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Identification Estimated with Bat Search Algorithms for Modeling of Inverter System


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DOI: https://doi.org/10.15866/iree.v13i2.14650

Abstract


The grid interlinked type inverter is a device that can efficiently transmit electricity through the conversion of power electronic systems. It would be advantageous to make use of various forms of renewable energy when considering the transmission of electric power. The prediction based on numerical simulations will be helpful in the development for the understanding and design of power electronic systems, predictive controller, power flow, stability, power quality analysis of the grid interlinked type inverter. This paper seeks to present a new technique examining the grid interlinked type inverter when creating a model of a nonlinear system identification through the use of nonlinear autoregressive exogenous inputs - wavelet neural network (NLARX-WNN). The NLARX-WNN was able to demonstrate the modeling approach needed for a single phase grid interlinked type microhydropower inverter. In addition, the model has estimated the optimal set of parameters via the bat search algorithms (BA). The tests of microhydro electric type inverter is performed and its model is defined. The simulated results made the NLARX-WNN solution, which was estimated with the BA, capable of the proposed scheme and this may serve to improve the accuracy of estimation when assessing the behaviour of the single phase grid interlinked type inverter. Once completed, the mathematical model can represent the system for analysing and identifying the characteristics of an electrical power system.
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Keywords


NLARX-WNN; Inverter Modeling; System Identification; Bat Search Algorithms

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References


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