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This paper presents a time-efficient modeling and simulation strategy for aggregated microinverters in large-scale photovoltaic systems. As photovoltaic microinverter systems are typically comprised of multiple power electronic converters, a suitable modeling and simulation strategy that can be used for rapid prototyping is required. Dynamic models incorporating switching action may induce significant computational burdens and long simulation durations. This paper introduces a single-matrix-form approach using the average model of a basic microinverter with two power stages consisting of a dc-dc and dc-ac converter. The proposed methodology using a common or intermediate source between two average models of cascaded converters to find the overall average model is introduced and is applicable to many other converter topologies and combinations. It provides better flexibility and simplicity when investigating various power topologies in system-level studies of microinverter and other power electronic systems. A 200 W prototype microinverter is tested to verify the proposed average and dynamic models. Furthermore, MATLAB/Simulink (2010a, Mathworks, Natick, MA, USA) is used to show the improved simulation speed and maintained accuracy of the multiple microinverter configurations when the derived average model is compared to a dynamic switching simulation model. [ABSTRACT FROM AUTHOR]

In this paper, power loss and cost models of power electronic converters based on converter ratings and datasheet information are presented. These models aid in creating rapid prototypes which facilitate the component selection process. Through rapid prototyping, users can estimate power loss and cost which are essential in design decisions. The proposed approach treats main power electronic components of a converter as building blocks that can be arranged to obtain multiple topologies to facilitate rapid prototyping. In order to get system-level power loss and cost models, two processes are implemented. The first process automatically provides minimum power loss or cost estimates and identifies components for specific applications and ratings; the second process estimates power losses and costs of each component of interest as well as the whole system. Two examples are used to illustrate the proposed approaches—boost and buck converters in continuous conduction mode. Achieved cost and loss estimates are over 93% accurate when compared to measured losses and real cost data. This research presents derivations of the proposed models, experimental validation of the models and demonstration of a user friendly interface that integrates all the models. Tools presented in this paper are expected to be very useful for practicing engineers, designers, and researchers, and are flexible and adaptable with changing or new technologies and varying component prices. [ABSTRACT FROM AUTHOR]