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An efficient data sheet based parameter estimation technique of solar PV.

K M Charu1,2, Padmanabh Thakur1, Nikita Rawat1

  • 1Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, Uttarakhand, India.

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|March 19, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient solar photovoltaic (PV) parameter estimation technique using manufacturer datasheets. The developed method with Particle Swarm Optimization (PSO) offers precise and rapid PV model parameter estimation.

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Area of Science:

  • Renewable Energy
  • Electrical Engineering
  • Computational Methods

Background:

  • Accurate solar photovoltaic (PV) model parameter estimation is crucial for performance analysis and grid integration.
  • Existing methods often require extensive data or complex procedures, limiting their practical application.

Purpose of the Study:

  • To develop an efficient and precise parameter estimation technique for solar PV models using only manufacturer datasheet information.
  • To compare the performance of Particle Swarm Optimization (PSO) and Harmony Search (HS) for this parameter estimation task.

Main Methods:

  • A nonlinear least square objective function was formulated using manufacturer datasheet variables.
  • Particle Swarm Optimization (PSO) and Harmony Search (HS) algorithms were applied to optimize the objective function.
  • Performance indices, including percentage maximum power deviation index (%MPDI) and overall model deviation index (OMDI), were used for evaluation.

Main Results:

  • The developed technique with PSO demonstrated superior performance over HS, achieving %MPDI of 0.0214% and OMDI of 0.213.
  • Comparative analysis showed the PSO-based method yielded smaller %MPDI (0.0041%) and OMDI (0.005) than existing methods.
  • The technique exhibited rapid convergence, completing estimation in just 5 seconds, and requires minimal data.

Conclusions:

  • The proposed parameter estimation technique, leveraging manufacturer datasheets and PSO, is highly efficient, accurate, and fast.
  • This data-efficient approach simplifies the process of obtaining accurate solar PV model parameters, enhancing their practical utility.