A Modified Bat Optimization Algorithm Based Parameter Extraction of Solar Cell Models
Chellaswamy C1, Muthammal R2, Geetha T S3
1Chellaswamy C, Department of Electronics and Communication Engineering, Lords Institute of Engineering and Technology, Hyderabad, India.
2Muthammal R, Department of Electronics and Communication Engineering, Saveetha Engineering College, Chennai. India.
3Geetha T S, Department of Electronics and Communication Engineering, Sriram Engineering College, Chennai. India.

Manuscript received on 03 April 2019 | Revised Manuscript received on 08 May 2019 | Manuscript published on 30 May 2019 | PP: 2330-2337 | Volume-8 Issue-1, May 2019 | Retrieval Number: A1135058119 /19©BEIESP
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Abstract: This article presents a new parameter extraction of solar photovoltaic (PV) cell models using a modified bat algorithm (MBA) to increase the speed and accuracy. The two diode models such as one diode and two diode models are used to verify the performance of the proposed MBA in parameter extraction problem. The proposed MBA algorithm overcomes the shortcomings of the bat algorithm. The novelty includes local and global searching ability of bat algorithm is improved by adapting the weight parameter, effectively increase the search region, and uniformity and ergodicity of population are improved by the chaos search strategy. The measured and estimated data sets are used to analyze the performance. Comparison is performed between other optimization algorithms such as simplified bird mating optimizer (SBMO), bat algorithm (BA), and artificial bee colony (ABC) and the results indicate that the proposed MBA outperforms among other methodology in terms of root mean squared error and robustness. The outcome of the proposed MBA shows that it is an efficient alternative method suit for extracting different parameters of solar PV models.
Index Terms: Photovoltaic Cell, Parameter Extraction, Solar Cell Model, Modified Bat Algorithm.

Scope of the Article: Data Analytics Modelling and Algorithms