Extraction of efficient electrical parameters of solar cell using firefly and cuckoo search algorithm

Chakrabarti, Tapas; Sharma, Udit; Chakrabarti, Tyajodeep; Sarkar, Subir Kumar

doi:10.1109/iicpe.2016.8079503

Cited by 4 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To improve the voltage stability of a power system based on the minimization of the total voltage deviation of the system, Rao et al utilized CS to obtain optimal tuning of the thyristorcontrolled series capacitor [21]. Chakrabarti et al applied CS optimization to extract the parameters of a doublediodelumped electrical circuit model of a solar cell [22]. Kumari et al proposed an approach to pre dict software development effect based on the CS algorithm [23].…”

Section: Minimum Zone Sphericity Evaluation Based On a Modified Cucko...mentioning

confidence: 99%

Minimum zone sphericity evaluation based on a modified cuckoo search algorithm with fuzzy logic

Huang

Jiang

Chao

et al. 2018

Meas. Sci. Technol.

View full text Add to dashboard Cite

This study proposes an intelligent algorithm that combines a modified cuckoo search (MCS) algorithm with an adaptive fuzzy logic controller (MCSF) to evaluate minimum zone sphericity with high speed and accuracy. To accelerate the convergence of the iteration procedure, the proposed MCS algorithm introduces an optimized initial solutions distribution model and a modified biased/selective mechanism to the original cuckoo search. Moreover, an adaptive fuzzy logic controller is designed to ensure global search ability in the early stage of the search process and strong convergence performance in the later stage of iteration. This is achieved by adaptively adjusting the control coefficient α of step size and the probability pa of discovering an invasive cuckoo’s egg in MCS. Simulation and comparison results indicate that the proposed method achieves excellent convergence behavior and reaches the global optima faster than conventional heuristic methods. The MCSF method runs 60 iterations in ~0.4 s, and its results for the standard deviation of sphericity are 1/8–1/2 of those of the conventional heuristic methods. The proposed method can easily be extended to evaluate minimum zone roundness, cylindricity, and straightness.

show abstract

Section: Minimum Zone Sphericity Evaluation Based On a Modified Cucko...mentioning

confidence: 99%

Minimum zone sphericity evaluation based on a modified cuckoo search algorithm with fuzzy logic

Huang

Jiang

Chao

et al. 2018

Meas. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…Compared to analytical methods, numerical methods require analyzing the entire I-V curve of PV modules. Due to the multimodal nature of the fitness function in parameter extraction problems, intelligent optimization algorithms are widely applied, including Particle Swarm Optimization (PSO) (Soon and Low, 2012), Artificial Bee Swarm Optimization (ABSO) (Askarzadeh and Rezazadeh, 2013;Oliva et al, 2014;Garoudja et al, 2015), Cuckoo Search (CS) (Chakrabarti et al, 2016), Bacterial Foraging Algorithm (BFA) (Asif and Li, 2008;Krishnakumar et al, 2013;Rajasekar et al, 2013;Subudhi and Pradhan, 2018), Genetic Algorithm (GA) (Harrag and Messalti, 2015;Kumar and Shiva, 2019), Differential Evolution (DE) Jiang et al, 2013), and Flower Pollination Algorithm (FPA) (Benkercha et al, 2018;Khursheed et al, 2021). In Ref (Soon and Low, 2012), the particle swarm optimization algorithm was employed, and the concept of inverse barrier constraints was introduced to restrict the parameter search space and thereby enhance the accuracy of parameter identification.…”

mentioning

confidence: 99%

A MIC-LSTM based parameter extraction method for single-diode PV model

Hao,

Liu,

Deng

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

In recent years, the installed capacity of renewable energy systems has seen rapid growth, particularly in photovoltaic (PV) power. Photovoltaic modules, being the fundamental elements of the PV system, play a crucial role in determining system performance. However, the challenge arises from the inconsistent decay rates of PV modules, which significantly impact the accuracy of PV system modeling. To address this issue, this paper introduces a novel MIC-LSTM based parameter extraction method for the single-diode PV model. This method focuses on accurately deriving PV module model parameters under various decay rates. By establishing a mapping relationship between the current-voltage (I-V) curve characteristics and the five unknown parameters in the photovoltaic module model, the proposed method demonstrates high precision in parameter extraction. Simulation and experimental verifications are carried out to validate the proposed method, where the extraction accuracy is 99.3%, 98.39%, 98.85%, 97.91%, and 98.36% for the five unknown model parameters.

show abstract

Power Distribution Loss Reduction Using Cuckoo Search

Fuad

Azlin

Zahari

et al. 2018

2018 7th International Conference on Computer and Communication Engineering (ICCCE)

View full text Add to dashboard Cite

The distribution system has the most portion power loss compared to the transmission and generation systems. One of the effective methods to reduce the power loss in the system is by reconfiguring the existing network. In distribution system, there are two types of switches, which are sectionalizing switches and tie-switches. Reconfiguration process changes the status of those switches until the objective is achieved. In this study, the reconfiguration method is proposed for distribution system using the Cuckoo Search Algorithm (CSA) method. The system used is a standard IEEE 33-bus radial distribution system. The main objective is to reduce the power loss in the system while satisfying the distribution constraints. The proposed method is used to give an optimal configuration of distribution network for power loss reduction and its validity is done by comparing it with Particle Swarm Optimization (PSO).

show abstract

Extraction of efficient electrical parameters of solar cell using firefly and cuckoo search algorithm

Cited by 4 publications

References 9 publications

Minimum zone sphericity evaluation based on a modified cuckoo search algorithm with fuzzy logic

Minimum zone sphericity evaluation based on a modified cuckoo search algorithm with fuzzy logic

A MIC-LSTM based parameter extraction method for single-diode PV model

Power Distribution Loss Reduction Using Cuckoo Search

Contact Info

Product

Resources

About