and thoroughly test fault monitoring and isolation algorithms in a safe, repeatable environment. After verifying and validating the design in the desktop environment, control and monitoring algorithms can be converted automatically to production-quality C or HDL code. This code can then be tested in a real-time environment to further reduce risk before making final hardware choices.
Integrating bidirectional power converters into the power system is only part of the challenge. To ensure that large-scale deployment of EVs and bidirectional power converters will not compromise grid stability or reliability, engineers must determine how these systems interact with the grid under a wide range of operating conditions. Engineers employ an essential tool for evaluating component and grid-level performance: system-level simulation studies.
Conducting Simulation Studies to Evaluate EV Charging Impacts on the Grid
Assessing the impact of EV charging on grid response requires detailed power system simulation studies, which engineers perform using Model-Based Design. Power system simulations are broadly classified into two types: phasor and electromagnetic transient( EMT). Phasor simulations are better suited for long-duration grid impact studies of EV charging, as they enable quasistatic simulations to be conducted over larger steps and longer time periods. A quasistatic simulation does not require detailed simulated dynamic responses. Instead, it focuses on moving through many operating points, where time steps can range from a few minutes to an hour, and the studied time periods can range from a few hours to a year or longer.
Quasistatic simulations over long time periods provide information on anticipated power demand throughout the system’ s lifetime. They are used for component sizing, evaluating technology mixes, and planning system upgrades. EMT studies are necessary when more detailed information about the operation of specific technologies is required, such as assessing the impact of power electronic switching harmonics on the power system.
Grid impact studies require engineers to consider potentially thousands of operational scenarios involving connecting EVs at multiple grid locations. For efficient operational scenario simulation on a large scale, parallel computing can distribute the scenarios across multiple cores.
Lumen Freedom Develops V2G-Ready Wireless Charging Systems
Lumen Freedom used Model-Based Design to develop wireless charging systems with built-in flexibility to meet future needs. Creating models for the communications systems, power electronics, and state machine enabled engineers to simulate the system’ s operation. Engineers used MATLAB ® and Simulink ® to design the core software models, main logic for the entire system, and the communication controller, which manages communication between the vehicle and charging pad. Rod Wilson, General Manager of Lumen Freedom, says,“ Our system will be ready for the transition to vehicle-to-home and vehicle-to-grid scenarios when the demand is there.”
V2G as a Catalyst for Grid Modernization
V2G technology can enhance grid stability and efficiency by enabling bidirectional EV battery charging. This approach offers system-level benefits, such as peak grid power demand mitigation and supporting the reliable operation of distributed energy resources. Advanced simulation models and smart charging algorithms enable precise energy management optimization, improving grid resilience and reducing reliance on emission-intensive power plants. As V2G systems see wider adoption, ongoing development and rigorous validation of these technologies are essential to building a more sustainable and robust energy infrastructure.
EV charging stations are typically connected to the grid through inverter-based resources( IBRs), which are power converters operated via digital control. IBR simulation requires small time steps— on the order of microseconds or nanoseconds— to capture the effects of power electronic switching, as well as detailed modeling of power converter topology and control systems.
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