Sliding mode control for Maximum Power Point Tracking of photovoltaic inverters in microgrids

In this paper the design of sliding mode controllers for Maximum Power Point Tracking (MPPT) of a photovoltaic inverter in microgrids is presented. A master-slave configuration of the microgrid is considered in islanded operation mode where the photovoltaic Distributed Generation unit (DGu) serves as a slave. The DGu is also affected by nonlinearities, parameters and modelling uncertainties, which make the use of the sliding mode control methodology particularly appropriate. Specifically, a sliding mode controller, relying on the so-called unit vector approach, is first proposed to control the photovoltaic inverter. Then, a Second Order Sliding Mode (SOSM) controller, adopting a Suboptimal SOSM algorithm, is proposed to alleviate the chattering phenomenon and feed a continuos modulating signal into the photovoltaic inverter. Simulation tests, carried out on a realistic scenario, confirm satisfactory closed-loop performance of the proposed control scheme

Decentralized Sliding Mode Control of Islanded AC Microgrids with Arbitrary Topology

The present paper deals with modelling of complex microgrids and the design of advanced control strategies of sliding mode type to control them in a decentralized way. More specifically, the model of a microgrid including several distributed generation units (DGus), connected according to an arbitrary complex and meshed topology, and working in islanded operation mode (IOM), is proposed. Moreover, it takes into account all the connection line parameters and it is affected by unknown load dynamics, nonlinearities and unavoidable modelling uncertainties, which make sliding mode control algorithms suitable to solve the considered control problem. Then, a decentralized second order sliding mode (SOSM) control scheme, based on the Suboptimal algorithm is designed for each DGu. The overall control scheme is theoretically analyzed, proving the asymptotic stability of the whole microgrid system. Simulation results confirm the effectiveness of the proposed control approach