The transformerless photo voltaic (PV) inverter system connected to grid has created a new trend in the energy market due to its reduced space requirement, low cost and increased efficiency when compared to its counterpart i.e with transformer. Transformerless inverter system suffers from common mode leakage currents due to parasitic capacitances between PV panels and ground. However, different new inverter topologies and state of the art modulation strategies are proposed in the literature to counter it. A dc-dc converter is of more significant to maintain the constant PV output voltage at string level and extract maximum power from PV. This paper presents Artificial neural network (ANN) algorithm-based dc-dc converter to track maximum power from PV module connected to grid without transformer. It also compares the performance of ANN based algorithm with conventional perturb and Observe maximum power point tracking (MPPT) technique. MATLAB/Simulink environment is used to pursue the simulation of ANN based algorithm and analyses its performance for variety of irradiance levels.

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The era of Renewable Energy sources has overtaken the usage of conventional energy sources like coal, fossil fuels etc. This paper presents grid interface of single phase transformerless inverter system using enhanced phase locked loop. To connect solar PV with grid it is required to estimate phase angle, voltage amplitude and phase angle measurement of grid and the output of inverter. It is required to track exact utility voltage vector for reliable control of power to the grid. This paper compares the frequency measurement and phase angle and voltage amplitude using simple phase locked loop system along with enhanced phase locked loop so that the enhanced phase locked loop (EPLL) is proved to be giving superior performance over simple phase locked loop. The simulation of both the techniques are pursued and the results are compared.