A Novel Variable Step Size Incremental Conductance Method with an Adaptive Scaling Factor

Chuang, Man-Tsai; Liu, Yi‐Hua; Ye, Song-Pei

doi:10.3390/app10155214

Cited by 10 publications

(5 citation statements)

References 27 publications

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“…Many algorithms are evolved to extract the Maximum Power Point (MPP) from the solar PV module under varying conditions of solar irradiance and temperature 4 . The traditional techniques of MPPT algorithms, which are based on the hill-climbing method such as Perturbation and Observation (P &O), Incremental Conductance (INC), Fractional Open Circuit Voltage(OCV), and Fractional Short Circuit Current techniques, have been discussed in [5][6][7][8][9][10][11] . These algorithms present a slow response under varying irradiation levels.…”

Section: Related Workmentioning

confidence: 99%

Recursive bit assignment with neural reference adaptive step (RNA) MPPT algorithm for photovoltaic system

Hegazy

Shokair

Saad

2023

Sci Rep

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Recent research has focused on photovoltaic (PV) systems due to their important properties. The efficiency of the PV system can be enhanced by many Maximum Power Point Tracking (MPPT) algorithms proposals. MPPT algorithms are used to achieve maximum PV output power by optimizing the duty cycle of the DC–DC buck/boost converter. This paper introduces an RNA algorithm as an efficient MPPT algorithm for the photovoltaic system. This proposed RNA algorithm consists of two main segments. The first segment is an artificial neural network for generating reference power. The second segment is a proposed Recursive Bit Assignment (RBA) network to allow variable step size of the boost converter duty cycle. The instant PV power adopts the RBA network to produce the variable duty cycle increment value. Additionally, the neural network is implemented in such a way to obtain the best performance. Many simulation results using MATLAB to test the system performance are presented. The performance characteristics of the photovoltaic system with variable irradiance and variable temperature are simulated. From results, the proposed RNA algorithm achieves fast tracking time, high energy efficiency, true maximum power point and acceptable ripple. Additionally, comparisons between the RNA algorithm and other related algorithms such as Perturb and Observe, the Neural Network and the Adaptive Neural Inference System Algorithms are executed. The proposed RNA algorithm achieves the best performance in all case studies such as; irradiance profile variation, severe temperature and irradiance diversions, and partial shading conditions. Besides, the experimental circuit of the PV system is also presented.

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Section: Related Workmentioning

confidence: 99%

Recursive bit assignment with neural reference adaptive step (RNA) MPPT algorithm for photovoltaic system

Hegazy

Shokair

Saad

2023

Sci Rep

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“…Steady state oscillations can be reduced by reducing the step size, but system tracking speed gets slower down if step size gets reduced Messalti et al (2017). Many research contributions available in literature to overcome these issues with the introduction of variable step size MPPT algorithms Hosseini et al (2013), Alkhawaldeh and Bhuiya (2021), Liu et al (2008), Tian et al (2014), Husain et al (2017), Chuang et al (2020), Suntio and Kuperman (2019), Kumar et al (2019), in which step size is regularly changed according to the environmental conditions and provides a simple and quick response with low oscillations. The step size of this method is mathematically written as shown in Equation 9 and Equation 10.…”

Section: Variable Step Size Mppt Algorithmsmentioning

confidence: 99%

A Review on MPPT Algorithms for Solar Pv Systems

Senthilkumar

Mohan

Deepa

et al. 2023

Int. J. Res. Granthaalayah

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In past few decades, solar energy plays a vital role in energy production among the different renewable energy resources. In shaded/unshaded photovoltaic (PV) systems, tracking of maximum power under different environmental conditions is provided by maximum power point tracking (MPPT). In recent years many works available on different types of MPPT techniques to track maximum power from PV systems with own pros and cons. This article comprehensively reviews the different traditional methods like perturb and observation (P&O), open circuit voltage (OCV), short circuit current (SCC), hill climbing (HC), incremental conductance (IC). Also recall the advanced MPPT techniques like particle swarm optimization (PSO), grey wolf optimization (GWO), cuckoo search (CS), artificial neural networks (ANN), fuzzy logic controller (FLC) available in literature. This review is conducted based on implementation, accuracy, tracking speed, cost, merits, and demerits of each technique. Traditional MPPT methods can’t able to track global maximum power point under partial shaded conditions and exhibits less efficiency when compared with advanced soft computing methods. Hybrid methods provide good efficiency and performance than traditional and advanced methods. Authors powerfully confirm that this article offers convenient information’s to enthusiastic engineers and new researchers those who are all working in solar PV systems.

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“…However, these traditional methods encountered a compromise between the level of precision and the rate of convergence. Here, the boost converter was operated with appropriate gate pulses that were applied using the FSSINC MPPT control methodology [18]. Its objective was to provide a quick and effective way to enhance tracking dynamics.…”

Section: Maximum Power Extractionmentioning

confidence: 99%

Alleviation of Power Quality Issues in MVF-DEANF-PLL Based Solar PV Systems under Polluted Grid Conditions

Mohan,

Siddhan,

Chinnadurai

2023

Sustainability

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Solar energy is a sustainable and environmentally safe power source due to its widespread availability and cleanliness. Nowadays, the grid-integrated solar photovoltaic system (SPVS) has to work with a polluted grid, an imbalanced load, and changing solar irradiation. When the grid is polluted, it is also crucial to enhance power quality (PQ) at a common coupling point (CCP) while supplying significantly distorted and unreliable loads. For effective synchronization and the production of unit templates, it is necessary to retrieve positive sequence components (PSCs) from distorted/imbalanced grid voltages. In this study, a control algorithm for a grid-integrated SPVS is developed using a multi-variable filter dual-enhanced adaptive notch filter phase-locked loop (MVF-DEANF-PLL) which offers seamless grid synchronization and PQ issue alleviation. In a polluted grid environment, the proposed control approach aids in the reduction in current/voltage harmonics, DC offset, unity power factor (UPF) operation, and rapid estimation of sequence components. Even in unbalanced grid conditions, the proposed control approach efficiently extracts PSCs of both unbalanced load current and polluted CCP grid voltages. These PSCs are utilized to generate unit templates and reference source currents. By using a flexible step-size incremental conductance (FSSINC) maximum power point tracking (MPPT) technique, the highest available power of SPVS is gathered. MATLAB/Simulink is utilized for modelling a 7.22 kW SPV system, and results from simulations which depict that the proposed algorithm efficiently resolves PQ concerns in distribution networks with a polluted grid. Test observations of a 1 kW laboratory-developed SPVS prototype were recorded in compliance with the IEEE-519 standard. The suggested control technique complies with the aforementioned standards by providing a sinusoidal balanced source current that has a THD of 2.5%. Comparisons between the proposed control’s performance and that of a conventional SRF-PLL-based control technique were also performed.

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A Novel Variable Step Size Incremental Conductance Method with an Adaptive Scaling Factor

Cited by 10 publications

References 27 publications

Recursive bit assignment with neural reference adaptive step (RNA) MPPT algorithm for photovoltaic system

Recursive bit assignment with neural reference adaptive step (RNA) MPPT algorithm for photovoltaic system

A Review on MPPT Algorithms for Solar Pv Systems

Alleviation of Power Quality Issues in MVF-DEANF-PLL Based Solar PV Systems under Polluted Grid Conditions

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