Interior Search Optimization Algorithm for Modeling Power Curve of Wind Turbine

Ahmed Agwa

Abstract


Incorrect sensor reading, operation stoppage, and defect, produce noise in the records of wind speed and the synchronized wind turbine (WT) power. This noise still remains even after purification so fitted curve of wind turbine power model (WTPM) may differ from that in the datasheet. WTPM is vital due to its role in managing and predicting wind energy. Identification of WTPM parameters can be addressed as a nonlinear optimization issue. The objective function targets minimizing the root of the mean squared errors among the accompanying computed and measured wind power points with subjection to group of parameters constraints. In this article, a newly designed interior search optimization algorithm (ISA) is applied to identify the WTPM obscure parameters. Three parametric models namely two logistic functions and amended hyperbolic tangent are analyzed neatly. Simulations are accomplished using MATLAB. The ISA applicability is evaluated via comparing its results with the observed results of two WTs. To legalize the ISA results, they are compared with other methods results. It can be declared here that the ISA performs well and possesses a fine strength to generate WTPM parameters with lesser errors.

Keywords


Parametric model; power curve; wind turbine; optimization approaches; interior search algorithm

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v10i3.11011.g8010

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