Solar radiation and solar energy estimation using ANN and Fuzzy logic concept: A comprehensive and systematic study

Patel, Dharmendrakumar A.; Patel, Shriya; Patel, Poojan; Shah, Manan

doi:10.1007/s11356-022-19185-z

Cited by 29 publications

(10 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many artificial neural networks (ANNs) are employed in the solution of issues such as pattern matching and data compression. As a promising and rising technology, artificial neural networks (ANNs) have emerged as a popular tool for forecasting and prediction [31,32].…”

Section: Related Workmentioning

confidence: 99%

Artificial Intelligence-Based Deep Learning Model for the Performance Enhancement of Photovoltaic Panels in Solar Energy Systems

Meena

Singh

Urhekar

et al. 2022

International Journal of Photoenergy

View full text Add to dashboard Cite

This study looks into artificial intelligence methods for scaling solar power systems, such as standalone, grid-connected, and hybrid systems, in order to lessen environmental effect. When all essential information is provided, conventional sizing methods may be a feasible alternative. It is impossible to apply typical procedures in instances where data is unavailable. The new suggested artificial intelligence model employing multilayered perceptrons is employed for sizing solar systems, and this model functions on current photovoltaic modules that incorporate hybrid-sizing models; so, they should not be rejected entirely. In this work, the convergence speed of the proposed model for single diode, two diodes, and three diodes are the comparison factors to estimate the performance of the proposed model.

show abstract

Section: Related Workmentioning

confidence: 99%

Artificial Intelligence-Based Deep Learning Model for the Performance Enhancement of Photovoltaic Panels in Solar Energy Systems

Meena

Singh

Urhekar

et al. 2022

International Journal of Photoenergy

View full text Add to dashboard Cite

show abstract

“…Artificial neural networks (ANN) play a crucial role in predicting solar radiation. [16][17][18] In a comparative study by Patel et al 19 and Behrang et al 20 the results obtained from ANN models were compared with those from conventional models, revealing significant improvements. AlShabi et al 21 introduced a novel estimation method for PV solar cell models, employing a multigroup grey wolf optimizer that exhibits superior performance when compared to other algorithms.…”

Section: Introductionmentioning

confidence: 99%

A novel soft sensing method using intelligent modeling method for solar irradiance and temperature in distributed PV power plant

Zhu,

Jiang,

Zhou

et al. 2024

Energy Science & Engineering

View full text Add to dashboard Cite

Distributed photovoltaic (PV) power plants often lack solar irradiance monitoring devices, significantly hindering crucial functions such as power forecasting, fault diagnosis, and performance calculation for distributed PV. To address this issue, a real‐time method for soft sensing solar irradiance was proposed in distributed PV. First, we investigated the typical relationship between solar irradiance, ambient temperature, and the electrical characteristics of PV cells. Based on this relationship, we utilized the small sample modeling technique of the Genetic Algorithm‐Support Vector Machine to calculate the ambient temperature. Subsequently, a solar irradiance calculation model based on the backpropagation neural network was developed, taking the PV array voltage, current, calculated ambient temperature, and power as inputs. This approach enables for the estimation of solar irradiance in distributed PV power plants through a simple and efficient calculation process. To demonstrate the reliability and flexibility of the algorithm, we conducted testing with data under various input conditions, such as different power plant configurations, and seasons, coefficient of determination for the proposed model reached 0.95. Overall, the novelty of the proposed method offers a practical solution for soft sensing of solar irradiance in PV power plants, enabling accurate performance analysis and effective operation management without hardware investment.

show abstract

“…ANN performance can be developed optimally by using fuzzy logic which presents the best analytical model [26]. The combination of fuzzy logic with ANN is the most effective for analysis compared to other empirical models based on input parameters for better result efficiency [27]. Fuzzy logic can show a better ANN performance improvement based on the parameter values used [28].…”

Section: Introductionmentioning

confidence: 99%

Optimization artificial neural network classification analysis model diagnosis Gingivitis disease

Ariandi

Yanto²,

Jamhur³

et al. 2023

IJEECS

View full text Add to dashboard Cite

<span lang="EN-US">Gingivitis is a disease that can be caused by the buildup of bacteria and plaque caused by leftover food. This disease can attack anyone, especially children who are not aware of maintaining dental and oral health. This study aims to build and optimize the classification analysis model for the diagnosis of Gingivitis. The classification analysis model was built using the artificial neural network (ANN) method which was optimized using fuzzy logic and the multiple linear regression (MRL) method. Optimization with fuzzy aims to develop a pattern of rules in the detection. The MRL method is also used as a process of measuring analysis patterns to ensure the analytical model presents maximum results. The results study indicate that the optimization of fuzzy and MRL methods provides excellent output. These results are based on the fuzzy output which can provide a pattern of 40 rules. The MRL method is can present the level of correlation of each analysis variable with a significant output having an average value of 94.2%. Based on the results of this study, the analysis model that is optimized with the fuzzy logic method and MRL contributes to maximizing the process of diagnosing Gingivitis.</span>

show abstract

Solar radiation and solar energy estimation using ANN and Fuzzy logic concept: A comprehensive and systematic study

Cited by 29 publications

References 66 publications

Artificial Intelligence-Based Deep Learning Model for the Performance Enhancement of Photovoltaic Panels in Solar Energy Systems

Artificial Intelligence-Based Deep Learning Model for the Performance Enhancement of Photovoltaic Panels in Solar Energy Systems

A novel soft sensing method using intelligent modeling method for solar irradiance and temperature in distributed PV power plant

Optimization artificial neural network classification analysis model diagnosis Gingivitis disease

Contact Info

Product

Resources

About