An effective QUATRE algorithm based on reorganized mechanism and its application for parameter estimation in improved...

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Computational Intelligence

Background:

• Traditional photovoltaic (PV) module parameter estimation methods are constrained by reference standards.
• The double diode model (DDM) is a common framework, but parameter extraction can be challenging.
• Existing algorithms like QUATRE may suffer from slow convergence and local optima.

Purpose of the Study:

• To develop a modified PV module model for parameter estimation independent of reference conditions.
• To enhance the QUATRE algorithm for improved precision and convergence in PV module parameter extraction.
• To validate the efficacy of the proposed RQUATRE algorithm against other metaheuristic approaches.

Main Methods:

• Modification of the double diode model (DDM) for reference-independent PV module parameterization.
• Integration of a recombination mechanism into the QUATRE algorithm, creating the RQUATRE algorithm.
• Comparative analysis of RQUATRE against FMO, PIO, QUATRE, PSO, and GWO on the CEC2017 test suite.
• Experimental validation of the RQUATRE algorithm for PV module parameter extraction.

Main Results:

• The RQUATRE algorithm demonstrated superior performance, outperforming other algorithms in numerous comparisons on the CEC2017 test suite.
• Achieved a Root Mean Square Error (RMSE) of 2.99 × 10^-3 in PV module parameter extraction, surpassing compared algorithms.
• Attained final fitting values below 10% for the Intensity Analysis Equation (IAE), meeting fitting requirements.

Conclusions:

• The proposed modified PV module model and RQUATRE algorithm offer a robust solution for accurate parameter estimation.
• The RQUATRE algorithm provides enhanced convergence and precision, overcoming limitations of traditional methods.
• The developed approach is suitable for PV module transformation and reconfiguration tasks.