Self-Adaptive Incremental Conductance Algorithm for Swift and Ripple-Free Maximum Power Harvesting From PV Array

Kumar, Nishant; Hussain, Ikhlaq; Singh, Bhim; Panigrahi, Bijaya Ketan

doi:10.1109/tii.2017.2765083

Cited by 120 publications

(59 citation statements)

References 29 publications

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“…Consequently, the researchers refocus on conventional techniques such as Incremental conductance (IC) based MPPTM is more effective [2]. IC along with variable step size gives excellent steady-state time response.…”

Section: Revised Manuscript Received On November 22 2019 * Correspomentioning

confidence: 99%

“…The main problem associated with fixed duty cycle step size is that slow response, large computation and noisy with low step size and large oscillation around its MPP, less efficient with high step size. So instead of searching the entire region, initially decide tracking region [3], [2], then keep large step size of duty cycle at initial state and less step size in tracking region.…”

Section: (B) Pando With Variable Step Sizementioning

confidence: 99%

“…However, the solar photovoltaic system suffers from poor efficiency due to photovoltaic conversion efficiency and the extraction of maximum power form system in the varying irradiance of the sun naturally or environmentally. Many researchers focus on extraction of maximum power by developing the MPPT algorithms [1]- [2].…”

Section: Introductionmentioning

confidence: 99%

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Estimating Efficiency of MPPT Techniques by Chattering Examination

2019

IJITEE

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Increasing the efficiency of MPPT techniques is the essential aspects of the Solar Photovoltaic System. This efficiency is affected by the chattering available with the MPPT techniques. An MPP technique which generates less chattering in the system is more efficient than the others. This paper presents the chattering analysis of the popular Maximum Power Point Tracking (MPPT) techniques Perturb & Observe (P&O) and Incremental conductance method for the fixed and variable step size. The algorithms are simulated under similar load and environment conditions. In the result it is found that the incremental conductance method has very less chattering in comparison with the P&O for the fixed step size and variable step size. Further, for the different solar radiation chattering is observed and tabulated

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Section: Revised Manuscript Received On November 22 2019 * Correspomentioning

confidence: 99%

Section: (B) Pando With Variable Step Sizementioning

confidence: 99%

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Estimating Efficiency of MPPT Techniques by Chattering Examination

2019

IJITEE

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show abstract

“…However, P&O and INC suffer from the problem of oscillation. Note that, contradictory to its general conception, INC still suffers from the oscillation problem, as pointed out in [35,36]. Convergence criteria can be applied to P&O and INC to mitigate the steady-state fluctuations.…”

Section: Convergence Criteriamentioning

confidence: 99%

A Review and New Problems Discovery of Four Simple Decentralized Maximum Power Point Tracking Algorithms—Perturb and Observe, Incremental Conductance, Golden Section Search, and Newton’s Quadratic Interpolation

2018

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Maximum Power Point Tracking (MPPT) enables photovoltaic (PV) systems to extract as much solar energy as possible. Depending on which type of controller is used, PV systems can be classified as centralized MPPT (CMPPT) or decentralized MPPT (DMPPT). In substring-level systems, it is known that the energy yield of DMPPT can outweigh the power electronics cost. At the substring level, it is usually assumed that the PV curve exhibits a single peak, even under partial shading. Thus, the control algorithms for DMPPT are usually less complicated than those employed in CMPPT systems. This paper provides a comprehensive review of four simple DMPPT algorithms, which are perturb and observe (P&O), incremental conductance (INC), golden section search (GSS), and Newton's quadratic interpolation (NQI). The comparison of these algorithms are done from the perspective of numerical analysis. Guidelines on how to set initial conditions and convergence criteria are thoroughly explained. This is of great interest to PV engineers when selecting algorithms for use in MPPT implementations. In addition, various problems that have never previously been identified before are highlighted and discussed. For instance, the problems of NQI trap is identified and methods on how to mitigate it are also discussed. All the algorithms are tested under various conditions including static, dynamic, and rapid changes of irradiance. Both simulation and experimental results indicate that P&O and INC are the best algorithms for DMPPT.

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“…A detailed literature look has been provided Viz. perturb and observe (P&O) [6]; Hill climbing (HC) [7] and incremental conductance (INC) [8]. Nevertheless, mentioned algorithms lose control under non-uniform weather conditions.…”

Section: Introductionmentioning

confidence: 99%

An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter

et al. 2019

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This research work explains the practical realization of hybrid solar wind-based standalone power system with maximum power point tracker (MPPT) to produce electrical power in rural places (residential applications). The wind inspired Ant Colony Optimization (ACO)-based MPPT algorithm is employed for the purpose of fast and accurate tracking power from wind energy system. Fuzzy Logic Control (FLC) inverter controlling strategy is adopted in this presented work compared to classical proportional-integral (PI) control. Moreover, single Cuk converter is operated as impedance power adapter to execute MPPT functioning. Here, ACO-based MPPT has been implemented with no voltage and current extra circuit requirement compared to existing evolutionary algorithms single cuk converter is employed to improve conversion efficiency of converter by maximizing power stages. DC-link voltage can be regulated by placing Cuk converter Permanent Magnet Synchronous Generator (PMSG) linked rectifier and inverter. The proposed MPPT method is responsible for rapid battery charging and gives power dispersion of battery for hybrid PV-Wind system. ACO-based MPPT provides seven times faster convergence compared to the particle swarm optimization (PSO) algorithm for achievement of maximum power point (MPP) and tracking efficiency. Satisfactory practical results have been realized using the dSPACE (DS1104) platform that justify the superiority of proposed algorithms designed under various operating situations.

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Self-Adaptive Incremental Conductance Algorithm for Swift and Ripple-Free Maximum Power Harvesting From PV Array

Cited by 120 publications

References 29 publications

Estimating Efficiency of MPPT Techniques by Chattering Examination

Estimating Efficiency of MPPT Techniques by Chattering Examination

A Review and New Problems Discovery of Four Simple Decentralized Maximum Power Point Tracking Algorithms—Perturb and Observe, Incremental Conductance, Golden Section Search, and Newton’s Quadratic Interpolation

An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter

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