Maximum power point tracking of grid connected photovoltaic system employing model predictive control

This paper presents a maximum power point tracking (MPPT) technique using model predictive control (MPC) for single phase grid connected photovoltaic (PV) systems. The technique exhibits fast convergence, which is ideal for rapidly varying environmental conditions such as changing temperature or insolation or changes in morphology of the PV array itself. The maximum power of PV system is tracked by a high gain DCDC converter and feeds to the grid through a seven-level inverter. Considering the stochastic behavior of the solar energy resources and the low conversion efficiency of PV cells, operation at the maximum possible power point is necessary to make the system economical. The main contribution of this paper is the development of incremental conductance (INC) method using two-step model predictive control. The multilevel inverter controller is based on fixed step current predictive control with small ripples and low total harmonic distortion (THD). The proposed MPC method for the grid connected PV system speeds up the control loop by sampling and predicting the error two steps before the switching signal is applied. As a result, more energy will be captured from the PV system and injected into grid particularly during partially cloudy sky. A comparison of the developed MPPT technique to the conventional INC method shows significant improvement in dynamic performance of the PV system. Implementation of the proposed predictive control is presented using the dSPACE DS1103.