A novel optimal identification of various solar PV cell parameters by using MRDT controller
Sunkara Sunil Kumar1, K Balakrishna2
1Vignan's Foundation for Science Technology and Research, Vadlamudi, India.
Scientific Reports
|May 7, 2024
Summary
Accurate solar power generation relies on precise photovoltaic (PV) cell parameter extraction. A new Modified Rao-based Dichotomy Technique (MRAODT) effectively identifies PV cell parameters, outperforming other algorithms.
Area of Science:
- Renewable Energy Systems
- Photovoltaic Cell Modeling
Background:
- Increasing reliance on renewable energy sources (RES) necessitates efficient solar power generation.
- Accurate parameter extraction is crucial for optimizing solar power supply and meeting peak demand.
Purpose of the Study:
- To introduce a Modified Rao-based Dichotomy Technique (MRAODT) for accurate photovoltaic (PV) cell parameter identification.
- To evaluate the performance of MRAODT against existing algorithms for PV parameter extraction.
Main Methods:
- The Modified Rao-based Dichotomy Technique (MRAODT) was developed to determine the actual parameters of PWP 201 polycrystalline and RTC France PV cells.
- MRAODT performance was benchmarked against the teaching and learning algorithm, African vultures algorithm, and tuna intelligence algorithm.
Main Results:
- The MRAODT demonstrated superior performance in PV cell parameter identification compared to the evaluated algorithms.
- MRAODT achieved faster parameter extraction times and quicker convergence, enhancing accuracy.
Conclusions:
- The Modified Rao-based Dichotomy Technique (MRAODT) offers a highly accurate and efficient method for photovoltaic cell parameter extraction.
- MRAODT presents a significant advancement for optimizing solar power generation systems.
Keywords:
2-Didoes based solar cell3-Diodes based solar cellAccuracyConvergence rateDichotomyPlus modified Rao techniqueRMSESingle diode cellMore Related Videos
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