The photovoltaic (PV) model is used in simulation studies to validate system design such as the maximum power point tracking algorithm and microgrid system. It is often difficult to simulate a PV module characteristic under different environmental conditions due to the limited information provided by the manufacturers. In this paper, a new approach using particle swarm optimization (PSO) with inverse barrier constraint is proposed to determine the unknown PV model parameters. The proposed method has been validated with three different PV technologies and the results show that the maximum mean modeling error at maximum power point is less than 0.02% for P m p and 0.3% for V m p .Index Terms-Inverse-barrier method, maximum power point (MPP), particle swarm optimization (PSO), photovoltaic (PV) model.

To increase the boost capability with minimum passive components, existing transformer-based Z-source inverter (ZSI) topologies require the turn ratio to be increased. This results in larger transformer windings to be used in high dc-ac voltage gain applications. This shortcoming is addressed in this study by introducing a sigma-ZSI (ΣZSI) that improves the dc-ac voltage gain by reducing the turn ratio leading to a lower winding transformer. The proposed topology is compared with the TZSI as they used the same number of transformers and capacitors configured in an X-shaped network. The comparison shows that the ΣZSI will have a higher dc-ac voltage gain at a turn ratio lower than 1.618 for a given shoot-through duty cycle allowing the use of smaller transformers. Simulation and experimental results have validated the effectiveness of the proposed ΣZSI.

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