Intelligent approach-based hybrid control algorithm for integration of solar photovoltaic system in smart grid environment

Integration of solar PV as a distributed generator (DG) require efficient and coordinated control measures for the proper synchronization. In this paper, a hybrid control algorithm for single stage solar photovoltaic (PV) system integrated with low voltage (LV)/medium voltage (MV) grid is proposed. The hybrid algorithm utilizes I cos ϕ technique and quasi-Newton back-propagation (QNBP) neural network (NN). The main contributions of the present work are: i) support the utility grid by feeding power and connected loads, ii) provide harmonics elimination, reactive power compensation, load balancing, iii) also works in power factor correction (PFC) and zero voltage regulation modes, iv) provides power quality improvement. The proposed control of grid tied PV system provides very fast response during static and dynamic conditions. The obtained results are compared with other well-established algorithms available in the literature. The comparison of the proposed algorithm is done on the basis of various parameters such as DC voltage undershoot and overshoot, settling time and THD in grid currents. The developed system is demonstrated in MATLAB/SIMULINK platform. Using the proposed algorithms there is significant improvement of 1.1% in total harmonic distortion (THD) of source current. The results of proposed controllers are experimentally validated on a developed laboratory protype.