An Improved Particle Swarm Optimization (PSO)–Based MPPT for PV With Reduced Steady-State Oscillation

Ishaque, Kashif; Salam, Zainal; Amjad, Muhammad; Mekhilef, Saad

doi:10.1109/tpel.2012.2185713

Cited by 926 publications

(413 citation statements)

References 31 publications

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“…11. Independent operating mode for each module enables configurations of different types of multi-level power configurations [37][38]. Under faulty condition, all control signals are deactivated and switches are off.…”

Section: Case Study : Modular Multi-level Photo-voltaic Systemmentioning

confidence: 99%

Efficient Energy Management System for Solar Energy

Kamala

Santhosh

2015

Automatika

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Original scientific paperSolar power is the major renewable energy source opted by developing countries as stand-alone / Grid enabled system. Industries and educational institutions are opting for solar energy to combat power crisis. This paper proposes knowledge based, self configurable, smart controller to efficiently use solar energy according to load, under frequent grid failure environment. It is enabled with fault identification and isolation. Extension to higher power capacity is easily achieved with plug and play mechanism. Proposed control architecture is implemented using Field Programmable Gate Array (FPGA), that supports modular level implementation with well defined interfaces for each sub-system. It can be used with low power as well as high power photo-voltaic system. Efficiency of the proposed architecture is demonstrated for the photo-voltaic system installed in educational institution.Key words: Field Programmable Gate Array, Photo-voltaic system, Pulse width modulation, Stand alone system. Sustav za efikasno upravljanje solarnom energijom. Solarna energija spada među glavne obnovljive izvore energije odabrana od strane zemalja u razvoju kao samostalnih izvora ili umrežene s ostalim izvorima. Industrija i edukacijske institucije predlažu solarnu energiju u borbi protiv energetske krize. U ovome radu predstavljen je samokonfigurabilan regulator za efikasno korištenje solarne energije s obzirom na opterećenje ičeste promjene u mreži. To je omogućeno uz identifikaciju kvara. Ekstenzija na visoke snage jednostavno se postiže sa uređajem koji se može odmah koristiti. Regulator je implementiran koristeći programirljive logičke sklopove (FPGA) koji podržavaju modularnu implementaciju svake razine sa sučeljem prema svakom podsustavu. Predloženi sustav može biti korišten za niske snage kao i za visoke snage kod fotonaponskih sustava. Efikasnost predložene arhitekture testirana je na fotonaponskom sustavu postavljenom na edukacijskoj instituciji.Ključne riječi: programirljivi logički sklopovi, fotonaponski sustav, pulsno-širinska modulacija, samostalni sustav

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Section: Case Study : Modular Multi-level Photo-voltaic Systemmentioning

confidence: 99%

Efficient Energy Management System for Solar Energy

Kamala

Santhosh

2015

Automatika

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“…A summary of the IPM is provided in the Appendix I and for further details, the reader is referred to [31] and [32]. Table 2 summarizes the execution time of the curve-inspecting and the proposed methods to solve the problem (6). It illustrates that the curve-inspecting technique is computationally quite expensive.…”

Section: The Proposed Mpp Estimation Algorithmmentioning

confidence: 99%

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

2014

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Citation: Dizqah, Arash, Maheri, Alireza and Busawon, Krishna (2014) Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) An Accurate Method for the PV Model Identification Based on a GeneticAlgorithm and the Interior-Point Method AbstractDue to the PV module simulation requirements as well as recent applications of model-based controllers, the accurate photovoltaic (PV) model identification method is becoming essential to reduce the PV power losses effectively. The classical PV model identification methods use the manufacturers provided maximum power point (MPP) at the standard test condition (STC). However, the nominal operating cell temperature (NOCT) is the more practical condition and it is shown that the extracted model is not well suited to it. The proposed method in this paper estimates an accurate equivalent electrical circuit for the PV modules using both the STC and NOCT information provided by the manufacturers. A multi-objective global optimization problem is formulated using only the main equation of the PV module at these two conditions that restrains the errors due to employing the experimental temperature coefficients. A novel combination of a genetic algorithm (GA) and the interior-point method (IPM) allows the proposed method to be fast and accurate regardless the PV technology. It is shown that the overall error, which is defined by the sum of the MPP errors of both the STC and the NOCT conditions, is improved by a factor between 5.1% to 31% depending on the PV technology.

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“…Though these methods have been shown to be effective in dealing with the nonlinear characteristics of the I-V curves, they incur considerable computational cost (Ishaque et al 2012). For example, FLC has to deal with fuzzification, rule base storage, inference mechanism, and defuzzification operations.…”

Section: Introductionmentioning

confidence: 99%

“…For NN, the large amount of data required for training and validating the NN models are a major constraint. Furthermore, as the operating conditions of the PV system vary continuously, MPPT has to respond to changes in insolation and temperature variations in real time (Ishaque et al 2012). …”

Section: Introductionmentioning

confidence: 99%

“…To address this issue, several researchers have proposed modifications to PSO to improve its performance in the maximum power point tracking (MPPT) under PSCs. The work in (Ishaque et al 2012) employed PSO to locate the nearest section where the global MPP may lie, and then used HillClimbing to find the exact point. A hybrid PSO and Artificial Neural Network (PSO-ANN) algorithm was proposed in this article to detect the global peak power point in the presence of several local peaks (Ngan and Tan 2016).…”

Section: Introductionmentioning

confidence: 99%

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A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays

Mao

Zhang

Duan

et al. 2017

International Journal of Green Energy

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Abstract:The power-voltage (P-V) characteristic curves of a PV array are nonlinear and have multiple peaks under partially shaded conditions (PSCs). This paper proposes a novel maximum power point tracking (MPPT) method for a PV system with reduced steady-state oscillation based on a two-stage particle swarm optimization (PSO) algorithm. The grouping method of the shuffled frog leaping algorithm (SFLA) is incorporated in the basic PSO algorithm (PSO-SFLA), ensuring fast and accurate searching of the global extremum. An adaptive speed factor is also introduced into the improved PSO to further enhance its convergence speed. Tests results show that the proposed method converges in less than half the time taken by the conventional PSO method, and the power is improved by 33% under the worst PSCs, which confirms the superiority of the proposed method over the standard PSO algorithm in terms of tracking speed and steady-state oscillations under different PSCs.

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An Improved Particle Swarm Optimization (PSO)–Based MPPT for PV With Reduced Steady-State Oscillation

Cited by 926 publications

References 31 publications

Efficient Energy Management System for Solar Energy

Efficient Energy Management System for Solar Energy

An accurate method for the PV model identification based on a genetic algorithm and the interior-point method

A Two-Stage Particle Swarm Optimization Algorithm for MPPT of Partially Shaded PV Arrays

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