scholarly journals Parameter Estimation of Three Diode Photovoltaic Model Using Grasshopper Optimization Algorithm

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 497 ◽  
Author(s):  
Omnia S. Elazab ◽  
Hany M. Hasanien ◽  
Ibrahim Alsaidan ◽  
Almoataz Y. Abdelaziz ◽  
S. M. Muyeen
Keyword(s):  
Mathematical Model ◽  
Optimization Algorithm ◽  
Parameter Extraction ◽  
Unknown Parameters ◽  
Pv Module ◽  
Highly Nonlinear ◽  
Grasshopper Optimization Algorithm ◽  
Pv Modules ◽  
Simulation Results ◽  
Grasshopper Optimization

While addressing the issue of improving the performance of Photovoltaic (PV) systems, the simulation results are highly influenced by the PV model accuracy. Building the PV module mathematical model is based on its I-V characteristic, which is a highly nonlinear relationship. All the PV cells’ data sheets do not provide full information about their parameters. This leads to a nonlinear mathematical model with several unknown parameters. This paper proposes a new application of the Grasshopper Optimization Algorithm (GOA) for parameter extraction of the three-diode PV model of a PV module. Two commercial PV modules, Kyocera KC200GT and Solarex MSX-60 PV cells are utilized in examining the GOA-based PV model. The simulation results are executed under various temperatures and irradiations. The proposed PV model is evaluated by comparing its results with the experimental results of these commercial PV modules. The efficiency of the GOA-based PV model is tested by making a fair comparison among its numerical results and other optimization method-based PV models. With the GOA, a precise three-diode PV model shall be established.

Performance Evaluation of Hybrid Photovoltaic Thermal Thermoelectric Collector Using Grasshopper Optimization Algorithm With Simulated Annealing

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Anmol Gupta ◽  
Sanjay Agrawal ◽  
Yash Pal
Keyword(s):  
Mathematical Model ◽  
Performance Evaluation ◽  
Simulated Annealing ◽  
Optimization Algorithm ◽  
Single Channel ◽  
Electrical Energy ◽  
Average Value ◽  
Grasshopper Optimization Algorithm ◽  
Mass Flowrate ◽  
Grasshopper Optimization

Abstract In this paper, a mathematical model of a single-channel photovoltaic thermal (PVT) air collector incorporated with a thermoelectric (TE) module has been presented. The overall electrical energy obtained from the photovoltaic thermal-thermoelectric (PVT-TE) collector is 5.78% higher than the PVT collector. Further, the grasshopper optimization algorithm (GOA) and hybrid grasshopper optimization algorithm with simulated annealing (GOA-SA) have been proposed and implemented to optimize the parameters of opaque PVT-TE collector. Although there are different parameters that influence the performance of PVT-TE system, yet in this study only four parameters, viz., length of the channel (L), width of the channel (b), mass flowrate of air in the channel (mair), and temperature of air at the inlet of channel (Tair,i) are considered for optimization. The simulation result demonstrates that the hybrid GOA-SA algorithm turned out to be an exceptionally effective method for optimal tuning of the parameters of the PVT-TE system. The result explicitly shows that the average value of overall electrical efficiency and exergy gain are 15.27% and 27.0565 W, respectively, when the parameters are optimized by the suggested GOA-SA algorithm which is way ahead with respect to the outcomes obtained with that of the calculated values or using GOA algorithm alone.

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

2019 ◽  
Vol 11 (23) ◽  
pp. 2795 ◽  
Author(s):  
Guojiang Xiong ◽  
Jing Zhang ◽  
Dongyuan Shi ◽  
Lin Zhu ◽  
Xufeng Yuan ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problems ◽  
Parameter Extraction ◽  
Search Strategies ◽  
Whale Optimization Algorithm ◽  
Solar Photovoltaic ◽  
Unknown Parameters ◽  
Highly Nonlinear ◽  
Whale Optimization ◽  
Selection Operator

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.

Robust design of a robot gripper mechanism using new hybrid grasshopper optimization algorithm

2021 ◽  
Author(s):  
Betül Sultan Yildiz ◽  
Nantiwat Pholdee ◽  
Sujin Bureerat ◽  
Ali Riza Yildiz ◽  
Sadiq M. Sait
Keyword(s):  
Robust Design ◽  
Optimization Algorithm ◽  
Robot Gripper ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization

An Image Segmentation Method Based on Two-Dimensional Entropy and Chaotic Lightning Attachment Procedure Optimization Algorithm

2020 ◽  
Vol 34 (11) ◽  
pp. 2054030 ◽  
Author(s):  
Wei Liu ◽  
Shuai Yang ◽  
Zhiwei Ye ◽  
Qian Huang ◽  
Yongkun Huang
Keyword(s):  
Image Segmentation ◽  
Maximum Entropy ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Computational Time ◽  
Two Dimensional ◽  
Threshold Segmentation ◽  
Grasshopper Optimization Algorithm ◽  
Grasshopper Optimization ◽  
Competitive Algorithms

Threshold segmentation has been widely used in recent years due to its simplicity and efficiency. The method of segmenting images by the two-dimensional maximum entropy is a species of the useful technique of threshold segmentation. However, the efficiency and stability of this technique are still not ideal and the traditional search algorithm cannot meet the needs of engineering problems. To mitigate the above problem, swarm intelligent optimization algorithms have been employed in this field for searching the optimal threshold vector. An effective technique of lightning attachment procedure optimization (LAPO) algorithm based on a two-dimensional maximum entropy criterion is offered in this paper, and besides, a chaotic strategy is embedded into LAPO to develop a new algorithm named CLAPO. In order to confirm the benefits of the method proposed in this paper, the other seven kinds of competitive algorithms, such as Ant–lion Optimizer (ALO) and Grasshopper Optimization Algorithm (GOA), are compared. Experiments are conducted on four different kinds of images and the simulation results are presented in several indexes (such as computational time, maximum fitness, average fitness, variance of fitness and other indexes) at different threshold levels for each test image. By scrutinizing the results of the experiment, the superiority of the introduced method is demonstrated, which can meet the needs of image segmentation excellently.

scholarly journals An Improved Generalized Method for Evaluation of Parameters, Modeling, and Simulation of Photovoltaic Modules

2017 ◽  
Vol 2017 ◽  
pp. 1-19 ◽  
Author(s):  
Vandana Jha ◽  
Uday Shankar Triar
Keyword(s):  
Modeling And Simulation ◽  
Standard Test ◽  
Unknown Parameters ◽  
Photovoltaic Modules ◽  
Pv Module ◽  
Test Conditions ◽  
Pv Modules ◽  
Evaluation Of Parameters ◽  
Output Characteristics ◽  
Matlab Programming

This paper proposes an improved generalized method for evaluation of parameters, modeling, and simulation of photovoltaic modules. A new concept “Level of Improvement” has been proposed for evaluating unknown parameters of the nonlinear I-V equation of the single-diode model of PV module at any environmental condition, taking the manufacturer-specified data at Standard Test Conditions as inputs. The main contribution of the new concept is the improvement in the accuracy of values of evaluated parameters up to various levels and is based on mathematical equations of PV modules. The proposed evaluating method is implemented by MATLAB programming and, for demonstration, by using the values of parameters of the I-V equation obtained from programming results, a PV module model is build with MATLAB. The parameters evaluated by the proposed technique are validated with the datasheet values of six different commercially available PV modules (thin film, monocrystalline, and polycrystalline) at Standard Test Conditions and Nominal Operating Cell Temperature Conditions. The module output characteristics generated by the proposed method are validated with experimental data of FS-270 PV module. The effects of variation of ideality factor and resistances on output characteristics are also studied. The superiority of the proposed technique is proved.

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