Hybrid maximum power point tracking technique based on PSO and incremental conductance

Abdulkadir, M.; Yatim, A.H.M.

doi:10.1109/cencon.2014.6967514

Cited by 19 publications

(15 citation statements)

References 10 publications

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“…The PSO has also been hybridized with the gravitational search algorithm (GSA) for the same purpose [35]. In addition, PSO also has been hybridized with incremental conductance [36], continuous genetic algorithm (CGA) [37], hill climbing [38,39], differential evolution (DE) [40], artificial neural networks (ANN) [41], simulated annealing [42], chaos searching technique [43], adaptive neuro-fuzzy inference system (PSO-ANFIS) [44], etc.…”

Section: Hybridizing the Pso With Other Mppt Techniquementioning

confidence: 99%

Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy

2020

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Partial shading of PV systems generates many peaks in the P–V curve. These peaks have one global peak (GP), the remaining being local peaks (LPs). Metaheuristic techniques such as PSO have proven superiority in capturing the GP and avoiding entrapment in an LP in comparison to conventional techniques. In case of partial shading conditions (PSC), the GP may change its position and value in the P–V curve and the PSO is unable to capture the GP unless they reinitialize. Reinitialization of PSO particles spends a long time for convergence; and it may cause premature convergence. This paper proposes a novel strategy for scanning the new position of the GP in case of PSC changes without a need for reinitialization. The proposed strategy sends a particle to the anticipated places of peaks to search for any peak with power greater than the current GP and when it locates this new GP it will move the PSO particles directly to the new GP. This strategy reduced the reinitialization time by 650% as compared to the time required for the random reinitialization of the conventional PSO technique. Moreover; this proposed strategy completely avoids the premature convergence associated with conventional PSO techniques.

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Section: Hybridizing the Pso With Other Mppt Techniquementioning

confidence: 99%

Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy

2020

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“…When there is rapid change of environmental conditions, there are global maxima along with local maxima. CIC with variable step size is not able to differentiate between local and global maxima, so further modification is made to track global maxima [41][42][43][44][45][46][47][48][49][50].…”

Section: By Increment Of Duty Cycle)mentioning

confidence: 99%

A Literature review on industrially accepted MPPT techniques for solar PV system

Yadav

Maurya

Gupta

2020

IJECE

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Solar energy is a clean renewable energy and it is available around 89,000 TW on the earth surface. To get maximum power from a solar PV system with minimum power transfer loss is one of the main design objectives of an energy transferring network. Power electronic devices perform a very important character for an efficient PV power tracking system control and either incorporates to transfer the generated power to the ac/dc grid or battery storage system. In this case the duty of the power electronics devices used in PV system is to track maximum power point under different operating conditions of environment, so that power tracking efficiency of solar PV system can be improved. This paper encapsulates based the on performance comparisions on the behavior of MPP under uniform and nonuniform operating conditions and selects the optimum duty cycle for industrially accepted MPPT techniques with their algorithm.

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“…Typically, an algorithm is used to search the region of GMPP identifying the corresponding value of voltage at the MPP. Then such value is used in a conventional MPPT, commonly P&O (Bataineh and Eid, 2018;Jiang et al, 2015;Jiang et al, 2013b;El-Helw et al, 2017), InC (Radjai et al, 2014;Punitha et al, 2013;Abdulkadir and Yatim, 2014) or HC (Chaieb and Sakly, 2018), in order to reach a GMPP. The primary advantage of those techniques is the capability of leading a conventional MPPT (such as P&O, InC or HC) to reach the GMPP under PSC and increase the efficiency of the system.…”

Section: Introductionmentioning

confidence: 99%

“…However, in such works the authors only compare the performance of hybrid methods to non-hybrid techniques, such as P&O, InC, HC, PSO and DE. For example, Abdulkadir and Yatim (2014) and Manickam et al (2016) compare their hybrid method to the conventional PSO method. In the same way, El-Helw et al (2017), present results comparison between the proposed hybrid method and non-hybrid ANN technique.…”

Section: Introductionmentioning

confidence: 99%

“…Batarseh and Zater (2018) reported 20 hybrid MPPT methods mentioned in literature that can be categorized into intelligent and non-intelligent techniques. Intelligent methods category includes techniques based on Fuzzy Logic Controllers (FLC) (Bataineh and Eid, 2018;Ajiatmo and Robandi, 2017), ANN (Jiang et al, 2015;Jiang et al, 2013b;El-Helw et al, 2017), PSO (Abdulkadir and Yatim, 2014;Manickam et al, 2016;Sundareswaran et al, 2015;Lian et al, 2014), and others such as Gravitational Search Algorithm (GSA) (Sundareswaran et al, 2016) and Simulated Annealing (SA) (Lyden and Haque, 2015). Most of such techniques perform the MPP search using two stages.…”

Section: Introductionmentioning

confidence: 99%

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Efficiency of Hybrid MPPT Techniques Based on ANN and PSO for Photovoltaic Systems under Partially Shading Conditions

Mitsuya¹,

Meneses²

2019

American Journal of Engineering and Applied Sciences

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Hybrid Maximum Power Point Tracking (MPPT) algorithms have been investigated as an alternative to improve the performance of conventional MPPT, such as Perturb and Observe (P&O), Incremental Conductance (InC) and Hill Climbing (HC) in Photovoltaic (PV) systems under Partially Shading Condition (PSC). In the present article, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) hybridized with P&O algorithm for MPPT are compared in terms of power efficiency. This paper not only compare hybrid MPPT methods against conventional MPPT, but also provide a comparison between two different hybrid techniques. In order to evaluate the performance of such hybrid methods, a PV system was computationally modelled and different PSC scenarios were implemented in MATLAB ® /Simulink, as well as the hybrid methods ANN+P&O and PSO+P&O. The hybrid methods ANN+P&O and PSO+P&O successfully improve the efficiency of P&O algorithm, respectively achieving 98.93% and 92.96% on average in the PSC scenarios tested, whereas P&O achieved 88.27% on average in such scenarios.

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Hybrid maximum power point tracking technique based on PSO and incremental conductance

Cited by 19 publications

References 10 publications

Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy

Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy

A Literature review on industrially accepted MPPT techniques for solar PV system

Efficiency of Hybrid MPPT Techniques Based on ANN and PSO for Photovoltaic Systems under Partially Shading Conditions

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