Search Results - (( panel extraction method algorithm ) OR ( using optimization _ algorithm ))

Performance analysis of PSO MPPT for photovoltaic (PV) system during irradiance changes / Kharismi Burhanudin by Burhanudin, Kharismi

“…Particle swarm optimization is soft computing methods which follow the bird swarm to track maximum power from PV panel. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail, M.S., Moghavvemi, Mahmoud, Mahlia, T.M.I.

“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm by Ismail M.S., Moghavvemi M., Mahlia T.M.I.

“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”

PARTICLE SWARM OPTIMIZATION MAXIMUM POWER POINT TRACKING FOR PARTIALLY SHADED SOLAR PV by Alvin, Ngu Tien Leong

“…This study proposes a particle swarm optimization (PSO) algorithm based on MPPT for the PGS to operate under PSC. …”
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

“…The result revealed that the ANN performance had the highest accuracy when training using the LM training algorithm. The ANN with the seven inputs (seven significant compounds from Z-score pre-processing technique) trained by one hidden neuron of LM algorithm provided the best performance with 100% for accuracy, specificity, sensitivity and precision as well as minimum convergence epoch.…”
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A novel MPPT approach for photovoltaic system using Pelican optimization and high-gain DC–DC converter by Akter, Khadiza, Motakabber, S. M. A., Alam, A. H. M. Zahirul, Yusoff, Siti Hajar, Pachauri, Rupendra Kumar, Malik, Hasmat, Jadoun, Vinay Kumar

“…In response to these needs, this study introduces the Pelican Optimization Algorithm (POA), a novel nature-inspired stochastic optimization technique designed to track the Maximum Power Point (MPP) of solar sources with high precision. …”
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Identifying Damage Types in Solar Panels Through Surface Image Analysis with Naive Bayes by Wiliani, Ninuk, T.K.A, Rahman, Ramli, Suzaimah

“…This study investigates the utilization of statistical feature extraction methods alongside Bernoulli Naive Bayes (BNB) and Gaussian Naive Bayes (GNB) algorithms to categorize different defect types, such as cracks, scratches, spots, and non-defective surfaces, through digital image analysis. …”
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Peripheral interface controller-based maximum power point tracking algorithm for photovoltaic DC to DC boost controller by Z. A. Ghani, E. Onn, M. Y. Zeain, Apriana Toding, F. A. Azidin, H. Othman, Z. Zakaria, Herwnsyah bin Lago

“…A method of developing a maximum power point tracking (MPPT) algorithm for photovoltaic (PV) utilizing a peripheral interface controller (PIC) is presented in this paper. …”
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Fuzzy logic-based hill climbing technique for photovoltaic maximum power point tracking converter by Taghvaee, Mohammad Hossein

“…Simulation results are presented to validate performance of the algorithm under different irradiation schemes, and to compare with the results obtained from conventional algorithm. …”
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

“…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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Fault-tolerant power extraction strategy for photovoltaic energy systems by Boutasseta, Nadir, Ramdani, Messaoud, Mekhilef, Saad

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Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin, M. F. F., Ab Rashid, N. M. Zuki, N. M.

“…PSO is also compared with another algorithm like Whale Optimization Algorithm, Ant Lion Optimizer, Dragonfly Algorithm, Grasshopper Optimization Algorithm, Moth-flame Optimization and Sine Cosine Algorithm. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm by Chong K.L., Lai S.H., Ahmed A.N., Wan Jaafar W.Z., El-Shafie A.

A hybrid bat�swarm algorithm for optimizing dam and reservoir operation by Yaseen Z.M., Allawi M.F., Karami H., Ehteram M., Farzin S., Ahmed A.N., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., El-Shafie A.

Fractional chaos maps with flower pollination algorithm for partial shading mitigation of photovoltaic systems by Yousri D., Babu T.S., Allam D., Ramachandaramurthy V.K., Beshr E., Eteiba M.B.

Improvement Of Solar Farm Efficiency And Energy Production By Using Distributed MPPPT by Janesh Kiran A/L Kalaichelvan

Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…Based on the experimental results, the optimized DA algorithm is a much better training algorithm for ANNs as compared to the usual gradient-descent backpropagation algorithm since the resultant ANNs trained by the optimized DA achieve higher accuracy. …”
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