ANN BASED MODEL PREDICTIVE CONTROL OF SINGLE PHASE GRID CONNECTED PHOTOVOLTAIC SYSTEM USING MPPT TECHNIQUE

Nowadays solar energy has great importance. Because it is easily available resource for energy generation. But the only problem is efficiency of solar system. And to increase its efficiency many MPPT techniques are available for use. Incremental conductance (INC) method is one of those well known MPPT techniques. Development of INC method using two - step model predictive control by emp loying artificial neural network (ANN) is the main contribution of this paper. The multilevel inverter controller is based on fixed step current predictive control with small ripples and low total harmonic distortion (THD). The MPC method for the grid conn ected PV system speeds up the control loop by sampling and predicting the error two steps before the switching signal is applied. PI controller is used in the INC method and MPC - MPPT methods. If any disturbances are occurred in the system then PI controlle r does not give better dynamic response. It is less tolerable to the changes. To overcome these, PI controller is replaced with ANN in MPC - MPPT method. ANN is introduced to improve transient stability of the system and THD of the current. The proposed MPC - MPPT technique with ANN for a grid connected PV System was implemented using MATLAB and SIMULINK. Performance of the ANN in MPC - MPPT method is compared with the PI controller in INC method and MPC - MPPT method .