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A robust variable-λ least logarithmic hyperbolic cosine function adaptive filtering-based control algorithm for grid-connected solar PV system
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DOI：10.1016/j.epsr.2023.109955.png)
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Abstract
En 中文
This paper implements a robust variable-lambda least logarithmic hyperbolic cosine function adaptive filtering (VLlncosh)-based control algorithm for a grid-connected solar photovoltaic system (GCPVS) which includes DSTATCOM features while integrating PV power to the grid at enhanced power quality (PQ). In this paper, a single-stage topology of GCPVS is considered, which can reduce the complexity, cost, and maintenance associ-ated with DC-DC converter employed in two-stage topology. In GCPVS, the nonlinear loads, which deteriorate the quality of the power, are attached to the point of common coupling (PCC), and maximum extracted PV power is allocated between these loads and the grid. The power transfer at the grid takes place at unity power factor (UPF). The proposed VLlncosh algorithm estimates the fundamental weight components of the distorted load current for grid reference currents generation with a variable learning parameter to ensure fast initial conver-gence and more steady-state accuracy. The control algorithm operates GCPVS such that it provides compensation to the load current harmonics, unbalanced load current, and load reactive power while complying with IEEE-519-2022 standard. The VLlncosh-based control algorithm is implemented for GCPVS modeled in MATLAB/ Simulink to evaluate its performance through simulation results. Further, the control algorithm is validated using the experimental prototype setup of GCPVS in the laboratory. The comparative assessment of the VLlncosh al-gorithm is provided to confirm its superior performance over LMS, sign-error LMS, and LMF algorithms.
Keywords:
DSTATCOM
Least logarithmic hyperbolic cosine function
LMS
Photovoltaic
Power quality
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