-voltage networks.

Digital modeling helps shorten project timelines and lowers expenses tied to trial-and-error experimentation. The ability to run repeated simulations improves resource management, which ultimately translates into consistent system performance. Many organizations maintain a power system simulation software list to keep track of licensed options and features. Choosing the best software for power system simulation usually involves evaluating overall functionality, vendor support, and compatibility with standards relevant to your specific region or industry.


“The goal is to replicate actual system performance without the expense or risk tied to real hardware experimentation.”

 

5 Power System Simulation Software




A wide range of platforms supports grid analysis and scenario testing, and each one offers distinct capabilities. Some place emphasis on user-friendly interfaces, while others stand out with advanced scripting or high-end modeling for large-scale projects. A targeted approach starts by understanding project requirements, including load flow studies, short-circuit analysis, or electromagnetic transient simulations. Assessing each platform’s core functionality and integration options is essential before making a selection.

  • ETAP: Supports comprehensive power flow, fault analysis, and transient stability tests. It includes detailed modules for various equipment parameters and allows expansions for renewable energy studies.
  • PSCAD: Offers electromagnetic transient simulation capabilities with a visual, drag-and-drop interface and detailed libraries for power electronic devices and equipment.
  • PSS®E: Known for its robust load flow and dynamic analysis features. It is widely used for large-scale transmission and generation projects to improve system reliability.
  • PowerFactory: Delivers flexible modeling options for steady-state and dynamic scenarios. It also includes modules for protection coordination and harmonic analysis in complex grids.
  • MATLAB/Simulink with Specialized Toolboxes: Provides an open architecture for custom scripts and model-based design. It is often adopted when deeper analysis of control systems and integration with other computational tools is required.

Many power engineers use more than one option to address different study needs. Each platform carries its own licensing model, computational methods, and user community, so it is helpful to compare both technical and cost aspects. Shortlisting the best power system simulation software depends on factors such as data compatibility, modeling depth, and vendor reputation. An informed decision often involves a team that reviews relevant case studies, existing hardware requirements, and training availability.

Tips for Choosing the Best Power System Simulation Software



Many professionals begin the selection process by identifying specific tasks such as load flow optimization, harmonic analysis, or fault diagnosis. A clear definition of goals helps filter out platforms that lack key features. Assessment of your existing tech stack offers insights into compatibility concerns, including hardware, operating systems, or additional libraries. Forward-focused teams factor in expansion plans and the possibility of integrating advanced automation or cloud-based pipelines at a later stage.

Cost optimization is an important step when searching for the best software for power system simulation. Some platforms rely on modular pricing models, so you only pay for the features you require. Benchmarking performance with small prototype scenarios can reveal data accuracy and speed of computation. A supportive user community, as well as documentation and tutorials, ensures that engineers can solve practical issues without external consulting costs.

Key Advantages for Engineers and Researchers


Professional teams benefit from structured modeling and detailed computations that go well beyond simple math equations. These advanced capabilities promote informed decisions and help maintain budgetary control. Many specialists also view simulation tools as valuable platforms for addressing long-term power supply stability and grid reliability. Comprehensive data insights can unlock new avenues of growth, including potential cost savings and safer work practices.

  • Reduced Prototyping Expenses: Simulated scenarios lower the amount of physical testing, saving on labor and material costs.
  • Improved Operational Safety: Modeling hazardous scenarios in a virtual setting avoids potential harm and hardware damage.
  • Enhanced Resource Allocation: Detailed forecast data reveals the best spots for upgrades, maintenance, or expansions, increasing system productivity.
  • Scalable Solutions: Many platforms include modular additions for distributed generation or large-scale network studies, helping you keep pace with energy shifts.
  • Greater Predictive Accuracy: Algorithms factor in different variables and constraints, making it possible to test borderline cases without direct field trials.

Thorough simulation helps teams address technical bottlenecks and plan expansions with fewer surprises. Busy engineers and researchers often juggle numerous tasks, so a user-friendly interface and reliable computational engine can make a significant impact. Collaborations across engineering departments gain momentum through shared simulation data, accelerating system improvements. Balanced investment in software tools and skill development leads to consistently positive outcomes.



“Comprehensive data insights can unlock new avenues of growth, including potential cost savings and safer work practices.”

 

Practical Applications in Energy



Transmission System Reinforcement

Grid operators handling vast networks focus on load flow analysis to estimate voltages, currents, and transfer limits during peak or off-peak cycles. Comprehensive simulations highlight areas that may be prone to bottlenecks and help with cost-effective reinforcement strategies. Power system simulation tools also offer ways to experiment with parallel lines or phase-shifting transformers, identifying configurations that optimize network throughput. Entities that rely on stable transmission frameworks reduce service interruptions and preserve equipment longevity.

Distribution System Analysis

Local networks handle dynamic load patterns from residential, commercial, and small industrial sectors. Software tools generate valuable data on voltage fluctuations, transformer loading, and feeder reconfiguration strategies. Planners discover the best ways to manage growth, integrate distributed generation, and streamline localized expansions. Future-facing modules account for microgrids and smart meters, giving operators a holistic view of system behavior.

Renewable Power Integration

Solar, wind, and other green sources introduce intermittent output, which can produce significant changes to grid performance. Simulation platforms handle forecasting models and advanced scenario testing for variable generation profiles. Operators benefit from high-fidelity modeling that reflects reactive power control, ramp rates, and voltage support. Thorough planning prevents unplanned curtailments and supports consistent supply for end users.

Common Challenges in System Modeling



Thorough preparation helps address issues, but every modeling process encounters potential pitfalls. Errors can stem from inaccurate data, unrealistic assumptions, or overcomplicated models. Some engineers focus on balancing fine-grained detail with computational efficiency. A holistic view of grid conditions, along with an updated database of real operating parameters, strengthens overall results.
  • Data Collection Gaps: Missing or incomplete equipment parameters reduce model accuracy.
  • Unrealistic Assumptions: Overly optimistic or simplified load predictions can mask the true needs of the grid.
  • Complex Computation: Large networks with many nodes challenge basic hardware setups and may slow down model execution.
  • Software Limitations: Some platforms lack certain types of solvers or specialized modules, limiting advanced system studies.
  • Integration Hurdles: Legacy systems or outdated files can complicate efforts to import existing models, leading to partial results.
Realistic timelines and budgets depend on a clear understanding of these issues. Proactive teams validate data inputs and confirm that the chosen platform supports relevant analyses. Many engineers run a set of smaller pilot simulations to refine assumptions and eliminate errors. This method prevents lost time and sets the stage for dependable, large-scale modeling results.

Connecting Key Insights for 2025


Simulation ecosystems continue to expand with options ranging from local deployments to cloud-based workflows. Thorough planning of budget, technical requirements, and training opportunities helps you stay prepared for new energy architectures. Many professionals foresee deeper penetration of renewables and demands on grids that require agile, data-driven responses. Software selection that balances advanced functionality with ease of use can support a future of consistent power delivery, efficient maintenance, and measured growth.

Engineers and innovators around the world are turning to real-time simulation to accelerate development, reduce risk, and push the boundaries of what’s possible. At OPAL-RT, we bring decades of expertise and a passion for innovation to deliver the most open, scalable, and high-performance simulation solutions in the industry. From Hardware-in-the-Loop testing to AI-enabled cloud simulation, our platforms empower you to design, test, and validate with confidence. 

Common Questions About Power System Simulation Tools



Many engineers choose specialized software designed for high-capacity networks, such as PSS®E or PowerFactory. These platforms handle complex calculations with efficient solvers and advanced libraries.

A documented list streamlines decision processes, budget checks, and feature comparisons. It also helps engineers avoid confusion when selecting software updates or expansions.

These solutions account for variable generation, inverter-based resources, and grid constraints in ways that traditional approaches may overlook. Scenario testing identifies points of stress and suggests operational improvements.

Decision factors include licensing options, available modules, and support agreements. Some open-source platforms or modular licensing models lower expenses while still offering robust features.

Engineers often combine solutions for specific tasks, such as electromagnetic transient analysis or distribution automation studies. This approach helps cover different aspects of network performance without overburdening a single platform.


 

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OPAL-RT’s HYPERSIM & SCALABLE’s EXata CPS: Real-Time Cyber-Physical Simulation of the Electric Power Grid for Cybersecurity Studies

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The Status Quo
21st century power grids face a number of make-or-break challenges on the Infrastructure/Security/Wide-Area Monitoring, Protection and Control fronts, notably mixed and hybrid old/new analog/digital equipment; newer energy sources like wind and solar integrated into older networks; as well as faster-switching converters and newer digital equipment that make the grid ‘smarter’, more sustainable, future-proofed and flexible—but that also leave it open to all the vulnerabilities associated with networked resources and communications.











Smart Grids & Their Inherent Complexities…
Modern power grids have become Cyber-Physical Systems (CPS) composed of electrical and communication infrastructure. As opposed to the analog networks of, say, 100 years ago that were made of cables and switches and hardware, today’s grids are studded with communications, administration and protection equipment that has been being ushered in for its precision and superior oversight functions since the dawn of the digital age.

Today’s grid is becoming more ‘intelligent’ through the:

  • Wide deployment of new technologies
  • Substation, transmission and distribution automation
  • Increased Distributed Energy Resources (DER) integration
  • Advanced two-way communication networks, and the
  • Development of synchro phasor systems














However, as an unavoidable consequence of the above, as newer technologies are adopted, the grid is becoming more vulnerable to cybersecurity threats of all kinds as well as communication equipment failures. Mixed technologies are harder to test; hybrid networks offer unique challenges as diagnostics for one simply aren’t adequate solutions for the other.











…& the Real-World Outcomes
We have seen that connecting Supervisory Controls and Data Acquisition (SCADA) systems and Operational Technology (OT) devices via the internet has significantly improved accessibility, automation, and efficiency of vast networks, but it also introduces vulnerabilities.

Without hyperbole, we can say that this makes every communication line a potential attack surface. Because of this, cyber threats against public utilities and other critical infrastructure are just as ubiquitous as attacks on government and corporate computing infrastructures.

These attacks may cause loss, and/or denial of access or manipulation of system views and control. Cyber-attacks against SCADA systems, such as power generation and distribution systems, water treatment plants, and transportation facilities, can cause widespread disruption of commerce and daily life.



Besides cyber-attacks, a larger amount of communications equipment also means more potential for human error, operator carelessness or negligence, and equipment failures that can also lead to serious consequences.



“There is a pressing need for operators of SCADA systems, microgrids, substations and other infrastructures to determine how resilient their operational systems are to cyberattacks and to develop plans to mitigate the associated risks.”











The Partnership











This is why 2018’s partnership between OPAL-RT and SCALABLE was so exciting and groundbreaking for both parties:
OPAL-RT TECHNOLOGIES are experts in real-time simulation of power systems and power electronics:





  • We provide real-time simulation technology and engineering R&D, both of which are used extensively in the development and testing of operational technology within the electric power grid.


            • We’re focused on improving the security and reliability of systems used to control, protect and monitor the grid.










    SCALABLE Network Technologies are experts in real-time simulations of communication network infrastructures:





        • Their EXata network emulation platform, with its cyber library of simulated attacks and vulnerabilities, is used to analyze and test the resilience of critical communication networks effectively.


            • Tools like EXata CPS allow customers to visualize their specific environments in a manageable laboratory setting and quickly evaluate a range of ‘what if’ scenarios to determine the impact on their systems if subjected to cyber-attack.


    The Much-Awaited HYPERSIM 2019.2, Featuring EXata CPS



























    The companies’ collaboration has borne fruit in HYPERSIM 2019.2:

    “EXata CPS is integrated in HYPERSIM 2019.2 on the same hardware to offer a complete real-time cyberphysical solution for the development, testing, and assessment of electrical grids with communication networks,” said Etienne Leduc, Product Owner of HYPERSIM. “HYPERSIM, which simulates the physical system, is the only real-time digital simulator with the power to simulate electromagnetic transients of large-scale power systems, tackling operational and reliability issues threatening a power system’s cybersecurity. This integration of EXata CPS and HYPERSIM provides a means to test the resilience of power systems to cyber-attacks and improve their cyber defenses, thereby helping to ensure cybersecurity, reliability, and efficiency of such systems.”






    Typical Configuration/Application










    The figure below shows the integration between the OPAL-RT simulator, at left, communicating with both EXata CPS and the devices under test (controllers or ECUs or other networked IT/Security devices) with monitoring, storing and interaction abilities, represented to the right.







    Types of Attack Supported
    The hybrid best-in-class duo of HYPERSIM and EXata CPS can model any number of types of attacks.

    The most significant attacks which can impact power systems are:
















                              • Denial of Service (DOS): These attacks can bring down or make unavailable a critical piece of equipment
                              • Packet Modification Attacks: These attacks make changes to the payload of packets and can result in:







                                        • Bogus input, such as modified sensor data, which can lead to erroneous decisions by the controllers
                                        • Bogus output, such as manipulated or misleading data sent, which can lead to unintended or incorrect actions 





























                                                    Communications Protocols Supported


                                                    Both companies’ support of Communication Protocols is extensive, as is evidently required in a context entirely dependent on I/O, digital communications and both IT and security infrastructure:





                                                    EXata CPS communicates with HYPERSIM through the following protocols:





















                                                                              • Generic Object-Oriented Substation Events (GOOSE), a subset of IEC 61850
                                                                              • 118 (over TCP/IP), used by synchrophasors
                                                                              • DNP3 (over TCP/IP)
                                                                              • Modbus (over TCP/IP)
                                                                              • IEC 60870-5-104 (over TCP/IP)

















                                                                                  Two Sample Attacks: Scenarios










                                                                                  The following graphic depicts the SCADA dashboard where two possible scenarios are modeled and simulated using the hybrid HYPERSIM/EXata CPS toolbox:






                                                                                  Scenario 1









                                                                                  In Scenario 1, we simulate a message delay attack once the grid is islanded:
















                                                                                                            • As there’s not enough generational power for all the loads in this microgrid, the residential load L1 needs to be shed upon islanding the grid






















                                                                                                                                          • By delaying the GOOSE message aimed at the breaker by 3 seconds, the frequency and voltage become unstable, which can lead to equipment damage or backup protections kicking in

















                                                                                                                                              Scenario 2









                                                                                                                                              In Scenario 2, while islanded, we simulate a packet value multiplication attack:
















                                                                                                                                                                        • By intercepting the power measurement of the L2 industrial load going to the microgrid controller and multiplying its value by 2, the controller thinks that it needs to react as there’s not enough generational power for all the loads






















                                                                                                                                                                                                      • In consequence, the residential load L3 needs to be shed by the microgrid controller, cutting power for families and small businesses






























                                                                                                                                                                                                          Highlights of this Article








                                                                                                                                                                                                        • OPAL-RT and SCALABLE partner to develop joint cybersecurity solutions based on OPAL-RT’s proven real-time simulators and solvers and SCALABLE’s accumulated expertise in cyber-physical security. Learn more >
                                                                                                                                                                                                        • EXata CPS, SCALABLE’s flagship CPS solution is supported in HYPERSIM 2019.2, OPAL-RT’s premiere real-time simulation platform for power systems and power electronics. Learn more >
                                                                                                                                                                                                        • OPAL-RT and SCALABLE co-host what promises to be a valuable and illuminating webinar on ensuring the safety and protection of electric power grids with OFFIS as special guest. Learn more >
                                                                                                                                                                                                        • OPAL-RT and SCALABLE published a white paper on this collaboration in August Learn more >


                                                                                                                                                                                                          •



                                                                                                                                                                                                          Traveling Wave Relay Testing

                                                                                                                                                                                                          /in , /by

                                                                                                                                                                                                          When we last spoke with Shijia Li, in November, she told us about Protection Relay Testing. She has since been made team leader for Protection and Smart Grid team within OPAL-RT’s AXES (Application, eXpertise and Electrical Simulation) division. This time, she is speaking to OPAL-RT Product News about OPAL-RT’s HIL Traveling Wave Test System.
                                                                                                                                                                                                          —

                                                                                                                                                                                                          Interviewer (IV): “Hello Shijia. First, can you tell us when we introduced the Traveling Wave test system?”

                                                                                                                                                                                                          Shijia Li (SL): “We developed it about 1.5 years ago.”

                                                                                                                                                                                                          IV: “Our software has been simulating faults on FPGAs for a while; why hadn’t we used this method previously?”

                                                                                                                                                                                                          SL: “Previously, the FPGA had not been used for protection system testing. It was used for simulating power electronics devices, or motors or drives, but not to simulate a power system with transmission lines, etc. This was the first time we’d tested the power system components on the FPGA; it was a new way to use the FPGA. It has the fast time step required to precisely locate (within a few meters) and diagnose faults on power system lines.”

                                                                                                                                                                                                          IV: “So prior to that, all protection was run on CPU? How did we make this breakthrough?”

                                                                                                                                                                                                          SL: “This actually came about because of a request from a client. They built a device containing an algorithm and needed a way to test it. The conventional tests [Editor’s note: CPU-based] wouldn’t work with their device, so we had to use an FPGA model to achieve a much smaller time step. We had an engineer developing a model–more of a mathematical model–to make it run much faster on an FPGA. That innovation also prompted us to improve our solver. The client’s engineers were so impressed with the results from our constant parameter (CP) line model that they’re eager to see our frequency dependent (FD) line model.”

                                                                                                                                                                                                          IV: “So we currently have two different line models?”

                                                                                                                                                                                                          SL: “As of now, we only have the CP line model, but our R&D department is finalizing the FD line model.”

                                                                                                                                                                                                          IV: “What’s the difference between the two models?”

                                                                                                                                                                                                          SL: “The FD line model more accurately represents overhead lines than the CP model. It has a richer harmonic content, which represents with higher fidelity a line during a fault; with the FD line model, we’ll be able to test single-ended TW fault locating algorithms, which is more challenging.”

                                                                                                                                                                                                          IV: “Impressive. This is a fairly new innovation, then, FPGAs being used to do work this precise, in this context?”

                                                                                                                                                                                                          SL: “Yes. The travelling wave is a very high-frequency phenomenon, so it requires faster simulation as well as faster hardware. Our usual I/O boards take one sample every microsecond, which is sufficient for simulations in the range of 10 to 50 µs, but when simulating the travelling wave phenomenon at 500 ns on the FPGA, we need I/O boards that can follow at this speed, to get better accuracy. Fortunately, we already have a board with a sampling rate of 2 MS/s.”

                                                                                                                                                                                                          IV: “What did utilities do before this? Did they simply say, ‘there’s a fault somewhere between kilometre 364 and 365’, for example?”

                                                                                                                                                                                                          SL: “We could say that. There are other ways of detecting the fault location that are not as accurate as this one; it really depends on the manufacturer. It is, for example, often expressed in a percentage of the setting, which relates to the length of the line, so the longer the line, the lower the accuracy.”

                                                                                                                                                                                                          IV: “This was a breakthrough in terms of narrowing the range?”

                                                                                                                                                                                                          SL: “Yes, absolutely. And this idea was floated a long time ago, but, at the time, the relay itself didn’t have enough computational power. The processor wasn’t fast enough to run the algorithm. But since technology has evolved, they can implement it on the hardware. To understand how much of a breakthrough that is, you have to look at it in the operational context. When there’s a fault on a line, there are some strategies that can be used to avoid sending out a team to investigate. These strategies vary from one utility to the next and are based on the environment around the fault location. Since there aren’t cameras everywhere, some assumptions must be made.”

                                                                                                                                                                                                          “For example, in rural areas, some might successively reclose and reopen breakers to try and clear a fault (in case a tree fell on a line, for example) to liberate the line. If every automated strategy fails, or, in dense urban areas, it is most often necessary to send out a team to investigate, which can be very costly. If the team has to search over a few kilometres for the location of the fault, it can take a lot of time. It’s even more difficult, for obvious reasons, with cables that are buried underground. Travelling wave relays might mean a high-cost reduction in many cases. This is the breakthrough.”

                                                                                                                                                                                                          IV: “This is an HIL process, right?”

                                                                                                                                                                                                          SL: “Yes, this is a hardware-in-the-loop (HIL) process, but obviously not on the lines themselves. There are testers that can be used in the field to perform simple signal injection tests. But what we’re doing is more in the lab: we’re using the same devices, the same settings. The device we are testing is monitoring the line. What we’re doing is we’re replacing that actual power line with our simulator: we send signals to the device, but the device is monitoring the lines on the simulator.”

                                                                                                                                                                                                          IV: “And the larger context for this is control and protection, one of your specialties. Was travelling wave testing something people had wanted to do for a while?”

                                                                                                                                                                                                          SL: “Well, it is not a new idea, but it’s not that long since it has actually been put into use. It is a new feature, and we do have customers expressing interest in it. Generally speaking, in the context of the protection industry, this would be considered an innovation: it’s not been widely used or adopted by most utilities. And we’re seeing some of our clients out there in the early stages, trying to convince people to adopt this technology.”

                                                                                                                                                                                                          IV: “How does this technology fit in, in terms of the industry in general?”

                                                                                                                                                                                                          SL: “The protection and control sectors are very well-established, mature sectors or fields, within the power system industry. The current devices and schemes or implementations we have are good enough to protect most power systems. For now, there are some new perspectives—the broader introduction of renewable energy—that may introduce some new challenges. And travelling wave technology, which brings a challenge in terms of testing: this is ultimately why we’re developing this solution.”

                                                                                                                                                                                                          “The microgrid also, and its protection, is a very hot topic in this field. Other than that, from the communication-aided protections: we use more and more fibre optics, so that’s something we could test as well. And that brings us to the IEC61850 digital substation concepts [Editor’s note: Product News blog post to come]: so let’s say, with one relay now, we can do a lot of complex functions and so, of course, the testing becomes exponentially more complex as well.”

                                                                                                                                                                                                          IV: “Thanks for speaking with us again, Shijia.”

                                                                                                                                                                                                          —

                                                                                                                                                                                                          About the Interviewee


                                                                                                                                                                                                          Shijia Li received her Bachelor’s degree from Zhejiang University, China in 2012 and Master’s degree from McGill University, Canada in 2015, both in the field of power engineering. She joined OPAL-RT in March 2015, where her work focuses on power system modelling and real-time simulation applications with protective relays and PMUs. Shijia is actively involved in developing technical solutions and providing advanced training to help users better utilize real-time simulation techniques for exploring the latest P&C/smart grid technologies. Currently, Shijia leads the Protection and Smart Grid team in OPAL-RT’s AXES (Application, eXpertise and Electrical Simulation division).