Optimal Performance of Dynamic Particle Swarm Optimization Based Maximum Power Trackers for Stand-Alone PV System Under Partial Shading Conditions; IEEE Access; Vol. 8
| Parent link: | IEEE Access Vol. 8.— 2020.— [P. 20770-20785] |
|---|---|
| Yhteisötekijä: | |
| Muut tekijät: | , , , , |
| Yhteenveto: | Title screen One of the important tasks for increasing the efficiency of photovoltaic (PV) system is the development and improvement of the maximum power point tracking algorithms (MPPT). These MPPT algorithms lead to the ability to catch efficiently the global maximum power point of the partially shaded PV array. One of these trackers is the particle swarm optimization (PSO) algorithm which is one of the Soft computing techniques. The conventional PSO based trackers have many advantages such as the simplicity of hardware implementation and independence from the installed system. The actual problem of the practical application of PSO is the determination of its parameters to ensure high effectiveness of extracting the global MPP. Analysis of scientific papers devoted to the PSO algorithm has shown that there is currently no methodology for the optimal parameters' selection of PSO algorithm based maximum power trackers for the PV system. This paper aims to create a convenient and reasonable method for choosing the optimal parameters of the PSO algorithm, taking into account the topology and parameters of the DC-DC converter and the configuration of solar panels. A new method for selecting the parameters of a buck converter connected to a battery has been presented. The optimal value of the sampling time for the digital MPP controllers, providing their maximum performance; has been determined based on a new methodology. Matlab/Simulink software package is used as the main research tool. The prominent outcomes identify that the modified PSO and its designed parameters best meet the requirements of the MPPT controller for the PV system. |
| Kieli: | englanti |
| Julkaistu: |
2020
|
| Aiheet: | |
| Linkit: | http://earchive.tpu.ru/handle/11683/64955 https://doi.org/10.1109/ACCESS.2020.2966430 |
| Aineistotyyppi: | Elektroninen Kirjan osa |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663695 |
MARC
| LEADER | 00000naa0a2200000 4500 | ||
|---|---|---|---|
| 001 | 663695 | ||
| 005 | 20250516115359.0 | ||
| 035 | |a (RuTPU)RU\TPU\network\34865 | ||
| 090 | |a 663695 | ||
| 100 | |a 20210226d2020 k||y0rusy50 ba | ||
| 101 | 0 | |a eng | |
| 102 | |a US | ||
| 135 | |a drcn ---uucaa | ||
| 181 | 0 | |a i | |
| 182 | 0 | |a b | |
| 200 | 1 | |a Optimal Performance of Dynamic Particle Swarm Optimization Based Maximum Power Trackers for Stand-Alone PV System Under Partial Shading Conditions |f S. G. Obukhov, I. M. Ibrahim Ahmed, A. Z. D. Ahmed [et al.] | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 42 tit.] | ||
| 330 | |a One of the important tasks for increasing the efficiency of photovoltaic (PV) system is the development and improvement of the maximum power point tracking algorithms (MPPT). These MPPT algorithms lead to the ability to catch efficiently the global maximum power point of the partially shaded PV array. One of these trackers is the particle swarm optimization (PSO) algorithm which is one of the Soft computing techniques. The conventional PSO based trackers have many advantages such as the simplicity of hardware implementation and independence from the installed system. The actual problem of the practical application of PSO is the determination of its parameters to ensure high effectiveness of extracting the global MPP. Analysis of scientific papers devoted to the PSO algorithm has shown that there is currently no methodology for the optimal parameters' selection of PSO algorithm based maximum power trackers for the PV system. This paper aims to create a convenient and reasonable method for choosing the optimal parameters of the PSO algorithm, taking into account the topology and parameters of the DC-DC converter and the configuration of solar panels. A new method for selecting the parameters of a buck converter connected to a battery has been presented. The optimal value of the sampling time for the digital MPP controllers, providing their maximum performance; has been determined based on a new methodology. Matlab/Simulink software package is used as the main research tool. The prominent outcomes identify that the modified PSO and its designed parameters best meet the requirements of the MPPT controller for the PV system. | ||
| 461 | |t IEEE Access | ||
| 463 | |t Vol. 8 |v [P. 20770-20785] |d 2020 | ||
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a batteries | |
| 610 | 1 | |a mathematical model | |
| 610 | 1 | |a maximum power point trackers | |
| 610 | 1 | |a photovoltaic systems | |
| 610 | 1 | |a buck converters | |
| 610 | 1 | |a voltage control | |
| 610 | 1 | |a resistance | |
| 701 | 1 | |a Obukhov |b S. G. |c specialist in the field of electric power engineering |c Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences |f 1963- |g Sergey Gennadievich |3 (RuTPU)RU\TPU\pers\37391 |9 20309 | |
| 701 | 1 | |a Ibrahim Ahmed |b I. M. |c specialist in the field of electric power engineering |c Research Engineer, Tomsk Polytechnic University |f 1987- |g Ibrahim Mohamed |3 (RuTPU)RU\TPU\pers\44741 |9 21838 | |
| 701 | 1 | |a Ahmed |b A. Z. D. |g A. Zaki Diab | |
| 701 | 1 | |a Al-Sumait |b A. S. |g Ameena Saad | |
| 701 | 1 | |a Aboelsaud Raef |b S. S. A. |c specialist in the field of electric power engineering |c Research Engineer, Tomsk Polytechnic University |f 1987- |g Siam Sayed Ahmed |3 (RuTPU)RU\TPU\pers\45079 | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа энергетики |b Отделение электроэнергетики и электротехники |3 (RuTPU)RU\TPU\col\23505 |
| 801 | 2 | |a RU |b 63413507 |c 20210329 |g RCR | |
| 850 | |a 63413507 | ||
| 856 | 4 | 0 | |u http://earchive.tpu.ru/handle/11683/64955 |
| 856 | 4 | 0 | |u https://doi.org/10.1109/ACCESS.2020.2966430 |
| 942 | |c CF | ||