Modeling and Testing of a Grid-Tied Inverter Controller

solar energy sources with electric utility grid on the background

Learn how to use Simulink, Simscape Electrical, and Speedgoat real target machines to model and implement a grid-tied inverter controller for efficient renewable energy conversion.

  • 1003

Grid-tied inverters convert the direct current (DC) produced by renewable energy sources into alternating current (AC) suitable for connection to the electric utility grid. Engineers must design and implement a robust control system to ensure optimal performance and reliable operation of these inverters. In this video series, MathWorks and Speedgoat experts explain how to use Simulink®, Simscape Electrical™, and Speedgoat real target machines to model, simulate, and implement such a control system.

Design Considerations

The first video delves into the essential design considerations and workflow steps when developing a grid-tied solar inverter controller. These considerations include:

  • Algorithm design
  • Desktop simulation
  • Control hardware selection
  • Hardware-in-the-loop testing
  • Compliance evaluation against the grid code.

Understanding these considerations sets the foundation for designing a control system that meets regulatory requirements and ensures seamless grid integration.

Control Design Workflow

The second video outlines a comprehensive control design workflow tailored to grid-tied solar inverters. It introduces key components like the MPPT (Maximum Power Point Tracking) algorithm, grid current control, and grid voltage control. The video emphasizes the importance of model-based design and demonstrates how Simulink can be used to create a virtual environment for testing and optimizing control algorithms.

Control Design Tasks

The third video delves deeper into the specific control design tasks of developing a grid-tied solar inverter controller. It covers topics such as model fidelity, designing the MPPT algorithm, and automatic tuning of PID gains.

Deploying a Control Algorithm

The fourth and final video focuses on the practical aspect of deploying a control algorithm onto a physical grid-tied solar inverter using Speedgoat hardware. It discusses considerations for real-time implementation, automatic code generation for C and HDL code, hardware-in-the-loop (HIL) testing, and deployment of the control algorithm to a microcontroller. This step ensures that the designed control system operates reliably in real-world scenarios and maximizes the efficiency of the solar inverter.

By following these steps, engineers can design and implement robust control systems for inverters that will ensure optimal performance and reliable operation over their entire lifespan.

Featured products

MathWorks® products

Speedgoat products

Learn more

If you would like to take your education to the next level, check out our Training Services. But if you don’t have time to learn, model, and implement a grid-tied inverter controller yourself, you should still be aware of world-changing trends. Reach out to our Consulting team, and get a ready-made solution perfectly customized for your project.

Recommended Events

Recommended Posts

Machine Learning with MATLAB

Explore how MATLAB transforms the world of machine learning. Discover 5 areas where MATLAB can help solve diverse learning problems. From interactive apps to Simulink integration, we’ve got you covered.

Deep Learning with MATLAB

Today we are living in a renaissance of artificial intelligence, Machine Learning, and Deep Learning, and everyone wants to be a part of this movement. But the question is if you interested in using deep learning technology, where do you begin?

Power Electronics Control Design

Discover three areas where Power Electronics Control Design with Simulink can transform your engineering projects. Reduce project time by 50%, access thousands of electrical modeling components, and build and tune motor control algorithms with ease.