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May 13, 2025
A Guide to Hardware-in-the-Loop (HIL) Testing in 2025
Hardware-in-the-loop testing gives engineering teams the confidence to launch groundbreaking solutions without risking product failures.
This approach combines physical hardware with simulated conditions to deliver practical, real-time insights. Many organizations struggle to validate complex control systems swiftly and cost-effectively. HIL testing stands out as a proven method that aligns with goals for speed, scalability, and measurable returns.
Teams in automotive, aerospace, and power systems now view hardware-in-the-loop setups as a powerful option for high-fidelity validation. Results gleaned from these tests guide improvements that support a demanding development timeline. Each new test scenario produces data that can reshape the next iteration of hardware or software designs. Users also appreciate the flexibility to replicate varied conditions without building multiple physical prototypes.
What Is Hardware-in-the-Loop (HIL) Testing?
“Hardware-in-the-Loop testing is an important method for validating complex control systems in real time.”
Hardware-in-the-Loop (HIL) testing is a real-time simulation technique used to validate and test embedded control systems by connecting them to a high-fidelity digital simulation of the physical system they control. Instead of testing with actual hardware prototypes, engineers use real-time simulators to replicate the behavior of complex systems such as electric vehicles, aircraft, or power grids, allowing the controller to interact with the virtual environment as if it were operating the real system. This enables faster, safer, and more cost-effective development by identifying issues early, reducing the need for physical testing, and accelerating time-to-market.
The term HIL stands for Hardware-in-the-Loop, and it involves a test bench where software algorithms interact with physical hardware in a controlled setup. This structure provides a safer, more cost-effective route to prototyping systems that need hands-on verification. The methodology is considered a key factor in accelerating time-to-market and enhancing confidence that a product will meet functional and safety requirements.
Key Components of HIL Systems
Real-time simulation demands several interconnected pieces of equipment and software to replicate realistic signals. Core components are specifically chosen to guarantee high-fidelity system responses, stable performance, and actionable results for the development team. Examining each item in detail sheds light on why HIL test benches have become essential to many product validation workflows. Understanding these individual elements can improve cost-efficiency while raising the overall quality of final designs.
Real-Time Simulator: This system processes your plant model or software architecture with sub-millisecond execution times. It includes high-performance CPUs or FPGA-based systems that can precisely replicate intricate dynamics.
I/O Interfaces: These ports connect the simulator to physical devices such as sensors or actuators. They collect incoming signals in real time while sending outputs to the hardware under test.
Physical Hardware Under Test: Controllers, embedded units, or partial mechanical assemblies are often integrated. This direct inclusion means your testing scenario reflects actual hardware constraints.
Power Conditioning and Signal Conditioning Units: These ensure voltage and current levels align with the operational requirements of both the hardware and the simulator. Stable signal management is crucial for accurate correlation between the virtual and physical elements.
Control and Monitoring Software: This software suite logs performance data and aids in generating test scenarios. It provides an intuitive interface to manage real-time interactions and observe outcomes.
Teams often tailor these pieces to match specific application needs, making them easy to scale as projects grow larger. The collection of elements also lays a solid foundation for robust test methodologies. Seamless communication among hardware, I/O, and the real-time simulator reveals how each subsystem responds under variable conditions. This synergy highlights the benefits that come from implementing HIL testing as a standard practice.
Benefits of Implementing HIL Testing
Design teams frequently look for ways to shorten development cycles and cut costs without compromising reliability. HIL setups address these objectives through consistent, repeatable test scenarios that reflect actual operating parameters. The approach brings measurable advantages, from minimizing the chance of expensive late-stage failures to improving stakeholder alignment.
Reduced Risk of Product Failures: Testing with real hardware under simulated conditions helps identify faults and inconsistencies early in the design process. By resolving issues before physical deployment, teams reduce the likelihood of costly recalls and protect their brand’s reputation.
Accelerated Development Time: HIL testing allows engineers to detect and correct errors more efficiently than traditional validation methods. This leads to faster iteration, quicker approvals, and a shorter time-to-market, all while maintaining high quality standards.
Greater Scalability: Modular HIL platforms make it easy to adapt as project complexity grows. Whether scaling to larger systems or integrating new components, the flexibility of HIL systems supports testing requirements without needing a complete overhaul.
Lower Overall Costs: Simulating real-world conditions in a lab environment significantly reduces the need for physical prototypes and field testing. The cost savings can be reinvested in design improvements, advanced analytics, or other areas of innovation.
Improved Collaboration Across Disciplines: HIL systems provide a shared testing environment that brings together electrical, mechanical, and software engineers. This encourages stronger teamwork, clearer communication, and more informed decision-making throughout the project.
Companies investigating hardware in the loop testing often find that adopting it fosters cost savings and quicker time-to-market. HIL stands out as a powerful step forward for anyone aiming to produce safer, more efficient systems. Thorough testing with hardware in the loop translates directly into greater trust in each subsystem. A closer look at challenges in HIL testing reveals strategies for handling any obstacles that appear during adoption.
Challenges in HIL Testing
Missteps at this stage can undermine even the most sophisticated validation approach. Some teams struggle with setup complexities or worry about the amount of time spent fine-tuning models. Awareness of specific hurdles allows for more efficient deployment of hardware-in-the-loop systems.
Complex Integration: Multifaceted electronics and software can complicate data exchange. Early planning of I/O and communications protocols removes uncertainty and improves performance.
High Initial Investment: Specialized hardware and real-time simulators can seem expensive. Selecting scalable options and phasing deployment can make adoption more cost-effective.
Model Accuracy Issues: Simulation fidelity must align with actual hardware to provide accurate test results. Using validated reference models and continuous verification addresses these inconsistencies.
Hardware Limitations: Sensors or actuators might have range constraints or other physical restrictions. Maintaining robust component libraries and upgrading key equipment helps keep tests relevant.
Skill Gaps: Real-time simulation is a specialized field, and not all teams have the necessary expertise. Offering training programs and collaborating with experienced consultants can shrink this knowledge gap.
By taking practical steps such as investing gradually, improving model validation, and upskilling teams, organizations can overcome these common HIL challenges. With the right approach, engineers can unlock the full potential of HIL testing and apply it across a wide range of applications, from electric vehicle development to advanced aerospace systems.
Applications of HIL Testing Across Industries
Many fields integrate hardware-in-the-loop strategies to achieve specific goals, whether they revolve around safety, performance, or adherence to strict regulations. Engineering teams look for proven ways to replicate real signals without subjecting equipment to uncertain operating conditions. HIL systems provide a controlled, repeatable testbed that refines design choices with authentic data. The following sections explain how various sectors benefit from this powerful validation method.
Automotive
Car manufacturers rely on HIL setups to validate engine control units, powertrains, and advanced driver-assist functions. Testing each component under scenarios that mimic realistic road conditions refines design outcomes before physical prototypes are finalized. This reduces time spent on repeated test drives and lowers the potential for on-road malfunctions. HIL testing also supports the growing shift toward electric and autonomous vehicles by providing a thorough way to check complex control algorithms.
Aerospace
Flight control systems and avionics require extensive verification to meet stringent safety criteria. Simulating flight conditions with a HIL rig uncovers vulnerabilities that might be overlooked during purely software-based evaluations. This approach helps maintain compliance with regulatory standards while controlling project budgets. Comprehensive hardware-in-the-loop tests also enhance confidence in new designs for drones, satellites, or next-generation aircraft.
“This approach helps maintain compliance with regulatory standards while controlling project budgets.”
Energy and Power Electronics
Power converters, inverters, and grid protection systems need thorough testing under shifting load requirements and electrical disturbances. Hardware-in-the-Loop frameworks offer a safe laboratory setup for verifying the performance of high-voltage or high-current devices. Engineers can introduce faults at the simulator level to measure how hardware responds without risking substation or field equipment. This flexibility helps power utilities and manufacturers confirm reliability while managing operational costs.
Research and Academia
Universities and research institutions incorporate HIL benches to investigate advanced control methods for robotics, mechatronics, and emerging technologies. This hands-on approach exposes future engineers to high-fidelity simulation and fosters practical problem-solving skills. Many projects revolve around refining hardware prototypes for everything from biomedical devices to next-generation automotive concepts. Access to hardware-in-the-loop resources encourages deeper exploration and sparks new ideas in engineering programs.
HIL vs. Software-in-the-Loop (SIL) Testing
The main difference between hardware-in-the-loop (HIL) testing and software-in-the-loop (SIL) testing involves how each framework integrates physical equipment. SIL methods rely on simulation alone, whereas HIL includes actual hardware components to increase test fidelity. Many design teams use SIL as a preliminary check for software algorithms, shifting to HIL when hardware prototypes become available. Understanding this progression clarifies when to choose one method over the other or integrate both in a single workflow.
Aspect
HIL
SIL
Hardware Involvement
Physical hardware is integrated
Entirely software-based
Accuracy
Higher accuracy with physical components
Suitable for early-stage validation
Cost Implications
Higher upfront costs for hardware
Generally lower initial costs
Safety Considerations
Ensures real hardware is tested safely
Pure simulation poses fewer safety risks
Scalability
Can be scaled with modular hardware
Scales quickly with computational resources
Teams that focus on cost optimization often start with SIL to verify control logic. HIL solutions follow as designs progress and more tangible validation becomes necessary. This combination keeps risk levels low while still allowing advanced testing of physical components. Each step introduces new insights that refine software, hardware, or both.
Steps to Implement HIL Testing in Your Development Process
Adopting hardware-in-the-loop techniques calls for strategic planning that covers hardware selection, model fidelity, and operational workflows. Many teams discover that a structured rollout prevents expensive mistakes and reduces training overhead. Following a series of precise steps helps integrate HIL into existing processes without disrupting ongoing product cycles.
1. Define Clear Objectives
Set measurable goals linked to product performance, safety, or regulatory compliance. This clarity helps your group focus on the most important components that need thorough hardware-in-the-loop validation. Relevant stakeholders can prioritize resources more effectively, reducing extra complexity. A well-defined objective sets the benchmark for evaluating the effectiveness of each test session.
2. Build a High-Fidelity Model
Accurate plant models or software simulations underpin any HIL setup. These models must reflect operational parameters, from sensor timings to actuator ranges. Teams often refine them repeatedly until they mirror actual performance with minimal error. This level of detail catches subtle issues and raises overall confidence in the test results.
3. Integrate Real-Time Hardware
Select compatible data acquisition systems, real-time CPUs or FPGAs, and I/O units that handle your project’s signal requirements. Each piece of hardware should align with your existing infrastructure to minimize complications. Early synergy between software and physical components speeds up the testing phase. Consistent calibration ensures the hardware responds exactly as expected.
4. Conduct Rigorous Validation
Run your test scenarios repeatedly under varied operating conditions, including extreme edge cases. This approach pushes both the hardware and software to their limits, revealing hidden flaws. Thorough documentation keeps track of all test outcomes, making it easier to resolve issues or replicate successes. Evaluating this data helps stakeholders make well-founded decisions on final design changes.
5. Refine and Scale for Growth
Gather insights from each test cycle to refine models, hardware configurations, or software algorithms. Version control and a clear revision strategy simplify collaborative efforts. Teams often expand the scope of HIL tests as they add more functionalities or address new market needs. A cycle of continuous improvement ensures the testing framework remains an integral part of future projects.
Once a team fully understands hardware-in-the-loop HIL testing, a structured plan like this significantly increases the likelihood of success. Each step lays the groundwork for reproducible validation, lowering the possibility of unforeseen issues. This structured path accommodates short timelines while containing costs. Key developments on the horizon confirm that HIL remains central to modern testing strategies.
Future Trends in HIL Testing
Hardware-in-the-loop setups are constantly expanding their capabilities to meet higher accuracy standards and adapt to complex multi-physics models. The continued adoption of AI-based techniques adds more predictive power to HIL frameworks, allowing tests to cover an even broader range of scenarios. Engineers seek more modular architectures that can accommodate everything from electric vehicles to next-generation aerospace designs. These developments highlight a push for advanced computational solutions that still provide a user-friendly interface.
Remote testing through cloud services also stands out as a practical direction for organizations with global teams. Real-time data sharing leads to faster optimization cycles and quicker paths to production-level solutions. More industries are discovering that a robust HIL infrastructure supports groundbreaking ideas while reducing overall risk. Each new feature or approach supports the drive to extend the reach of hardware-in-the-loop testing beyond its original boundaries.
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 HIL Testing
What is HIL used for?
HIL is used to replicate realistic conditions for validating control systems, embedded software, and mechanical components. Development teams gain valuable performance data without building excessive physical prototypes. This method helps lower costs, manage risks, and produce confident outcomes.
Why is hardware-in-the-loop important for time-to-market?
Hardware-in-the-loop shortens validation cycles by uncovering defects at an earlier stage. Repeating tests with real hardware in a lab setup reduces delays associated with late design changes. Each iteration progresses faster and aligns development goals with market release schedules.
How does HIL compare to pure software testing?
Pure software testing focuses on simulated scenarios without incorporating physical hardware. HIL testing merges simulation with actual components, increasing the accuracy of results. Many teams find that combining both methods provides well-rounded validation for critical projects.
Can HIL testing lower overall project costs?
Practical hardware-in-the-loop setups reduce the need for multiple physical prototypes and full-scale field tests. Precise data captures anomalies before they become costly fixes. This leads to efficient resource allocation and higher returns on your project budget.
What does HIL mean for cross-functional collaboration?
HIL stands for Hardware-in-the-Loop, and it allows various disciplines to test designs within a single, unified setup. Mechanical, electrical, and software teams gain immediate insights into how systems interact. This shared perspective fosters deeper collaboration and more informed results.
Hardware-in-the-Loop (HIL) testing is a proven method that…
https://www.opal-rt.com/wp-content/uploads/2025/04/hil_testing_in_automotive_hero_banner.png.png6301200Jared Foxworthy/wp-content/uploads/2016/03/logo_opal_blanc.pngJared Foxworthy2025-04-23 09:30:422025-05-13 10:41:07What Is HIL Testing in Automotive?
Knowledge Box: Introduction to Linux, Networking and More!
This course offers a diverse blend of essential background knowledge designed to equip you with the skills needed for any project related to communication protocols and/or Linux.
This course was originally built to provide background knowledge for the OPAL-RT and EXata co-simulation setup, but since then, it has been improved to yield a bigger reach.
You will learn more about the following: – Shell Terminal, SSH and MobaXterm – Linux, and the history of Linux at OPAL-RT – Analyzing network protocols using TShark and Wireshark – Understanding better the fundamental concepts of networks – and more!
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP101: RT-LAB - Real-Time Simulation Systems Fundamentals
This course introduces OPAL-RT systems and applications using RT-LAB. This course is a prerequisite for eMEGASIM, eFPGASIM, and ePHASORSIM. RT-LAB is used in a variety of domains, including power systems, power electronics, automotive applications, aerospace, mechatronics and more.
Prerequisites: • Basic knowledge of Matlab®/Simulink®
GOALS: – Learn the fundamentals of real-time simulation – Get started with RT-LAB Software – Understand when and how to use distributed and parallel real-time simulation – Connect models with I/Os
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP102 - HYPERSIM - Introduction to Power Systems Real-Time Simulation
This course teaches the basics of the HYPERSIM® real-time simulation software platform and its operating principles.
GOALS: – Understand the operating principles of HYPERSIM® – Use ScopeView to analyze results – Build and run a number of control and power system simulation cases showing the capabilities of HYPERSIM® – Connect models with I/Os
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP103: Introduction to Power Electronics Real-Time Simulation with OPAL-RT Add-On for NI VeriStand
This course covers the configuration of a real-time system using the OPAL-RT Power Electronics Add-On for NI VeriStand on the National Instruments hardware platform.
Goals: – Learn the fundamentals of real-time simulation – Review the basics of NI VeriStand and the NI hardware platforms – Understand FPGA-based simulation of power electronics using the eHS solver
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP204: Electro-Mechanical Real-Time Simulation with ePHASORsim
This course is intended for new ePHASORsim users who want to learn Phasor Domain real-time simulation. ePHASORsim simulates electro-mechanical transient stability phenomena of very large power grids with thousands of buses, generators, transformers, transmission lines, loads and controllers.
Prerequisites: • OP-101: RT-LAB – Real-Time Simulation Systems Fundamentals
GOALS: – Understand the concept of Phasor Domain simulation features, benefits and limitations – Import PSS/E, DIgSILENT or other model-based design tools into ePHASORsim – Connect I/Os and communication buses with ePHASORsim – Learn about the interaction of ePHASORsim and RT-LAB
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP205: Power Electronics Real-Time Simulation with eHS
This course is intended for power electronics and control engineers who want to perform fast power electronics real-time simulation using the combined power of FPGA and OPAL-RT’s unique dedicated solver eHS.
Prerequisites: • OP-101: RT-LAB – Real-Time Simulation Systems Fundamentals
GOALS: – Discover the features, flexibility and limitations of FPGA for power electronics real-time simulation – Understand the overall architecture of real-time simulator between processors and FPGA – Experience first-hand power electronics real-time FPGA applications using eHS solver
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP203: ARTEMiS - Power Systems Real-Time Simulation
This course is intended for professionals who want to simulate power systems with ARTEMiS by converting their Simulink‘s SimPowerSystems™ based model into a complete HIL system.
Prerequisites: • OP-101: RT-LAB – Real-Time Simulation Systems Fundamentals
GOALS: – Learn how to run power systems models in real-time for HIL applications – Take advantage of dedicated toolboxes for real-time simulation of power systems and power electronics – Understand Artemis-SSN, State-Space Nodal solver, as well as its applications – Learn how to improve the real-time simulation switching results with RT-EVENTS – Learn how to adapt your SimPowerSystems model for real-time simulation
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP205: Power Electronics Real-Time Simulation with eHS
This course is intended for professionals who want to simulate power electronic circuits with our FPGA-based solver: eHS. This toolbox provides the flexibility and speed required for very fast power conversion applications for HIL simulation.
GOALS: – Learn how to run power electronic circuits in real-time for HIL applications – Take advantage of FPGA high performance for solving power electronic circuits in real-time – Learn how to design your power electronic circuits with the OPAL-RT Schematic Editor – Learn how to implement a control algorithm on CPU for your power electronic circuits – Learn how to interface your power electronic circuits design with external controller – Learn how to simulate faults on power electronic converter circuits
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
This course is intended for new ePHASORSIM users who want to learn Phasor Domain real-time simulation. ePHASORSIM simulates electro-mechanical transient stability phenomena of very large power grids with thousands of buses, generators, transformers, transmission lines, loads and controllers.
Prerequisites: • OP101: RT-LAB – Real-Time Simulation Systems Fundamentals
GOALS: – Understand the concept of Phasor Domain simulation features, benefits and limitations – Import PSS/E, DIgSILENT or other model-based design tools into ePHASORSIM – Connect I/Os and communication buses with ePHASORSIM – Learn about the interaction of ePHASORsim and RT-LAB
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP103: Introduction to Power Electronics Real-Time Simulation with OPAL-RT Add-On for NI VeriStand
This course covers how to use the FPGA-Based electric hardware solver (eHS) on the Power Electronics Add-On for NI VeriStand, developed by OPAL-RT, with NI’s VeriStand software to give a user the tools necessary to test power electronics and electric motors in real-time.
GOALS: – Learn the fundamentals of real-time simulation – Review the basics of NI Veristand and the NI hardware platforms – Understand FPGA-based simulation of power electronics using the eHS solver – Configure the real-time system using the Power Electronics Add-On for NI Veristand – Connect to physical systems using I/O channels
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
OP213: Integration of EXata CPS with RT-LAB / HYPERSIM
This course covers the cyber-physical co-simulation setup between Keysight’s EXata CPS and OPAL-RT’s RT-LAB / HYPERSIM. Learn how to install EXata CPS on your computer, license the software, and go through step-by-step examples on how to implement faults, cyber attacks and integrate both software.
GOALS: – Learn how to install and configure the EXata CPS software – Go through different step-by-steps showing how to couple the two software – Implement your first cyber-attacks and analyze the impacts – Connect an external device to your co-simulation setup
Note: All self-paced e-Learning courses are available for free for OPAL-RT customers.
Dr. Ron Brandl completed his studies in electrical engineering in 2010 and received his doctorate in engineering from the University of Kassel in 2018. Since 2011, Ron Brandl is working as a research associate at the Fraunhofer Institute for Energy Economics and Energy System Technology – IEE, where he heads the group ‘Power Electronics Applications’ and is part of the Fraunhofer Competence Center ‘Cognitive Energy Systems’. Additionally, Ron Brandl is working as project manager and researcher at the European Distributed Energy Resource Laboratories e.V. – DERlab since 2018. His expertise covers topics such as real-time simulations, power hardware-in-the-loop technology, power electronics and system stability, electromobility and AI in energy. He is involved in the design of test centers for smart grids, participates in various national and European research projects, is part of several working groups, such as the IEEE Task Force “Real-Time Simulation of Power and Energy Systems”, the IEEE P2004 Working Group “Recommended Practice for HIL Simulation Based Testing” and he is National Expert and Operating Agent of the IEA-ISGAN Annex 5 “Smart Grid International Research Facility Network”.
Dr. Danielle Nasrallah
Biography
Danielle Sami Nasrallah received an Engineer’s diploma in electromechanical engineering and a Diplôme d’Études Approfondies in electrical engineering from École supérieure d’ingénieurs de Beyrouth (ÉSIB), Beirut, Lebanon in 2000 and 2002, respectively, and a Ph. D. degree in Robotics Modelling and Control from McGill University, Montreal, QC, Canada, in 2006. During her Ph. D. studies she worked on a part-time basis at Robotics Design as a control and robotics engineer. She moved to Meta Vision Systems in 2006-2007 as a control and applications engineer.
In 2008, she joined the electrical department of the Royal Military College of Kingston as an assistant professor and, in 2009, she was a visiting assistant professor at the American University of Beirut. From 2010 to 2014, she worked as a consultant in control and systems engineering. In 2014, she joined OPAL-RT TECHNOLOGIES where she is presently a technical lead in control and intelligent mobility. She retained links with academia as she lectures in Robotics and Control at both Concordia and McGill Universities.
Sebastian Hubschneider
Biography
Sebastian Hubschneider finished his studies of electrical engineering and information technology at the Karlsruhe Institute of Technology (KIT) in June 2015 with the academic degree Master of Science. During his time at the University, he specialized in power engineering with a focus on energy grids and the energy sector in general, including markets and the economy.
Since July 2015, Sebastian works as a research associate at the Institute of Electric Energy Systems and High-Voltage Technology (IEH), KIT. His research focuses on Power Hardware-in-the-Loop systems in conjunction with energy grids and electrical equipment.
Mike Mekkanen
Abstract
The development process of the microgrid controller (MGC) is that we first develop the controlling function in C that matches with the SIL preliminary algorithm developed by OPAL-RT/HYPERSIM. Secondly, a real HIL lightweight IED controller based on an iec61850 library is developed. Thirdly, we then test both the developed algorithm and the lightweight IED controller via various simulation scenarios. We perform testing scenarios of a developed MGS in a microgrid cyber-physical simulation subject to cyber-attacks in our lab. These testing are designed through performing two MGC testing scenarios. First, a delay attack is implemented, when the microgrid is islanded–the MGC monitors whole MG circuit breakers (CBs) specifically in this scenario—and the PCC CB should disconnect Load 4. Secondly, we test a packet manipulation on a measured data attack. External MGC HIL monitors the power generation as well as load consumption, in case (no balance) a trip command is issued to disconnect Load 3 via GOOSE. We then provide this development procedure for HIL MGC, which can communicate with the real-time simulator’s HYPERSIM simulation model over IEC 61850 GOOSE, as well as run the designed intelligent controlling algorithm and send the dispatching signal back to the real-time simulator model.
Georg Lauss
Biography
Georg Lauss received the Dipl.-Ing. degree from the Johannes Kepler University JKU Linz, Austria, in 2006 and jointly from the Eidgenössischen Technischen Hochschule ETHZ, Zürich, Switzerland, and the Université Pierre-et-Marie-Curie, Paris, France. He is a researcher with the AIT Austrian Institute of Technology, Vienna, Austria. His main interests include electromagnetic systems, power electronics, system and control theory, mathematical methods for optimized control systems, hardware-in-the-loop simulation systems, and real-time simulation for electromagnetic power systems.
Georg Lauss is the Chairman of the IEEE WG P2004 Recommended Practice for Hardware-in-the-Loop (HIL) Simulation Based Testing of Electric Power Apparatus and Controls and the IEEE PES Task Force on Real-Time Simulation of Power and Energy Systems.
Dr. Charalambos Konstantinou
Biography
Charalambos Konstantinou is an Assistant Professor of Computer Science (CS) and Affiliate Professor of Electrical and Computer Engineering (ECE) at the Computer, Electrical and Mathematical Sciences and Engineering Division (CEMSE) of King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. He is the Principal Investigator of the Secure Next Generation Resilient Systems Lab (SENTRY) and a member of the Resilient Computing and Cybersecurity Center (RC3) at KAUST. His research interests are in secure, trustworthy, and resilient cyber-physical and embedded IoT systems. He is also interested in critical infrastructures security and resilience with a special focus on smart grid technologies, renewable energy integration, and real-time simulation.
He received a Ph.D. in Electrical Engineering from New York University (NYU), NY, in 2018, and a Dipl.-Ing.-M.Eng. Degree in Electrical and Computer Engineering from National Technical University of Athens (NTUA), Greece, in 2012. Before joining KAUST, he was an Assistant Professor with the Center for Advanced Power Systems (CAPS) at Florida State University (FSU). He is a Senior Member of IEEE, a member of ACM, and an ACM Distinguished Speaker (2021-2024).
Christine Van Slyke
Biography
Christine Van Slyke is Vice President of Global Sales and Marketing at SCALABLE Network Technologies. She has been with SCALABLE for over seven years and has a Masters in Business Administration. She has more than 20 years of experience in business, technology, and strategy development. Prior to SCALABLE, she spent more than a decade helping TELUS—one of Canada’s leading telecommunications and managed solutions providers expand its offerings across the Province of Ontario.
Deepak Fulwani
Abstract
This talk will discuss methods to implement different topologies of DC Microgrids.
Aitor Ollacarizqueta
Abstract
CENER has developed an EMS to manage either microgrids or renewable generation plants hybridized with energy storage systems. Its first prototype has been validated at its facilities in the ATENEA microgrid, which have been previously simulated through RT-LAB using a OP4510 target.
The EMS consists of a SCADA where the user can configure almost any plant based on renewable generation systems, loads, electric vehicle, connection to utility grid, gen-set and different types of energy storage systems. Also, the EMS lets the user select between several strategies and plant control depending on the configuration chosen before and their interests.
Since the study focuses on the ATENEA microgrid, which is composed of lithium, flow and lead-acid energy storage systems, a gen-set, programmable loads, one electric car, solar generation and grid connection, this system has been modelled and then simulated in an OPAL-RT target.
Through a previous process of validation of every model as well as the communication system with the EMS, the built system allows to design, adjust, and validate the strategies and control systems before testing them in ATENEA.
José Eduardo Alves Junior
Abstract
Synchrophasor measurement technology is based on calculation of phasors obtained from Phasor Measurement Units. This technology is used in several countries to get better observability of electric systems. CEPEL’s Synchronous Phase Measurement Laboratory (LabPMU), in Cidade Universitária, Rio de Janeiro, RJ, is a laboratory infrastructure conceived to provide performance tests of PMUs and research on applications based on this technology. One relevant project carried out at LabPMU is to use Fractional Cycle Digital Fourier Transform Algorithm for Phasor Measurement Units (FC-DFT). This project aims to achieve faster PMUs, regarding the increasing presence of power electronics interfaced resources in power system generation and transmission. The presentation will show power electronic electrical simulations using HYPERSIM, in order to show the benefits of the algorithm. Two different simulation circuits were used: an HVDC multi-infeed circuit, as that arrangement is extensively used in the world, especially in Brazil; and a simulation of a distribution circuit provided with a PV array connected to the distribution electrical system through a converter (switching function model). Some occurrences of the power electronics equipment are simulated, and the results are the input of the FC-PMU. The FC-DFT results are then analyzed, showing that the equipment may deliver beneficial information for the control system operator and for early forensic analysis.
Shahab Karrari
Abstract
Low-inertia power systems can experience high rates of change of frequency and large frequency deviations during power imbalances. Inertia emulation using high power density storage systems such as a Flywheel Energy Storage System (FESS), can help limit the rate of change of frequency following sudden changes in generation or demand. In this presentation, a new adaptive inertia emulation controller for a high-speed FESS is proposed. To validate the behavior of the FESS with the proposed control design, the controller is implemented on a real 60 kW high-speed FESS, using the concept of rapid control prototyping. The performance of the FESS, equipped with the adaptive inertia emulation controller, is evaluated by means of Power Hardware-in-the-Loop (PHIL) simulations using the real-time simulation model of a low voltage microgrid. To reduce the overall loop delay, the established PHIL setup uses fiber optic connections to the power amplifier and several I/O expansion units. The State-space Nodal (SSN) solver is also applied to reduce the simulation time step of the microgrid model. The results of PHIL simulation show that the FESS with the newly-proposed adaptive inertia emulation controller outperforms the previously-suggested adaptive control designs, in terms of reducing the maximum rate of change of frequency and limiting the maximum frequency deviation, while not demanding significantly more energy from the FESS.
Matias Diaz
Abstract
Modular Multilevel Cascaded Converters (MMCC) have attracted considerable attention from the power electronic and drive research community since their introduction at the beginning of 2000. Originally, MMCCs were proposed for High-Voltage Direct Current (HVDC) transmission systems. Still, recently, they have been introduced into other fields, e.g., static compensators, wind energy conversion systems, and motor drives.
Among MMCCs, the Modular Multilevel Converter (M2C) is a well-established topology used extensively for HVDC transmission. However, the M2C has some difficulties in achieving good performance in applications where the electrical machine operates at a very low speed.
Therefore, other MMCC topologies, such as the Hexverter, the Modular Multilevel Matrix Converter, the Series-Shunt MMCC have been studied in the last few years. However, novel converters require complex implementations and control strategies that have hindered the number of works where experimental results of these topologies are reported.
In this context, this presentation introduces a joint project lead by the University of Santiago of Chile, in collaboration with OPAL-RT and Conecta Engineering, where a reconfigurable MMCC composed of 120 power modules is implemented using OPAL-RT MMCC modules. Thus, the testbed can perform rapid control prototyping testing and Power Hardware in The Loop analyses of novel topologies such as M3C, Hexverter and other novel topologies.
Catalin Gavriluta
Abstract
Smart grid applications, especially those focusing on the coordination of distributed flexibilities, include many devices governed by increasingly complex software architectures, all linked together by communication technology. In theory, some of these applications would have the potential to revolutionize the way the grid is being operated. However, in practice they are met with skepticism due to the uncertainties and vulnerabilities that these systems might introduce. Therefore, exhaustive testing and validation steps need to be undertaken before deployment to guarantee reliability. Approaching this task manually is extremely time-consuming and error prone. In this presentation we show an approach to automatically generate cyber-physical test beds which allow the evaluation of such applications. The proposed method uses PSAL (Power System Automation Language) to describe the cyber-physical system under test, i.e., the electrical network, the sensors, the actuators, as well as the various controllers/software components and their interconnections. Several model generators parse the PSAL code, and they automatically build a real-time simulation of the physical system; they establish various interfaces for the controllers to interact with the sensors and actuators; they package the controllers and deploy them to their designated locations; and they configure the data collection framework to enable the recording and analysis of experiment data.
Mukesh Singh
Abstract
The success of EVs depends on the charging infrastructure. Due to different charging standards, it is difficult for EV manufacturers to rely on any one standard. Therefore, there is a need to design a charging system which can fit in many charging protocols. This presentation will give an insight into the different charging standards and their probable solutions.
Balaji Mendi
Abstract
This paper presents the design and development of a wind turbine emulator (WTE), based on a separately excited DC motor, using an OPAL-RT digital simulator. The power-motor speed characteristics for different armature voltages in the motor are like the power-turbine speed characteristics for varying wind speeds in the turbine. WTE is a power electronic step-down chopper that is interfaced with a mathematical model of wind turbine present in the RT simulator. The wind turbine model generates a reference armature current that is compared with the actual armature current of the motor. The PI controller is used here to minimize the current error and provides a desired switching pulse to the MOSFET. The laboratory setup consists of a WTE that is coupled to a three-phase permanent magnet synchronous generator (PMSG) as a standalone system. The turbine model and PMSG model are presented in this paper. The effectiveness of this RT-LAB-based WTE is verified by simulation and experimental results under various wind speed and load change conditions.
Preeti Gupta
Abstract
Precision is the most important aspect for designing, controlling, or validating any power system—and due to this, real-time simulation is growing. Especially in design, it allows accurate modeling of a system, which is the baseline of design. Therefore, in this work, a switching function-based model of a three-phase voltage source inverter is transformed into a real-time model using OPAL-RT’s real time simulator (OP4510) with hardware-in-the-loop technology for its implementation in an actual power system. For the validation of its behavior in real time, it has been compared to the detailed inverter model having the same input variables and control dynamics. The results reveal that the proposed inverter model keeps the total harmonic distortion within limits as per the latest grid code and, at the same time, it maintains the required accuracy for the system. Further, this work shows the importance of real-time simulation by comparing its mode of simulation with other offline modes of simulations such as normal, accelerator and rapid accelerator.
Renzo Espinoza
Abstract
This work proposes an interfacing technique that uses the built-in three-phase transmission line models available in simulation platforms to perform Root Mean Square (RMS)-Electromagnetic Transient (EMT) real-time, multi-domain and multi-rate co-simulation. The main objective of this paper is to show the application of this kind of simulation in hardware-in-the-loop (HIL) testing of protective relays. Two well-known platforms are considered in this work: OPAL-RT with its ePHASORSIM tool is used for RMS simulation, and RTDS is used for EMT simulation. However, the proposed technique is sufficiently general to be applied to other real-time simulation platforms that have similar built-in transmission line models. To convert waveforms to phasors, a non-buffered rapid curve fitting method was implemented to attend to real-time constraints. During the testing phase of this research, tests for the HIL were completed using an actual transmission line protection relay. The presented results of tests highlight the benefits of the proposed interfacing technique.
Louis Filliot
Abstract
With the increasing level of penetration of renewable production and the need for long-distance energy transport, Multi-Terminal DC grids (MTDC) have become a crucial field of research for the future development of wide-scale DC grids.
These MTDC grids pose several technical challenges: protecting the DC grid against electrical faults; transforming DC voltage; and controlling the flow of energy in a meshed system. The possible technical solutions and new technologies addressing these issues need to be assessed through real-time and HIL simulations to demonstrate the system’s performance.
With that perspective, an MTDC HIL test bench is being developed at the Supergrid Institute to test and validate any proposed control and protection solution.
On this HIL setup, several Raspberry PIs are used to simulate in real time the different IEDs of the system: protection relays, station supervisors, DC Grid Control. These IEDs communicate with each other and with the electrical model using the IEC61850 communication protocol.
The electrical benchmark is a 4 Terminal DC Grid, modelled with HYPERSIM and running in real time with an OP5700 simulator.
The HYPERSIM model uses a Graphical User Interface (GUI), coded in Python and using the Python API provided by HYPERSIM. This interface allows a user to interact with the electrical system: launch a start-up sequence to connect the DC Grid, simulate a fault to test the implemented protection strategy.
Georg Lauss
Abstract
Part 1: The global power system’s transition to nearly 100% renewable-based generation presents new challenges not only in terms of control strategies but also in terms of tools required to perform HIL simulations. In this context, conventional generators such as synchronous machines may be gradually replaced by power electronic converters or similar generation units. HIL simulation setups of large grid models with multiple switching inverters are a challenge due to the high-level of accuracy required. The coupling of the power electronic domain with the network-level domain is currently the major issue to overcome. Two approaches are followed: the first one involves the coupling of the FPGA and the CPU model, while the second one uses the ARTEMiS library.
Part 2: Non-real-time or offline simulation methodologies using numerical solving techniques for network or component models have their limitations with respect to the necessity of high complexity. Therefore, they may prove insufficient with respect to resulting simulation accuracy or computation time. Real-time simulation based HIL simulation testing can overcome these issues, because physical hardware equipment, including the entire control system, is interlinked with the simulated network model via HIL interfaces. This enables natural coupling which guarantees the conservation of instantaneous power via the conservation of the through and across quantities at interfaces as exists in the real-world system.
Biography
Georg Lauss received the Dipl.-Ing. degree from the Johannes Kepler University JKU Linz, Austria, in 2006 and jointly from the Eidgenössischen Technischen Hochschule ETHZ, Zürich, Switzerland, and the Université Pierre-et-Marie-Curie, Paris, France. He is a researcher with the AIT Austrian Institute of Technology, Vienna, Austria. His main interests include electromagnetic systems, power electronics, system and control theory, mathematical methods for optimized control systems, hardware-in-the-loop simulation systems, and real-time simulation for electromagnetic power systems. Georg Lauss is the Chairman of the IEEE WG P2004 Recommended Practice for Hardware-inthe-Loop (HIL) Simulation Based Testing of Electric Power Apparatus and Controls and the IEEE PES Task Force on Real-Time Simulation of Power and Energy Systems.
Sanjeev Pannala
Abstract
The distribution system has undergone tremendous upgrades that have leaned toward a more carbon-free, reliable, and resilient infrastructure. This has been made possible by incorporating more sophisticated controllers in conventional generation, smart inverters based distributed generation, automatic load regulators, seamless interfacing of mini, micro and nano grids etc. To the contrary, the system is exposed to different events resulting from intermittent generation, as well as the unpredictable and uncertain behavior of loads in distribution networks. Real-time digital simulators from OPAL-RT let the power professionals study these events through digital twin models and by tweaking system parameters to create diverse and disruptive steady, dynamic, and transient event signatures–and also provides real datasets through the direct interface of sensors, PMUs, remote terminal units, smart measurement/meters, for testing and validating the AI-centric data analytics. Online testing of data analytical tools is made easy through real-time simulators by OPAL-RT as it has dedicated input and output digital/analog channels for export/import signals from/to power system models and supports standard communication protocols such as DNP3, C31.118-2011, etc. This presentation revolves around the wide usage of OPAL-RT’s real-time digital simulations in prospective testing environments of data analytics through real and simulated distribution phasor measurement units. Actual case studies are emphasized in the presentation.
Raju Chintakindi
Abstract
Wide Area Monitoring and Smart Automation (WAMSA) is today’s innovative research area under smart grid execution to overcome real-time protection difficulties. Modern communications and information processing technologies offer outstanding real-time benefits. The development of big data applications and satellite uplinks are rapidly changing. Several new measurement devices are being incorporated into an advanced smart grid metering infrastructure. In this process, PMUs can sense, converting signals from voltage and current into digital form under real-time wide-area monitoring systems. In modern power systems’ real-time applications point of view, big data analytics are playing a vital role with increasingly popular technological concept that contains smart electricity facilities, for instance, smart power control, energy utilization, and management. Initially, it emphasized smart grids, modern data analytics, massive-scale information control, and reliable monitoring methods with the extreme size of data required. This paper summarizes the PMU setup and installation overview in the Unified Real-time Dynamic State Measurement project (URTDSM) with the synchrophasor based wide-area monitoring system in India. The novelty of this presentation is to focus on big data potential functions and practices like fault detection, transient stability, load forecasting, and power quality monitoring into real-time wide-area monitoring.
Bolívar Escobar
Abstract
The advancement of technology has allowed the exponential development of electric engineering applications, and several of these fields are: digital simulation in real-time in conjunction with synchro-phasor measurements in electrical power systems; the generation of data applying the Monte Carlo method; and the analysis of data by application of data mining techniques. Research on load-shedding schemes, together with the application of the above-mentioned fields, allows the prediction of certain events that have caused the disconnections of large amounts of load, and even the operating output (blackout) of large power systems, around the world.
The present project proposes a methodology for the implementation of a load shedding scheme as a function of voltage and frequency that allows, through an indicator, and by means of an indicator calculated in real time through a previously-trained regressor, to determine the amount of load to be disconnected after the occurrence of a contingency for loss of generation.
To do this, a comprehensive real-time digital simulation platform is implemented, which uses OPAL-RT’s ePHASORsim, together with the functionalities of CENACE’s WAMS system, WAProtector, to execute a Software in the loop (SIL) to perform adaptive load shedding in real time, triggered when the indicator condition calculated by the regressor previously-trained with simulation results obtained from PowerFactory is met.
Ricky Zhang
Abstract
Our UPS HIL Testbench presentation will focus on how we used OPAL-RT’s solution in the UPS HIL system design to speed up the product launch, as well as key parameters Gs Understanding and TSB bridge usage in the UPS HIL system.
Isao Iyoda
Abstract
Japan intends on attaining carbon neutrality before 2050, and offshore wind farms are one of the primary energy sources that will help to realize this ambition. Since the sea depth around Japan is more that 50m, facilities of transmission systems for offshore wind farms must be installed on floating platforms. Middle frequency (500Hz) convertors are a promising equipment that reduce the weight and volume of transformers used for substations on the floating platform. MMC is a solution that can operate at 500Hz with less switching loss. It however requires much system analysis to develop and tune the control system. Real-time simulators are a useful tool for small academic laboratories to study on MMC. It saves risks of hardware trouble caused by mis-operation of the control system. An example of studies–such as the fundamental operations of scaled models (200V, 1A) of MMC convertors, real time simulation for tuning of control systems, as well as harmonics studies in our laboratory–will be introduced in the presentation
Ibrahim Elsabrouty
Abstract
Sharing the user story / experience from Maschinenfabrik Reinhausen (MR) with OPAL-RT products in a Modular Multilevel Converter development project, problems, challenges and benefits.
Emilio Piesciorovsky
Abstract
This study presents an interface method (IM) to interconnect real-time simulators (RTSs) without amplifiers for different intelligent electronic devices (IEDs), such as protective relays, smart meters, and other devices. It is a significant topic for the power systems protection community because there are many protection devices with different requirements. These protection devices have pinouts that measure bus voltages/currents and breaker pole states and generate trip/close pulse signals. Most of the emulation test beds with RTSs and HIL need amplifiers to connect IEDs from different product manufacturers because the low-voltage interface levels are not available in some instruction manuals. Additionally, commercial amplifiers have cutoff frequency limitations and have an excessive cost when several IEDs are wired onto test beds. Then, the validation of protection and control systems with RTSs and IEDs in the loop from different vendors without amplifiers results in an unfeasible alternative. In this paper, the IM was based on using an interface box, power source, and RTS to identify IED inputs/outputs. The sequence to recognize IED pinouts and calculate the current/voltage scaling factors is described. The IM was validated satisfactorily with RTS and a protection device (with unknown pinouts) in the loop.
Biography
Emilio C. Piesciorovsky graduated with a BS in electrical engineering from the National Technological University, Argentina (1995). He received his MS in marketing international from La Plata National University, Argentina (2001). He worked as an engineer for Pirelli Power Cables and Systems, SDMO Industries, ABB, and Casco Systems.
He completed his MS (2009) and PhD (2015) in electrical engineering from Kansas State University. Then, he worked as a postdoc at Tennessee Technological University and Oak Ridge National Laboratory.
Currently, he is a professional technical staff member and lab space manager in the power system protection area at Oak Ridge National Laboratory. He is the author/coauthor of more than 20 publications, and is an IEEE senior member; piesciorovec@ornl.gov.
Genesis Alvarez
Abstract
As the complexity of today’s power system increases, it is crucial to have a system protection training program that can incorporate evolving changes and mimics a realistic environment. Dominion Energy is developing real-time models to conduct closed-loop tests. The Substation Automated Training Simulator (SATS) infrastructure is composed of a OP5700 simulator, four OP5600 expansion boxes, and 24 Omicron Power Amplifiers, all mounted on five equipment panels. This system is hardwired to protective relay equipment panels and to primary equipment. There are a variety of use cases that can introduce various abnormal scenarios that may be encountered in a real power system. This closed-loop system enables a simulation to seamlessly replicate the power system response while switching primary substation equipment. Beyond that, it also provides a method of validating entire protection schemes including equipment wiring, individual protective relay settings, and overall device coordination.
Dr. Flavia Khatounian
Abstract
Flavia Khatounian received her diploma in Electrical and Mechanical Engineering from Saint Joseph University of Beirut (USJ-ESIB), Lebanon, in 2002, and the Ph.D. degree in Electrical Engineering from the Ecole Normale Supérieure (ENS) de Cachan, France, in 2007. She joined the Saint Joseph University of Beirut in 2008 where she is nowadays a full-time associate professor at the Faculty of Engineering and Head of the Electrical and Mechanical Engineering Department.
Her research interests include power electronics and electrical machines identification and control. She serves as a reviewer for high impact factor journals and international conferences and is a member of the IEEE, IEEE Industrial Electronics Society (IES) and IEEE Robotics and Automation Society (RAS) where she volunteers currently as a vice chair of the Lebanon Joint Chapter, RA24/IM09/CS23 (CH08807). She is the author or coauthor of 2 book chapters and more than 40 scientific papers.
Wagner Seizo Hokama
Abstract
We are currently undergoing a major digital transformation in almost all processes of an electricity distribution company. CPFL (www.cpfl.com.br), one of the largest companies in the sector of energy in Brazil, seeks digitalization in all its operational processes, aiming at gains such as cost reduction and increase in the quality and productivity of services. In line with this corporate strategy, the CPFL group’s Smart Grids engineering management seeks digital technological solutions with the same purpose in its projects. We understand that the complete digitalization of a substation involves the application of the Process Bus (IEC 61850-9-2) for the Substation Protection and Control System (SPCS). The implementation of the Process Bus goes far beyond the economics of removing copper cables from substation ducts. It enables a new horizon of opportunities that a digitalization of signals can offer, such as the implementation of the automation of SPCS operational tests. Substations fully digital could require weeks to test all of its functions, i.e, relay testing is expensive and intelligent choices regarding what we test and how the test must be made. The purpose of this paper is to propose the use of real Real-Time Digital Simulators (RTS), capable of publishing and subscribing GOOSE and Sample Values messages on the Process Bus, to perform operational tests in SPCS. In other words, the idea is present all the benefits achieved when RTS is applied for relay testing in field and not in laboratory environment only.
Historic: Currently, factory acceptance tests (FAT) are carried out using analog signal injection equipment (secondary current and voltage), one bay at time. It is a very slow and laborious process as they involve the connection and disconnection of several copper cables in the panels, still in the factory. It is also worth noting that because bay-by-bay tests are performed, it is often not possible to evaluate the dynamic behavior of the other bays in the event of a real disturbance due to the lack of modeling of their components and interconnections.
Requirements: To carry out these tests through the Process Bus, it will be necessary a RTS portable and robust, in order to facilitate its transport for carrying out tests in the factories, where the SPCS panels are assembled, and in the substations, where commissioning, maintenance and troubleshooting are performed. The simulator must also be able to be synchronized by a GPS via PTP (Precision Time Protocol) or similar protocol, publish and subscribe GOOSE and SV messages. The substation modeling capacity will facilitate the execution of operational tests, as well as the SCD file import, as defined by the IEC 61850 standard, arising from the SPCS configuration.
Expected results: The implementation of the Process Bus in the SPCS will allow the use of digital tools for the injection of current, voltage and binary signals from all the bays of the substation, available on the same bus, without the need to connect any copper cables and power amplifiers. This facility will enable the automatic generation of sequential and standardized operational tests, aiming at increasing their quality (precision and repeatability) and faster performance, compared to the technique currently used with analog equipment. In addition, it will be possible to carry out unprecedented tests such as the verification of the dynamic behavior (permanent and transient phenomena) for the entire substation with voltage, frequency and current values, due to the application of the modeling of all electrical equivalents that make up the substation and the power system.
Adekunle Oyenusi
Abstract
Oftentimes, technology is viewed mainly from the perspective of changes that it brings in the lives of people and especially in the ease that is occasioned in its application. Whilst not deviating from this traditional perspective, this Paper goes further to examine the role of real-time simulation in the development of Power Sector of developing economies, especially in Nigeria and the West African Region. The Paper attempts the contribution of Real-time solutions to the development of human capital development whilst at the same time taking a stock of the economic opportunity provided for manufacturers in their incursion into the African markets. It concludes by showing a possible win-win solution for all stakeholders in which the Power Sector records improvement through these technologies while manufacturers build on this business to increase turnover and undertakes researches into new areas.
Raphael Mencher
Abstract
The use of DC technology in various applications is increasingly coming to the fore with a view to efficient and sustainable energy supply with the integration of renewable energies and energy storage systems. Besides advantages in improved controllability, system efficiency, and economic feasibility, protection strategies of dc grids are more challenging compared to ac grids due to the missing natural zero crossing of the current. Therefore, specially designed dc circuit breakers or the conception of breaker-less dc grids, using current limiting modulation schemes need to be developed.
As part of the Flexible Electrical Networks (FEN) Medium Voltage Direct Current (MVDC) research grid, a 7 MVA three-phase Dual-Active Bridge (DAB) is built with a nominal voltage of 5 kV. The switching frequency of this converter is 1 kHz, and three single-phase high-frequency transformers provide galvanic isolation and the necessary series inductance. For high power converters in breaker-less dc grids, a fault current limiting control is developed, taking several aspects into account. The most critical factor, thereby, is the small leakage inductance of the converter transformers, resulting in high power dynamics during normal operation and excessive fault currents when the DC link voltage collapses. Another issue is the large minimum turn-on time of the used IGCT semiconductors, which permit the use of conventional modulation schemes.
This presentation shows a control-hardware-in-the-loop simulation to test the actual converter control platform in case of a grid fault. Therefore, the control platform is connected via adapter boards to an Opal-RT OP4510 real-time simulator. One adapter board convert fiber optical signals into electrical while the other one is feeding back measurement signals for the closed loop control. The converter waveforms of the real-time simulation are compared to offline simulation and hardware measurements at 2 KV. Moreover, the fault current limiting modulation in case of pole-to-pole and pole-to-ground fault is implemented on the control platform and tested using the real-time simulation. The results are compared to offline simulation.
Binyu Xiong
Abstract
With the rapid growth of renewable and distributed energy resources (DER), their impact on the legacy AC grid is becoming an important topic. Among integration strategies, the dc microgrid is attractive because of the high efficiency and simple dc interface for various DERs and energy storage devices. When connected to the ac grid, it utilizes a dc-ac converter as the interface. However, there are still many major challenges to integrate dc microgrids in the legacy power system.
Dc-ac converters using traditional power electronics control strategy have fast dynamics. However, the key equipment in power system: the synchronous machine (SM), has slow dynamics with large inertia.
The power generated by DERs is intermittent and will be instantly presented to the grid through fast respondingdc-ac converters. These interactions will lead to frequency, angle, and voltage instability.
Today, the dc-ac converters lack rotational inertia and do not interact with the grid like the SMs.To solve these problems, dc-ac converters mimicking synchronous machinesare proposed. These virtual synchronous machines (VSM) offer several benefits.
A much larger inertia than traditional dc-ac converters is introduced.
Their models are simple hence promising for studying scalability and stability of paralleled VSMs.
The use of phase lock loop (PLL) is eliminated during normal operation, since the VSMs can synchronize with the grid based on the power balance.
Seamless transition from grid-connecting mode to islanding mode and resynchronization back with the grid as a voltage source.
This project proposes a microgrid integration concept to address above mentioned issues. It controls the distributed dc-ac converter as a VSM-based interface (VSM), and includes the following:
A frequency regulation improved but enables the ac frequency and dc voltage being regulated within desired ranges.
An improved dual droop control separately for the VSM and the dc side energy storages to support the VSM functionsand achieve the power management.
An additional power system stabilizer (PSS) to enhance the system stability and energy storages in the dc microgrid into a VSM from the grid point of view.
The digital simulation platforms that use mathematical models of the target systems may not be reliable because some components are usually inaccurate or unavailable. The hardware or field tests eliminate the problems of digital simulation platforms. However, it requires a long setup time, high cost, and application-specific design. These challenges obstruct the extensive utilization of the hardware or field test platforms. These platforms are costly to maintain and difficult to reconfigure. They limit the possibility of conducting the study of the different microgrid scenarios.
To solve these issues, aCHIL platform has been developed based on the OPAL-RT real-time simulators (OP5600/OP5607) and dSPACE MicroLabBox controller (ML1202). The CHIL platform combines the advantages of digital simulation and an external controller. The OP5600 real-time digital simulator at Clean Energy Research Lab in Nanyang Technological University is installed with 12 Intel Xeon E5 processors with a frequency of 3.2 GHz.
Raju Chintakindi
Abstract
With rising global energy demand, transmission lines are operated at their limits, causing electrical gridsto operate under extreme voltage instability conditions. To meet the increased load-demand and the forced tendency across the globe of tilting towards even more renewable generation, solar and windfarms are integrated with increased size and capacity. These uncontrolled natural power injection againmay affect the system’s voltage stability. To avoid blackouts and to achieve the maximum voltagestability of power systems, operators need to do effective real-time grid monitoring and control at loadterminals. Load models are important in the analysis of voltage stability, and accurate load models areuseful in analysing the voltage stability conditions. Phasor-measurement-unit (PMU) based wide-areamonitoring and smart-automation is an innovative technology for measuring load voltage magnitude,phase angle, and frequency variations in a DFIG integrated large wind power system. This researchpaper focuses on estimating the real-time voltage stability through the use of linear, nonlinear, anddynamic load models in presence of a DFIG based wind-farm in WSCC three-machine nine-bus powernetwork using PMU data. This study is carried out using MATLAB-Simulink software.
OP101: RT-LAB - Real-Time Simulation Systems Fundamentals
OP101: RT-LAB – Real-Time Simulation Systems Fundamentals
This course introduces OPAL-RT systems and applications using RT-LAB. This course is a prerequisite for eMEGASIM, eFPGASIM, and ePHASORSIM. RT-LAB is used in a variety of domains, including power systems, power electronics, automotive applications, aerospace, mechatronics and more. Prerequisites: • Basic knowledge of Matlab®/Simulink®
Goals: • Learn the fundamentals of real-time simulation • Get started with RT-LAB Software • Understand when and how to use distributed and parallel real-time simulation • Connect models with I/Os
SECTION 2 – USING THE SIMULATOR • Video 5 – Running a Simulation in RT-LAB • Video 6 – Execution Performance • Video 7 – Probe Control • Video 8 – Parameters, Variables & Signals • Video 9 – Data Logging • Video 10 – Inputs & Outputs
This work develops Hardware-in-the-loop (HIL) simulation against cyber attacks. The test setup in Opal-EXata cyber attack example ( paper), is based on the software-in-the-loop (CSIL) MGC, however, the hardware-in-the-loop HIL testing is left for the developer. Thus, we design a light-weight intelligent electronic device (IED) that performs MGC, interfaces are developed based on IEC 61850 GOOSE protocol from/to the real-time simulation and the MGC. They are executed on two equipment stages, FPGA and BeagleBoneBlack. The concept behind using these boards is based on their low cost, flexibility, support for various interfaces/protocols, I/O pins, and ease of configuration. CSIL versus CHIL tests are used to evaluate the MG behavior against different cyber attacks. We also evaluate the MGC designed control function in accordance with IEC 61850 GOOSE protocol. Two scenarios was carried out, In the first scenario, the MG will be islanded in second 1, in this case the MGC will check the power balance and implement the power balance operation emergency condition (the difference not exceeds 3MW). If the check emergency condition becomes true, the MGC attempts to immediately disconnect the sheddable Load 4 to maintain the MG stability. Be that as a delay attack is introduced to the GOOSE trip command packets sent from the MGC to Load 4, the load shedding function may fail to operate in the required timeframe. In this case this will cause severe unbalance between generation/load relationship and oscillations on MG nominal operation parameters such as e.g., frequency, voltages etc. Through the C code available delay function within the MGC initial code, a one-second delay attack is applied to the MGC GOOSE message command. MGC based on its normal operation will receive measurements that is sent from each MG assists via GOOSE. Be that as a Man-in-the-middle attack is introduced to the load measurements data. Before the load measurements data being received by MGC. The data is manipulated in the middle of its way to the MGC. In this case, the MGC may take incorrect actions based on these received non-critical measurements. According to the test scenario 2, the active power measurement from Load 2 is duplicated by applying a packet manipulation attack to the GOOSE message. In this case, the MGC will take the incorrect action (false tripping) because it perceives the controlling operation emergency condition is true (total load will be more than 3MW greater than the total generation). As a result, a trip command is sent to disconnect Load 3. . It also causes oscillations on MG nominal operation parameters such as e.g., frequency, voltages etc. Comparison between both achieving testing results, SIL and HIL will be made within the rest of this work. The results are The development and performance of an MGC against cyber attack control schemes have been implemented in this paper. These are done by design and deployed on a light-weighted intelligent IED. The MGC control solution and its relevant communication system have been designed in compliance with the IEC 61850 and executed on two equipment stages, FPGA and BeagleBoneBlack. CSIL versus CHIL tests are used to evaluate/assess the MG behavior against different cyber attack scenarios. Moreover, we also evaluated IEC 61850 GOOSE protocol implementation, processing and finally control action performance. The obtained results demonstrate that the light-weight MGC approach and data modeling of various IEC 61850 predefined data object LNs are correct for the design of the power balance control/protection function against cyber attack. In addition, they demonstrate the successful implementations of the designed control/protection function and the modeled MGC LNs in various cyber-attack case studies on reliable detection of the emergency condition. Further work on the analysis of the data received by MGC, implementation of different cyber attacks and power balance detection algorithms is needed.
Dashboard Building
When HYPERSIM’s in-schematic signal monitoring is not enough, when networks are very large, or when more types of widgets are required, or even for training purposes, it may be practical to build distinct dashboards with a more concise organization of the information. Several tools can be used to achieve this, such as NI LabVIEW. Information is sent in real time from HYPERSIM using compatible communication protocols such as TCP/UDP or OPC UA and displays are refreshed every few milliseconds.
Jean Patric da Costa was born in Santa Maria, Brazil, in 1979. He received a B.S. degree in electrical engineering and a master’s and Ph.D. degrees from the Federal University of Santa Maria, Santa Maria, Brazil, in 2004, 2006, and 2011. He is currently a Professor with the Department of Electrical Engineering, Universidade Tecnológica Federal do Paraná (UTFPR), Curitiba, Brazil. His research interests include control of static converters, smart grids, ancillary services, and distributed generators.
Dr. Philippe Viarouge
Biography
Philippe Viarouge was born in Périgueux France in 1954. He received the engineering and Doctor of engineering degrees, the french accreditation to supervise research (HDR) from the “Institut National Polytechnique de Toulouse”, France, in 1976, 1979 and 1992.
Since 1979, he has been a professor with the Department of Electrical & Computer Engineering at Laval University, Quebec, Canada. He is working in the research laboratory LEEPCI. His research interests include the design & modeling of electrical machines and medium frequency magnetic components, AC drives and power electronics. He was Project Associate and consulting engineer at CERN, Geneva, Switzerland, in 2010 and 2018 respectively.
Controller Architecture
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Jared Foxworthy2025-05-13 11:05:472025-05-13 11:05:47What is Software-in-the-Loop (SIL)?
