An improved method for MPPT using ANN and GA with maximum power comparison through Perturb &amp; Observe technique

Prasad, Lal Bahadur; Sahu, Suneet; Gupta, Manika; Srivastava, Rishabh; Mozhui, Lichamo; Asthana, Dhawal

doi:10.1109/upcon.2016.7894653

Cited by 11 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The author in [82] proposed a hybrid technique in which a GA is used to optimize the ANN algorithm to accurately find the GMPP under PSC. In this method, the optimized data from the GA is used to train the ANN by using a Bayesian regulation technique that predicts the MPP at given irradiance and temperature.…”

Section: Ann With Gamentioning

confidence: 99%

Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review

2023

View full text Add to dashboard Cite

To efficiently and accurately track the Global Maximum Power Point (GMPP) of the PV system under Varying Environmental Conditions (VECs), numerous hybrid Maximum Power Point Tracking (MPPT) techniques were developed. In this research work, different hybrid MPPT techniques are categorized into three types: a combination of conventional algorithms, a combination of soft computing algorithms, and a combination of conventional and soft computing algorithms are discussed in detail. Particularly, about 90 hybrid MPPT techniques are presented, and their key specifications, such as accuracy, speed, cost, complexity, etc., are summarized. Along with these specifications, numerous other parameters, such as the PV panel’s location, season, tilt, orientation, etc., are also discussed, which makes its selection easier according to the requirements. This research work is organized in such a manner that it provides a valuable path for energy engineers and researchers to select an appropriate MPPT technique based on the projects’ limitations and objectives.

show abstract

Section: Ann With Gamentioning

confidence: 99%

Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review

2023

View full text Add to dashboard Cite

show abstract

“…Ref. [ 91 ] the author proposes two algorithms, the first hybrid combined ANN with Bayesian regulation (BR) and the second combining GA + ANN. The results are checked against simple P&O.…”

Section: Mppt Control Using Ann and Hybrid Metaherustic Algorithmsmentioning

confidence: 99%

Artificial Neural Networks in MPPT Algorithms for Optimization of Photovoltaic Power Systems: A Review

et al. 2021

View full text Add to dashboard Cite

The use of photovoltaic systems for clean electrical energy has increased. However, due to their low efficiency, researchers have looked for ways to increase their effectiveness and improve their efficiency. The Maximum Power Point Tracking (MPPT) inverters allow us to maximize the extraction of as much energy as possible from PV panels, and they require algorithms to extract the Maximum Power Point (MPP). Several intelligent algorithms show acceptable performance; however, few consider using Artificial Neural Networks (ANN). These have the advantage of giving a fast and accurate tracking of the MPP. The controller effectiveness depends on the algorithm used in the hidden layer and how well the neural network has been trained. Articles over the last six years were studied. A review of different papers, reports, and other documents using ANN for MPPT control is presented. The algorithms are based on ANN or in a hybrid combination with FL or a metaheuristic algorithm. ANN MPPT algorithms deliver an average performance of 98% in uniform conditions, exhibit a faster convergence speed, and have fewer oscillations around the MPP, according to this research.

show abstract

“…Simulations are carried out with the aid of Matlab/Simulink. Also, MPPT of a PV solar module in the perturb and observe method was introduced in the study [7], the research papers consist of comparison results obtained from the genetic algorithm optimized ANN MPPT system with the current system. With temperature and irradiance as its basis, the Bayesian regulation-oriented ANN approach performs system power output prediction at maximum power points.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Photovoltaic Panel Performance Through Artificial Neural Network and Maximum Power Point Tracking

Almajeed,

Fadhil,

Rasheed

et al. 2024

JESA

View full text Add to dashboard Cite

An improved method for MPPT using ANN and GA with maximum power comparison through Perturb & Observe technique

Cited by 11 publications

References 5 publications

Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review

Hybrid Maximum Power Extraction Methods for Photovoltaic Systems: A Comprehensive Review

Artificial Neural Networks in MPPT Algorithms for Optimization of Photovoltaic Power Systems: A Review

Enhancing Photovoltaic Panel Performance Through Artificial Neural Network and Maximum Power Point Tracking

Contact Info

Product

Resources

About