A Photovoltaic Load Predictive Control Model of Microgrid Based on Secondary Frequency Conversion under Random Conditions

With the increasing application rate of renewable energy and distributed generators based on power electronics technology in microgrid, its high random and low inertia power disturbance bring more problems to frequency control. In order to solve these problems, this article put forward a micro grid photovoltaic predictive control model with secondary frequency regulation under random conditions. The control strategy includes unknown input observers. RESs/DGs uses load virtual synchronous generator (VSG) control to increase the inertia of the system. In order to improve the effect of predictive control, unknown input observers are used to estimate the system state and random power disturbances. By overcoming the quadratic programming (QP) optimization problem with variable constraints, the distributed recovery power of each DG is received. By setting appropriate weighting factors, RESs/DGs can participate in secondary frequency control preferentially. An island microgrid model composed of photovoltaic power sources is established. Compared with the general secondary control system, this system improves the system frequency, increases the recovery speed, and diminishs the frequency deviation.