Model predictive control of grid connected inverters using different discretization strategies

Global warming and its implications like rising sea levels and higher temperatures have lit a fire underneath the world's sense of urgency towards a seemingly inevitable disaster. Thanks to social media, people are now aware of the issue and are pressuring lawmakers to legislate laws that dampen the growth rate of the pollution we are generating. As a result, we are slowly shifting our reliance on environmentally unfriendly to sustainable energy. Power electronics is a key enabling technology for the development of sustainable energy, as it allows to convert power coming from a variety of sources into utility grade power. In particular, voltage sourced inverters (VSIs) are used to convert dc power, e.g., power generated by photovoltaic arrays, into ac power, allowing the power source to be connected to the ac grid. The control of a grid-connected two-level VSI using model predictive control (MPC) is the main subject of this paper. The MPC implementation will be approached with three different discretization methods for the plant: first-order forward Euler's method, Modified Euler's method and third-order Runge Kutta method. MPC performance is tested under all stated discretization methods, comparing dynamic response and computational burden.