Abstract
The appropriate selection of parameters of photovoltaic models is necessary for an accurate evaluation, control, and optimization of photovoltaic systems. Even though various strategies have been developed to address this issue, but, a precise and reliable scheme for identifying the model parameters remains a challenge. To improve parameter identification of different photovoltaic models, an opposition-based learning reptile search algorithm with Cauchy mutation strategy (OBL-RSACM) is introduced in this research. In OBL-RSACM, the individuals in search space get doubled by generating their opposite guess of the solution which overcomes the issue of strucking of solution in local minima and also enhances the convergence speed. Cauchy mutation strategy is also incorporated in the basic reptile search algorithm (RSA) which enhances the search mechanism, modifies the control parameter, mutation-driven scheme, and greedy approach of selection during the search process of the RSA. Thus, improves the exploration process and maintains the proper balance between exploration and exploitation. The proposed OBL-RSACM is applied to estimate the parameters of different photovoltaic models, i.e., single diode, double diode, and photovoltaic module. A comprehensive comparison of experimental results and analysis demonstrated that OBL-RSACM outperformed other state-of-the-art algorithms in terms of accuracy, reliability, and computational efficacy.
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Data availability statement
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- \(I_{out}\) :
-
Output current
- \(I_{photo}\) :
-
Photo generated current source
- \(I_{shunt}\) :
-
Shunt resistance current
- \(I_{diode}\) :
-
Diode current
- \(R_{sh}\) :
-
Shunt resistance
- \(R_{s}\) :
-
Series resistance
- \(I_{sat}\) :
-
Reverse saturation current
- \(V_{0ut}\) :
-
Output voltage
- \(n\) :
-
Diode ideal factor
- \(k\) :
-
Boltzmann constant
- \(q\) :
-
Magnitude of charge
- \(T\) :
-
Temperature
- \(I_{diode1}\) :
-
First diode current
- \(I_{diode2}\) :
-
Second diode current
- \(I_{sat1}\) :
-
Diffusion currents
- \(I_{sat2}\) :
-
Saturation currents
- \(NP\) :
-
Number of populations
- \(D\) :
-
Dimension
- RSA:
-
Reptile search algorithm
- OBL:
-
Opposition based learning
- CM:
-
Cauchy mutation
- RMSE:
-
Root mean square error
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Chauhan, S., Vashishtha, G. & Kumar, A. Approximating parameters of photovoltaic models using an amended reptile search algorithm. J Ambient Intell Human Comput 14, 9073–9088 (2023). https://doi.org/10.1007/s12652-022-04412-9
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DOI: https://doi.org/10.1007/s12652-022-04412-9