PSO and P&amp;O based MPPT technique for SPV panel under varying atmospheric conditions

Suryavanshi, Rahul; Joshi, Diwakar R.; Jangamshetti, Suresh H.

doi:10.1109/epscicon.2012.6175270

Cited by 25 publications

(10 citation statements)

References 10 publications

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“…Different local points and only one global point will be generated on the P-V characteristic curve. A technique of using Perturbation and Observation method (P&O) combined with a Particle Swarm Optimization method (PSO) has shown an efficient result for tracking global MPP and differentiate it from the local ones [15,16]. However, it has the disadvantage of long convergence time and failure to track global MPP rapidly, especially when the array is exposed to fast changing weather conditions.…”

Section: (1)mentioning

confidence: 99%

A Hybrid (ACO-PSO) Algorithm Based on Maximum Power Point Tracking and its Performance Improvement within Shadow Conditions

Aaref¹,

Mohammed²,

Noori³

2018

IJET

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In this study, a hybrid Ant Colony Optimization-Particle Swarm Optimization (ACO-PSO) algorithm was proposed to optimally determine the maximum power point tracking (MPPT) parameters. The main goal of current study is to improve the overall performance of the MPPT system.The efforts of oscillation filtering and noise suppression were taken in this design, as well as the time response and the settling time. The proposed method is employed to track the global MPP under different shadow conditions, based on three different irradiation levels to test the ability and accuracy of the proposed method. The results of tracking MPP by the proposed MPPT technique showed that the improved method tracked the MPP for all the tested cases with a reasonable accuracy and in a very short convergence time as compared to the P&O method.

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Section: (1)mentioning

confidence: 99%

A Hybrid (ACO-PSO) Algorithm Based on Maximum Power Point Tracking and its Performance Improvement within Shadow Conditions

Aaref¹,

Mohammed²,

Noori³

2018

IJET

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“…To accommodate quick variations in irradiance, this method must be modified. Among the several techniques, the perturb observe algorithm is the most straightforward and cost-effective [4]. Incremental Conductance (INC) is a more advanced version of the (P&O) method to address all of the algorithm's shortcomings.…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization for Maximum Power Point Tracking Under Varying Atmospheric Conditions

Hussain¹,

Talib²

2022

Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9

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Based on research into Photovoltaic (PV) systems under diverse conditions, and a new maximum power-point tracking approach was developed. Due to the presence of variable circumstances, PV curves have several peaks, decreasing the efficiency of the conventional techniques. As a result, the suggested algorithm, based on the technique of particulate swarm (PSO) optimization, enhances the output power of photovoltaic (PV) systems under such abnormal conditions and outperforms existing methods. The suggested method is evaluated using MATLAB under numerous scenarios involving non-uniform irradiation and varying temperature levels, and to investigate its performance sufficiently, the outputs of the method suggested are compared for the P&O technique This study aims to explain the design and simulation of a particle swarm optimization (PSO) technique with a boost converter for determining the maximum permissible power of solar photovoltaic panels under changing climatic conditions. The simulations showed that the tracker ability of the PSO algorithm is highly effective, much quicker, and has a shorter settling time and overshoot than conventional techniques.

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“…The RL model is an unsupervised learning environment in which artificial agents (representatives) continue to learn and behave directly based on rough interactions with the environment (usually called policies); i.e., with the PV system. RL based MPPT technology has been proposed both for uniform radiation [22] , [23] and PSC [24] , [25] . To reduce the effort of RLMPPT techniques, frequently the action space has got to be discretized.…”

Section: Introductionmentioning

confidence: 99%

Modeling & implementation of DRLA based partially shaded solar system integration with 3-ϕ conventional grid using constant current controller

Guntupalli

Sudhakaran

Raj

2022

Heliyon

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PSO and P&O based MPPT technique for SPV panel under varying atmospheric conditions

Cited by 25 publications

References 10 publications

A Hybrid (ACO-PSO) Algorithm Based on Maximum Power Point Tracking and its Performance Improvement within Shadow Conditions

A Hybrid (ACO-PSO) Algorithm Based on Maximum Power Point Tracking and its Performance Improvement within Shadow Conditions

Particle Swarm Optimization for Maximum Power Point Tracking Under Varying Atmospheric Conditions

Modeling & implementation of DRLA based partially shaded solar system integration with 3-ϕ conventional grid using constant current controller

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