This study presents a high-efficient maximum power point tracking (MPPT) of photovoltaic (PV) systems by means of model-predictive control (MPC) techniques that is applied to a high-gain DC-DC converter. The high variability and stochastic nature of solar energy requires that the MPPT control continuously adjust the power converter operating point in order to track the changing maximum power point; a concept well known in the literature. The main contribution of this study is a modelpredictive-based controller with a fixed step that is combined with the traditional incremental conductance (INC) method. This technique improves the speed at which the controller can track rapid changes in solar insolation and results in an increase in the overall efficiency of the PV system. The controller speeds up convergence since MPC predicts error before the switching signal is applied to the high-gain multilevel DC-DC converter and thus is able to choose the next switch event to minimise error between the commanded and actual converter operation. Comparing the proposed technique to the conventional INC method shows substantial improvement in MPPT effectiveness and PV system performance. The performance of the proposed MPC-MPPT is analysed and validated experimentally.

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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 DC-DC 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.