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May 13, 2025
What is Software-in-the-Loop (SIL)?
Software-in-the-Loop (SIL) testing accelerates software validation, cuts costs, and boosts confidence in complex development cycles.
This process focuses on running actual production code inside a simulated setup, exposing potential flaws and optimizing performance long before physical hardware is introduced. Teams seeking a more efficient path to market often rely on SIL to speed up deliverables and reduce late-stage surprises. The goal is practical: avoid unnecessary risks and build quality into your code from the start.
A proactive approach to SIL encourages thorough, consistent checks that save money, minimize defects, and support scalable expansion. Code verification becomes an ongoing practice rather than a one-time event, improving reliability for mission-critical applications. This method is a core driver behind confident product launches and streamlined workflows in many industries. Achieving success with software in the loop testing opens doors to higher returns on investment and smoother hardware integration down the line.
“Teams often ask what is software-in-the-loop and how it differs from other methodologies; the key lies in verifying code correctness under controlled simulations to ensure stability for later hardware integration.”
What is Software-in-the-Loop (SIL) Testing?
Software-in-the-Loop (SIL) testing is a simulation technique used to validate control algorithms and embedded software in a virtual environment before deploying it to physical hardware. In this process, the control software runs on a development computer or virtual processor and interacts with simulated models of the system it is intended to control, such as an engine, inverter, or braking system. SIL testing helps engineers assess functionality, identify software issues, and optimize control strategies during early development stages.
This method is a key part of model-based design, offering a fast, cost-effective way to test without requiring physical prototypes. It allows for extensive testing across different operating conditions and failure scenarios, making it easier to catch and correct issues early. SIL testing improves software quality, shortens development cycles, and prepares the control logic for the next phase of validation, such as Hardware-in-the-Loop (HIL) testing.
Key Benefits of Implementing SIL Testing
Implementing a well-structured SIL framework brings significant advantages for teams focused on cost-effectiveness and faster development timelines. This approach accelerates identification of software bugs, supports efficient iteration, and strengthens overall project outcomes.
Accelerated Iterations: Quick feedback loops reduce delays and shorten the release cycle, maximizing return on investment.
Early Defect Detection: Coding errors surface while code is still easy to fix, resulting in fewer costly revisions later.
Improved Risk Management: Gaining insight into software behavior helps avoid unexpected issues during hardware deployment.
Enhanced Collaboration: Cross-functional teams interact more cohesively when initial testing does not rely on physical prototypes.
Lower Operational Costs: Software-based checks minimize spending on hardware resources and maintenance.
Seamless Growth Potential: Expanding coverage is straightforward when simulations run on flexible software platforms.
Greater Confidence in Final Product: Thorough validation in controlled simulations builds trust in the overall solution.
Each of these benefits supports a more predictable development pathway that ultimately helps stakeholders move quickly while containing costs. Teams looking to enhance quality often rely on SIL as a stepping stone for further validation methods, ensuring minimal surprises when hardware testing begins.
Challenges in SIL Testing
Adopting SIL testing can introduce certain difficulties, especially if teams are new to model-based methods or lack familiarity with simulation frameworks. Recognizing these hurdles ahead of time allows you to mitigate risks and keep progress on track.
Model Fidelity Issues: When virtual models do not accurately reflect real conditions, the accuracy of test results suffers. High-quality modeling is critical for trustworthy data.
Integration Conflicts: Merging disparate software modules can create mismatched interfaces. Careful version control and standardized protocols help avoid these setbacks.
Limited Resources: Smaller groups may struggle with the learning curve involved in advanced simulation tools. Adequate training and modular test setups often resolve this gap.
Inconsistent Test Configurations: Shifting from one testing framework to another creates potential for data misalignment. Unified guidelines and consistent settings keep results reliable.
Insufficient Automation: Manual processes slow down iteration and heighten the chance of error. Automated scripts and integrated toolchains reduce overhead and improve reliability.
Once these challenges are identified, strategic planning and robust tooling turn SIL testing into a powerful practice. Addressing each obstacle ensures that your organization stays on schedule, promotes collaboration, and secures a higher level of software readiness.
Software-in-the-Loop (SIL) vs. Hardware-in-the-Loop (HIL)
The main difference between SIL and HIL lies in the physical hardware presence. SIL runs fully in a virtual context, focusing on software correctness without actual electronic components in place. HIL, on the other hand, involves connecting real hardware to a simulation to validate how components respond under realistic input and output conditions. Both techniques aim to verify software integrity, but HIL adds a deeper level of fidelity that reflects real signal interactions.
Teams often select SIL during early phases to optimize code efficiency, confirm logic flow, and uncover integration errors. HIL typically appears once software proves stable enough to handle interactions with actual hardware setups. Organizations balancing speed to market with thorough verification frequently adopt both methods at different points in the project timeline. Combined, they create a flexible test strategy that addresses both software integrity and hardware behavior.
Aspect
SIL
HIL
Level of Testing
Software-focused, no physical hardware required
Involves real hardware components for high-fidelity testing
Cost Considerations
Generally lower investment, fewer devices to procure
Equipment costs can be substantial due to specialized hardware
Setup Complexity
Straightforward, reliant on software frameworks
More complex, requires integration of hardware and real signals
Testing Stage
Ideal for early-phase validation of code logic
Typically used later when software is mature enough for hardware interaction
Typical Use Cases
Rapid checks of algorithms, unit tests, embedded software validation
Full system integration tests, performance benchmarking, final hardware acceptance
Applications of SIL Testing in Various Industries
Many fields use SIL testing to streamline code validation and ensure consistent performance before major investments in physical prototypes. This approach is especially popular among sectors that prioritize safe operation, reliability, and scalable product deployment.
Energy Sector
Power generation and distribution solutions often require advanced control logic to regulate voltage, current, and switching functions. SIL testing checks these software routines in a simulated power grid scenario, allowing engineers to fine-tune algorithms for stability. Project managers appreciate the cost savings realized when large-scale prototypes are not required in early stages. This technique also accelerates time-to-market by confirming code reliability before hardware demonstrations.
Automotive
Manufacturers develop complex control software for engine management, electric drivetrains, braking, and infotainment features. SIL testing examines these modules through repeatable scenarios, making it simpler to detect and correct errors. Safety-critical aspects, such as advanced driver-assistance systems, benefit from robust software validation in a controlled software setup. Development teams harness the speed and cost savings to deliver vehicles with fewer defects and a shorter product launch cycle.
Aerospace
Flight control, avionics, and mission-critical applications demand precision at every step. SIL testing allows engineers to simulate flight paths, sensor inputs, and communication protocols while verifying that software logic behaves as expected. This method lowers project risks, especially when teams must meet stringent certification requirements. Projects are less likely to encounter last-minute changes, saving time and money in the final phases of production.
Research and Education
Universities and research institutions use SIL to investigate new algorithms and experiment with different parameter values. The ability to run multiple scenarios at minimal cost drives innovation in many fields. Students gain hands-on experience testing real code in a digital platform, building critical problem-solving skills. Research groups also benefit from streamlined collaboration as they share and refine simulation models across disciplines.
Steps to Implement SIL Testing in Your Development Process
Effective SIL testing relies on careful preparation and consistent refinement. Teams that invest time in setting clear objectives for each test phase often spot potential flaws long before final production. This proactive approach boosts organizational confidence and accelerates project milestones. A phased rollout strategy, combined with robust automation, ensures that code changes are verified quickly.
Several steps guide you through a streamlined SIL workflow, each stage laying the groundwork for the next. Following a structured sequence creates an organized progression from initial setup to final validation. Thorough documentation of results helps everyone stay aligned, reducing confusion and keeping the entire team moving forward. The following sections highlight the core actions involved in a typical SIL process.
Step 1: Define Test Requirements
Start by specifying clear objectives, such as identifying memory usage constraints or verifying real-time response in critical loops. Narrow targets help you focus on essential metrics, saving time during debugging. This stage also involves determining the scope, such as which modules require immediate attention. A precise roadmap guides testing efforts and promotes accountability.
Step 2: Build Accurate Models
Simulation fidelity depends on the quality of the models used to replicate operational conditions. Teams gather real measurements or theoretical data to ensure the mathematical representations closely match actual scenarios. This phase often includes calibration, validation, and iterative adjustments to refine accuracy. Well-crafted models allow software components to behave as they would in eventual hardware tests.
Step 3: Integrate Production Code
Bringing real code into the simulated platform is essential for spotting issues that might not appear in purely model-based tests. Development teams compile their modules and connect them to the simulation framework under consistent version control practices. Small incremental merges reduce the chance of major disruptions later, leading to smoother collaboration. This step confirms that each part of the system cooperates reliably, paving the way for final validation.
Step 4: Automate Test Execution
Manual testing can be slow and prone to oversight, which delays progress. Automated scripts run repeated scenarios, collect results, and generate clear reports that quickly identify anomalies. This approach cuts operational costs, particularly when you need to validate large volumes of test cases in a limited timeframe. Consistent automation also supports continuous integration by providing near-instant feedback on each code commit.
Step 5: Evaluate Outcomes and Optimize
Each test run should deliver quantifiable metrics showing how the software performed. Teams compare these results against predefined acceptance criteria to decide if further refinement is necessary. This closed-loop feedback cycle drives incremental improvements that ultimately strengthen product stability. A data-driven mindset ensures that final deployments meet the highest standards for efficiency and reliability.
Implementing these steps in a methodical manner ensures that SIL testing becomes a key component of your development pipeline. Projects benefit from early detection of flaws, cost-effective trial runs, and a streamlined handoff to hardware-based validation.
Trends in SIL Testing
Growth in cloud computing and artificial intelligence is reshaping how SIL tests are conducted, providing on-demand computational resources and automated analysis. Advanced machine learning algorithms assist with anomaly detection by comparing outcomes against complex baseline patterns. This capability stands out for teams that require around-the-clock testing without manual oversight. The result is a more responsive system that flags potential problems early.
Another emerging direction is the integration of high-fidelity physics engines, which allow even more accurate representations of operational conditions. This level of realism supports deeper exploration of performance under varying load profiles, communication delays, and multi-system interactions. As software becomes more intricate, expanded SIL frameworks will play an essential role in ensuring robust code. Adaptability and data-driven approaches will remain central as new industries adopt large-scale validation.
SIL testing creates a strategic advantage for developers seeking a dependable path to validate software before hardware investment. Careful planning and systematic execution help you capitalize on faster turnaround times, improved reliability, and lower costs. This method often serves as the bridge between conceptual coding efforts and hardware checks. Teams that implement SIL effectively find themselves better prepared to seize untapped potential and deliver results with minimal technical setbacks.
Organizations that incorporate SIL testing at multiple stages see added confidence in final software quality. This systematic approach helps stakeholders adapt to shifting requirements and manage resources more effectively. The future of SIL looks bright as technology advances, making it easier to conduct automated, high-precision tests on any scale. Engineers who adopt these tactics position themselves for smoother, more cost-effective product rollouts.
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 Software-in-the-loop
What is software in the loop, and why is it popular now?
This practice involves running compiled code in a virtual setup to test its stability and logic flow before deploying any hardware. Many teams adopt it for faster development cycles, lower costs, and reduced risk of late-stage issues.
How does software-in-the-loop definition differ from hardware-based methods?
The software-in-the-loop definition focuses on validating code within a simulation, while hardware-based methods require physical devices. SIL is more cost-effective and suitable for early development, whereas hardware approaches are typically used later to confirm real interactions.
Can SIL be applied in smaller projects or academic research?
Yes, SIL applies to projects of all sizes, including research and educational contexts. Students often benefit from learning SIL concepts because it teaches them to analyze real code outcomes without expensive equipment.
Is it difficult to maintain a SIL framework as the project grows?
Growth in SIL can be managed with strategic planning, proper version control, and clear guidelines for adding new models and test cases. Scalable software platforms and automated scripts make it easier to support larger codebases and more complex requirements.
Does SIL testing replace other types of validation?
SIL testing does not replace hardware tests entirely; it lays the groundwork by identifying software-level flaws first. Later stages still benefit from Hardware-in-the-Loop or physical prototyping to confirm that the integrated system performs as intended.
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)?
