Robust Model Predictive Control for Photovoltaic Inverter System with Grid Fault Ride-Through Capabi

Abstract

In this paper, the integration of photovoltaics into distribution power systems with grid fault ride-through capability is investigated by proposing a robust model predictive control scheme. The control system is developed in normal conditions. It regulates the constant dc-link voltage, and it also provides the maximum power transfer to the grid by controlling unity power factor. During grid abnormality, the control system is reorganized to maintain a constant dc-link voltage, prevents the active power and injects a reactive power to support the grid operation. The model predictive control scheme is derived from the dc-link and the grid models. The proposed control scheme is experimentally validated using a hardware prototype of the photovoltaic system connected to an emulated three-phase grid. Experimental results show that the proposed controller is able to provide dc-link voltage regulation, while curtailing the active power during grid abnormalities. Moreover, the controller is able to support the grid under such conditions. The control scheme is quite robust against unknown disturbances and parametric uncertainties in the system.

Existing System

Takagi-Sugeno-Kang probabilistic fuzzy neural network control.

Proposed System

A robust model predictive control scheme has been proposed to operate a three phase grid-connected PV inverter system with grid fault ride-through capability. The robustness of the predictive controller is achieved by a disturbance compensator through an integral action, which eliminates the steady state tracking error. The controlled PV system has been experimentally validated under different disturbances such as external disturbance (variable irradiance) and parametric uncertainties. It proves to be efficient in transferring adequate power during the grid fault for the proper operation of the grid.

Architecture

Grid connected PV energy conversion system