MATLAB and Simulink for Developing Power Generation and Transmission Equipment

From the leading wind turbine manufacturers to companies developing high voltage transmission equipment, engineers use MATLAB® and Simulink® to design control and monitoring algorithms for a wide range of power generation and transmission equipment.

  • Develop and validate algorithms in a safe environment using complex system models that include physical components (mechanical, electrical, hydraulic, etc.), control systems, and fault injection
  • Detect design errors early and evaluate different control strategies
  • Deploy code on embedded targets (using microcontrollers or FPGAs), PLCs, or production servers
  • Optimize equipment design to increase uptime and equipment efficiency

Power Plant Model

With MATLAB and Simulink, engineers can use a simulation model of the components, systems, or plants to test and validate their design before implementing it on actual equipment. Virtual commissioning allows engineers to identify and eliminate design errors early in the process, decreasing the development and validation time, while reducing risk and potential damage.

Power Plant Model

Control Design

Control Design

MATLAB and Simulink help engineers develop control and supervisory logic algorithms for power equipment and test them under operating conditions that are not easy to verify in field conditions.

Engineers use plant modeling in designing control algorithms for applications that include inverter or wind turbine control, as well as other grid-compliant controllers.

Automatic code generation enables the deployment of the algorithms to the actual control hardware.


Predictive Maintenance

Engineers use MATLAB® and Simulink® to develop and deploy condition monitoring and predictive maintenance software for Power Generation and Transmission equipment.

Using interactive apps to access and pre-process data, engineers can design algorithms (e.g., to determine remaining useful life [RUL]) and deploy them in operation. This allows engineers to optimize service intervals and reduce maintenance costs when compared to reactive or preventive maintenance.

Predictive Maintenance

Using MATLAB and Simulink for Power Generation and Transmission Equipment

“Using Model-Based Design we developed a complex control system in significantly less time than our traditional process would have required. We eliminated months of hand-coding by generating code from our models, and we used simulations to enable early design verification.”

Anthony Totterdell, GE Grid