Hardware-in-the-loop testing is a direct method for predicting how physical equipment interacts with control software in real time. Engineers integrate actual hardware components with virtual models to fine-tune complex systems before large-scale manufacturing. This approach helps uncover design flaws early and avoids expensive rework. Project teams appreciate the precision and immediate feedback, which ultimately shorten development cycles.
Many engineering teams often ask what is hardware-in-the -oop and how it aligns with best practices for real-time simulation. HIL offers an advanced way to see how mechanical systems behave under varied operating conditions without constructing full-scale prototypes. Testing procedures become more streamlined and repeatable, helping you reduce cost. Integrating real sensors and actuators into a simulated test framework also ensures data accuracy for thorough analysis.
What Is Hardware-in-the-Loop (HIL) Testing?
Hardware-in the-loop (HIL) testing often prompts a straightforward explanation: it links physical hardware components to a virtual model running in a real-time simulator. This setup evaluates genuine system performance under controlled conditions, which is essential when verifying safety, efficiency, or reliability metrics. Traditional bench testing might reveal certain issues, yet HIL offers deeper visibility because it replicates dynamic events in a repeatable way. Developers use this type of testing to confirm that control signals and power flows are properly managed before field deployment.
The approach typically involves connecting sensors, actuators, or even entire subassemblies to a digital domain designed to mirror operational scenarios. While software simulations alone can guide early development, the presence of tangible hardware adds a layer of authenticity that purely virtual methods cannot match. HIL helps you gather data on the physical responses to varying loads, temperatures, or voltage levels without building a costly test bench. Engineers across many industries, including power electronics and automotive, value HIL for accelerating validation schedules.
How HIL Testing Validates Control Systems
Control systems often exhibit complex interactions between multiple components, making them prone to hidden faults if tested only in simplified conditions. HIL provides a structured domain for testing every control loop with genuine hardware signals, thus capturing real performance data in real time. This reduces ambiguity and offers clarity on how sensors respond and how controllers adjust outputs based on the input conditions. Accurate insights gained from HIL allow engineering teams to refine algorithms and calibrate hardware interfaces more effectively.
For instance, a powertrain control system in an electric vehicle benefits from HIL testing by allowing the battery management unit, drivetrain components, and other modules to work together as they would in normal operation. This integrated approach leads to better alignment between hardware and software, minimizing unexpected failures after mass production begins. Large-scale projects see HIL as an integral strategy because it sets a high standard for performance evaluation at each phase. The result is a stable, well-coordinated system that meets or exceeds compliance requirements.
Main Types of HIL Configurations
Organizations employ various HIL setups to match the specific demands of their development projects. Some solutions focus on micro-level component validation, while others handle entire assemblies or system-level interactions. Different configurations are chosen based on budget, testing frequency, or hardware availability. A well-planned HIL layout significantly boosts reliability and return on investment by ensuring that every part is evaluated under the right conditions.
Processor-in-the-Loop (PIL): This setup verifies the functionality of embedded processors by interfacing real processing units with simulated inputs and outputs. Engineers often rely on PIL to highlight timing constraints and confirm if the target processor can handle computational demands. It shows exactly how the application code behaves under real processor conditions.
Power Hardware-in-the-Loop (PHIL): This configuration adds actual power components to the loop, such as converters or power amplifiers, allowing teams to assess behavior under load. System stability and safety become clearer because current and voltage waveforms are subjected to genuine electrical effects. PHIL is especially common in microgrid and renewable energy projects that need accurate power flow representation.
Electric Motor HIL: This option involves connecting the motor drive hardware to a digital representation of mechanical loads, letting you measure torque responses and other performance metrics. Development teams rely on motor HIL to confirm if speed control algorithms function correctly across a broad range of conditions. This approach identifies mechanical stress points early, which reduces maintenance costs later.
Automotive ECU HIL: Automotive engineers often use HIL benches to test electronic control units in real-time conditions without the full vehicle. Signals for sensors like temperature, pressure, or speed are emulated, and the ECU responds as if it were in a running system. This method helps confirm compliance with stringent industry regulations by isolating faults before the final assembly.
Mechanical Subassembly HIL: Some organizations test specific mechanical subassemblies, like hydraulic actuators or gearboxes, by coupling them with simulated conditions. The hardware experiences forces and motion that mirror real operation, enabling precise optimization. This configuration highlights how physical wear and tear might develop over time, prompting earlier design modifications.
Selecting the right configuration depends on the nature of your project and the extent of physical component integration required. Some teams combine multiple forms of HIL when working on large systems that span several domains, such as power distribution and vehicle control. Tailoring the approach ensures a balanced combination of scope and detail, yielding meaningful insights that drive better performance. Engineers who recognize these configurations can balance cost and testing depth, accelerating design cycles and production readiness.
Steps to Implement HIL
Effective HIL implementation hinges on a methodical process that aligns real hardware and software models in a stable test domain. Each step addresses potential sources of error and ensures that you gather accurate data for advanced system tuning. Teams reduce cost overruns by mapping out a clear plan before integrating all components. The following core stages help you achieve consistency and thorough validation:
Step 1: Define System Requirements
Clear objectives guide every successful HIL project. Engineers identify the control variables, performance constraints, and hardware specifications upfront. This approach helps you avoid confusion about the signals, data rates, and measurement ranges used during the tests. A structured list of requirements keeps the project focused and lowers the risk of scope creep.
Step 2: Develop Accurate Models
Functional models of the system or subsystem are created in real-time simulation tools, ensuring that the virtual elements mirror the physical domain. Engineers calibrate these models based on known performance benchmarks, verifying that each parameter, such as voltage level or fluid pressure, reflects real-life values. Detailed modeling reduces guesswork in subsequent steps. Verification at this stage lays the groundwork for integrating hardware seamlessly.
Step 3: Integrate Hardware Interfaces
Physical components such as sensors, actuators, or embedded controllers must connect smoothly to the simulator’s I/O channels. Proper cabling, signal conditioning, and data synchronization prevent faulty readings or missed events. This integration process often includes robust checklists to confirm accurate pin assignments and voltage references. Meticulous attention here guarantees that subsequent testing data remains trustworthy.
Step 4: Conduct Preliminary Validation
Initial trials confirm whether the combined hardware and simulation setup behaves as intended under controlled conditions. Engineers might run static load tests or simple operational scenarios to verify signal timing and data acquisition. These smaller evaluations help you fine-tune parameters before running high-fidelity scenarios. Addressing minor issues now can save significant effort once the system is fully operational.
Step 5: Iterate and Optimize
Ongoing refinement is essential after the first validation cycle. Teams examine logs and performance metrics to make incremental improvements, focusing on control algorithms or hardware response times. This iterative approach enhances system reliability by catching subtle design issues early. Each refinement cycle moves the project closer to a validated, production-ready solution.
Challenges in HIL
Implementing HIL may reveal complexities that require technical expertise, careful budgeting, or strong collaboration among multiple departments. These challenges can slow progress if not addressed systematically, yet foresight helps you reduce friction in the process. Some difficulties arise from hardware limitations, while others relate to organizational factors. Identifying these pitfalls early can substantially improve test outcomes.
Real-time synchronization difficulties: Maintaining precise timing between hardware signals and the simulator is vital, and any mismatch can compromise data integrity. Engineers often use dedicated hardware interfaces and high-speed protocols to handle this, but setup can be intricate.
Limited hardware availability: Some critical components might be scarce or costly, forcing test engineers to share resources with other teams. Efficient scheduling and resource management become necessary to keep the project on track.
Model fidelity concerns: High-fidelity simulations require detailed representations of mechanical, electrical, or thermal processes, which can be time-consuming to develop. Oversimplifying these models leads to inaccurate results.
Complexity in data interpretation: Large volumes of test data can overwhelm teams if they lack systematic tools for analysis. Well-chosen software solutions and robust data logging practices help you transform raw output into actionable insights.
Organizational communication gaps: Coordination between control engineers, hardware specialists, and project managers is crucial for timely decisions. Clear roles and responsibilities reduce misaligned efforts and missed milestones.
Addressing each challenge often involves a blend of technology upgrades, process improvements, and stakeholder alignment. Even advanced teams can encounter setbacks when new components or updated specifications emerge unexpectedly. Practical contingency plans and a willingness to refine initial assumptions keep the program on course. Ultimately, resilience in handling these hurdles benefits the entire development lifecycle.
Key Benefits of Hardware-in-the-Loop
Project leads appreciate the consistent outcomes and measurable gains that HIL testing offers. Speed to market is often boosted by early detection of issues, and budgets are better managed due to fewer last-minute surprises. The flexibility of adding or substituting hardware components enables real-time diagnostics and iterative improvements. A closer look at these benefits highlights why HIL stands out as a practical approach.
Enhanced safety testing: Putting actual hardware in controlled test loops avoids risky on-site evaluations. Major hazards or malfunctions are discovered in a safe setting.
Reduced development cycles: Iterative feedback from real hardware shortens each testing phase, shrinking the timeline to launch. This efficiency helps you respond more effectively to design changes.
Lower overall costs: Early identification of design flaws prevents late-stage rework, which can consume significant resources. Eliminating excessive physical prototypes also conserves budget.
Greater confidence in final products: HIL reveals detailed performance data, enabling robust validations of control algorithms and mechanical behaviors. Stakeholders trust outcomes supported by real hardware interactions.
Improved collaboration among teams: Engineers, operators, and even financial managers can align on test results, thanks to transparent insights delivered by HIL setups. This alignment drives more coordinated project outcomes.
Organizations that invest in HIL often view it as a strategic asset rather than an isolated testing tool. The capacity to link hardware and software under precise conditions fosters deeper learning about every subsystem. Collaboration around shared data speeds up decisions while ensuring compliance with industry standards. Over time, these benefits compound, resulting in more effective growth.
Trends in HIL for Emerging Technologies
New developments in autonomous systems and renewable energy have placed HIL at the center of advanced product development. Engineers are integrating machine learning algorithms into the simulation loop, allowing predictive insights based on real sensor feedback. This shift elevates test coverage and helps you detect anomalies before they escalate into major failures. The growing need for zero-emission transport solutions also aligns with HIL to refine battery, motor, and charging systems at scale.
Cloud-based platforms now offer remote collaboration features, where distributed teams run large sets of HIL simulations concurrently. This technology accommodates broader test scenarios and speeds up your time to market. Enhanced synergy between hardware and AI-driven analytics refines control system calibration for better efficiency. Many companies view these HIL advancements as opportunities to tap into new revenue streams while minimizing overall risk.
Hardware-in-the-loop fosters robust system development across multiple sectors that demand high reliability and peak performance. The process connects real and virtual elements in a test bed that quickly flags potential issues and paves the way for cost-effective fixes. Engineers and project stakeholders rely on its accurate results to guide essential decisions for product deployment. When executed with a clear plan and scalable approach, HIL stands out as a key driver for quality and efficiency.
Engineers and innovators across industries 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-based cloud simulation, our platforms allow you to design, test, and validate with confidence.
Common Questions About HIL Testing
What does HIL stand for?
HIL stands for Hardware-in-the-Loop. It is a technique that integrates physical hardware components into a simulated test framework to ensure accurate testing of complex systems.
Is hardware-in-the-loop testing different from software-in-the-loop?
Software-in-the-loop (SIL) testing focuses only on virtual models, while HIL adds actual hardware components for deeper insights. The presence of real hardware in HIL captures physical behavior and unique performance factors that SIL alone may overlook.
How does HIL help reduce project costs?
Budgets remain more stable because defects are discovered early, avoiding last-minute design revisions. Fewer prototypes and rework cycles also lead to substantial savings over the project’s timeline.
Can HIL testing scale for high-voltage or industrial applications?
Yes. Many platforms support higher power ratings, specialized I/O boards, and dedicated amplifiers to handle industrial demands while maintaining real-time performance.
Why do teams ask what is hardware-in-the-loop testing in automotive?
Engineers want a reliable way to verify electronic control units, powertrains, and safety functions before physical vehicle assembly. HIL exposes software and hardware to real sensor inputs, revealing potential issues under realistic conditions.
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)?
