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Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach
摘要： The integration of photovoltaic systems (PVSs) in future power systems grows into a more attractive choice. Thus, the studies related to PVSs operation have gained immense interest. Particularly, research in identifying PV cell model parameters remains an agile field because of the non-linearity of PV cell characteristics and its wide dependency on meteorological conditions of irradiation level and temperature. This paper proposes an Opposition-based Learning Modified Salp Swarm Algorithm (OLMSSA) for accurate identification of the two-diode model parameters of the electrical equivalent circuit of the PV cell/module. Six metaheuristic algorithms, including the recently released basic algorithm SSA, used with the benchmark test PV model of the double diode, and a practical PV module, are employed to assess the performance of OLMSSA. The experimental results and the in-depth comparative study clearly demonstrate that OLMSSA is highly competitive and even significantly better than the reported results of the majority of recently-developed parameter identification methods.
关键词： Metaheuristic Optimizer,Two-diode model,I-V characteristics,Parameters extraction,Photovoltaic panels,Salp Swarm Algorithm
更新于2025-09-19 17:13:59
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Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach
摘要： Estimation of single-diode and two-diode solar cell parameters by using chaotic optimization approach (COA) is addressed. The proposed approach is based on the use of experimentally determined current-voltage (I-V) characteristics. It outperforms a large number of other techniques in terms of average error between the measured and the estimated I-V values, as well as of time complexity. Implementation of the proposed approach on the I-V curves measured in laboratory environment for different values of solar irradiation and temperature prove its applicability in terms of accuracy, effectiveness and the ease of implementation for a wide range of practical environment conditions. The COA-based parameter estimation is, therefore, useful for PV power converter designers who require fast and accurate model for PV cell/module.
关键词： COA,Solar cell parameters,single-diode model,two-diode model
更新于2025-09-12 10:27:22
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[IEEE 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Kota Kinabalu, Malaysia (2018.10.7-2018.10.10)] 2018 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Modifications to Accelerate the Iterative Algorithm for the Two-diode Model of PV Module
摘要： This work proposes two modifications—namely Adaptive Search Range (ASR) and improved Newton-Raphson Method (iNRM), to enhance the computation speed of the iterative computational method for the two-diode model. These modifications significantly improve the computation speed without introducing any compromise in terms of accuracy. Moreover, they are very simple to implement and do not require any additional information as input. By implementing ASR, the algorithm is only required to calculate a fraction (25%) of the P- V curve at every iteration. On the other hand, the iNRM improves the calculation of the curve by guiding the initial value of current for each point of voltage. To evaluate their effectiveness, the original algorithm and its modified versions are coded in Matlab script. They are used to identify the model parameters of three PV modules of different technologies. The computation time of the algorithm with both ASR and iNRM implemented is observed to be up to 4.7 times faster. Furthermore, the values of the model parameters are computed to be exactly equal—which implies that the accuracy of the original algorithm the is retained. With these merits, the modifications are envisaged to be critical improvements to the algorithm, especially for application in computers with lower specifications.
关键词： photovoltaic,pv modelling,two-diode model,simulation
更新于2025-09-09 09:28:46