Shuffled Complex Evolution on Photovoltaic Parameter Extraction: A Comparative Analysis

Gomes, Ruan C. M.; Vitorino, Montiê A.; Corrêa, Maurício Beltrão de Rossiter; Fernandes, Darlan A.; Wang, Ruxi

doi:10.1109/tste.2016.2620941

Cited by 65 publications

(24 citation statements)

References 32 publications

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“…Although the current models are used as electrical circuits and can analyze mathematically, the identification of parameters is not just as simple because the structure of PV cells is described with the concepts of solid-state physics. 20 Based on many published works, the P-V and I-V curves, which are based on the diode model, can be used as direct indicators of performance of solar cell and modules. 18 One of the most important requirements in maximizing the capacity of PV systems is to extract parameters of a solar cell/module.…”

Section: Modelsmentioning

confidence: 99%

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Generation and combination of the solar cells: A current model review

Khatibi

Astaraei

Ahmadi

2019

Energy Science & Engineering

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Generally, first and second generations of photovoltaic (PV) cells are including mono‐crystalline silicon, amorphous silicon, and dye‐synthesized solar cells. Investigating the electrical current behavior of these sorts of PV cells shows that a modified multi‐ or single diode(s) model with shunt and series resistance can use as a good choice in a specific range of the current. For other constructions such as multi‐junction PV cells that consist of the third generation, the network models are the best choice. Also, the network models can be used for the first and second generations to improve the validity of model in the wider range of current. In addition to existing generations, PV array and modules, which are serial and parallel arrays of PV cells, will lead to a higher current or voltage. The main disadvantage of using these sorts of systems is their more space occupation. This problem can be solved by using the concentrated PV (CPV) systems that focus the received irradiation on a smaller surface. By considering the generated current, voltage, power, temperature effect, and financial analysis, it seems third‐generation PV systems are more efficient among all the generations. Finally, by considering the ratio of generated current on the occupied space, the CPV systems will be a better choice.

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Section: Modelsmentioning

confidence: 99%

“…19 It seems that the most effective parameters of the efficiency of PV systems are physical parameters. 20 Based on many published works, the P-V and I-V curves, which are based on the diode model, can be used as direct indicators of performance of solar cell and modules. 18,19,[21][22][23] There are two different types of models for a PV cell.…”

Section: Modelsmentioning

confidence: 99%

Generation and combination of the solar cells: A current model review

Khatibi

Astaraei

Ahmadi

2019

Energy Science & Engineering

View full text Add to dashboard Cite

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“…ese data points such as short-circuit point, open-circuit point, and maximum power point of the current-voltage (I-V) characteristic curve are nameplate rating data measured under standard test condition (STC). ey will change over time due to PV degradation [6]. In addition, some assumptions and approximations are introduced to simplify the established mathematical models.…”

Section: Introductionmentioning

confidence: 99%

Application of Supply-Demand-Based Optimization for Parameter Extraction of Solar Photovoltaic Models

et al. 2019

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Modeling solar photovoltaic (PV) systems accurately is based on optimal values of unknown model parameters of PV cells and modules. In recent years, the use of metaheuristics for parameter extraction of PV models gains more and more attentions thanks to their efficacy in solving highly nonlinear multimodal optimization problems. This work addresses a novel application of supply-demand-based optimization (SDO) to extract accurate and reliable parameters for PV models. SDO is a very young and efficient metaheuristic inspired by the supply and demand mechanism in economics. Its exploration and exploitation are balanced well by incorporating different dynamic modes of the cobweb model organically. To validate the feasibility and effectiveness of SDO, four PV models with diverse characteristics including RTC France silicon solar cell, PVM 752 GaAs thin film cell, STM6-40/36 monocrystalline module, and STP6-120/36 polycrystalline module are employed. The experimental results comparing with ten state-of-the-art algorithms demonstrate that SDO performs better or highly competitively in terms of accuracy, robustness, and convergence. In addition, the sensitivity of SDO to variation of population size is empirically investigated. The results indicate that SDO with a relatively small population size can extract accurate and reliable parameters for PV models.

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“…In this context, the incorrectly specified values for these data points will degrade the extraction accuracy considerably due to the extraction strategy of "taking a part for the whole" [5,6]. In addition, those employed special data points are factory measured under the STC, while the PV degradation makes the model parameters change over time [7], which further influences the extraction accuracy of the "taking a part for the whole" methods.…”

Section: Introductionmentioning

confidence: 99%

Modified Search Strategies Assisted Crossover Whale Optimization Algorithm with Selection Operator for Parameter Extraction of Solar Photovoltaic Models

et al. 2019

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Extracting accurate values for involved unknown parameters of solar photovoltaic (PV) models is very important for modeling PV systems. In recent years, the use of metaheuristic algorithms for this problem tends to be more popular and vibrant due to their efficacy in solving highly nonlinear multimodal optimization problems. The whale optimization algorithm (WOA) is a relatively new and competitive metaheuristic algorithm. In this paper, an improved variant of WOA referred to as MCSWOA, is proposed to the parameter extraction of PV models. In MCSWOA, three improved components are integrated together: (i) Two modified search strategies named WOA/rand/1 and WOA/current-to-best/1 inspired by differential evolution are designed to balance the exploration and exploitation; (ii) a crossover operator based on the above modified search strategies is introduced to meet the search-oriented requirements of different dimensions; and (iii) a selection operator instead of the “generate-and-go” operator used in the original WOA is employed to prevent the population quality getting worse and thus to guarantee the consistency of evolutionary direction. The proposed MCSWOA is applied to five PV types. Both single diode and double diode models are used to model these five PV types. The good performance of MCSWOA is verified by various algorithms.

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Shuffled Complex Evolution on Photovoltaic Parameter Extraction: A Comparative Analysis

Cited by 65 publications

References 32 publications

Generation and combination of the solar cells: A current model review

Generation and combination of the solar cells: A current model review

Application of Supply-Demand-Based Optimization for Parameter Extraction of Solar Photovoltaic Models

Modified Search Strategies Assisted Crossover Whale Optimization Algorithm with Selection Operator for Parameter Extraction of Solar Photovoltaic Models

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