| 000 | 03667nlm1a2200517 4500 | ||
|---|---|---|---|
| 001 | 668723 | ||
| 005 | 20231030042158.0 | ||
| 035 | _a(RuTPU)RU\TPU\network\39960 | ||
| 035 | _aRU\TPU\network\39932 | ||
| 090 | _a668723 | ||
| 100 | _a20230119a2022 k y0engy50 ba | ||
| 101 | 0 | _aeng | |
| 135 | _adrcn ---uucaa | ||
| 181 | 0 | _ai | |
| 182 | 0 | _ab | |
| 200 | 1 |
_aStatic models for implementing photovoltaic panels characteristics under various environmental conditions using improved gradient-based optimizer _fA. M. Mokhamed Elsaed (Mohamed Abd Elaziz), A. Rolla, A. Iman [et al.] |
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| 203 |
_aText _celectronic |
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| 300 | _aTitle screen | ||
| 320 | _a[References: 72 tit.] | ||
| 330 | _aAn accurate definition of the photovoltaic (PV) models is an essential task to emulate and understand the physical behavior of the PV cell/panels. The highly used PV models are the static equivalent circuits, including single and double diode models. However, the accurate definition of the static models is mainly based on their estimated parameters. Proposing a reliable Optimization-based approached is a challenging aim. So, this paper proposes a novel and efficient optimizer to identify PV single and double diode models' parameters for several PV modules using different sets of experimentally measured data. The developed method depends on improving the gradient-based optimization algorithm (GBO) using a new crossover operator to enhances agents' diversity. Furthermore, a modified local escaping operator is applied to improve exploitation of GBO. The performance of the improvement GBO (IGBO) is evaluated using different experimental datasets for numerous PV modules under several operating conditions of temperature and radiation. The efficiency of IGBO is validated through a massive comparison with a set of recent state-of-the-art techniques. Reported results, fitting curves, and convergence curves provide proof for the efficiency of IGBO in providing high qualifies results with remarkable convergence speed. | ||
| 333 | _aРежим доступа: по договору с организацией-держателем ресурса | ||
| 461 | _tSustainable Energy Technologies and Assessments | ||
| 463 |
_tVol. 52, pt. B _v[102150, 18 p.] _d2022 |
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| 610 | 1 | _aэлектронный ресурс | |
| 610 | 1 | _aтруды учёных ТПУ | |
| 610 | 1 | _asolar energy technology | |
| 610 | 1 | _agradient-based optimizer | |
| 610 | 1 | _aparameters estimation | |
| 610 | 1 | _asingle diode model | |
| 610 | 1 | _atwo diode model | |
| 610 | 1 | _aсолнечная энергия | |
| 610 | 1 | _aоптимизаторы | |
| 610 | 1 | _aградиент | |
| 701 | 1 |
_aMokhamed Elsaed (Mohamed Abd Elaziz) _bA. M. _cSpecialist in the field of informatics and computer technology _cProfessor of Tomsk Polytechnic University _f1987- _gAkhmed Mokhamed _2stltpush _3(RuTPU)RU\TPU\pers\46943 |
|
| 701 | 1 |
_aRolla _bA. _gAlmodfer |
|
| 701 | 1 |
_aIman _bA. _gAhmadianfar |
|
| 701 | 1 |
_aIbrahim _bA. I. _gAnwar Ibrahim |
|
| 701 | 1 |
_aMohammed _bM. _gMudhsh |
|
| 701 | 1 |
_aLaith _bA. _gAbualigah |
|
| 701 | 0 | _aSongfeng Lu | |
| 701 | 1 |
_aAhmed _bA. _gAbd El-Latif |
|
| 701 | 1 |
_aYousri _bD. _gDalia |
|
| 712 | 0 | 2 |
_aНациональный исследовательский Томский политехнический университет _bИнженерная школа информационных технологий и робототехники _bОтделение информационных технологий _h7951 _2stltpush _3(RuTPU)RU\TPU\col\23515 |
| 801 | 2 |
_aRU _b63413507 _c20230119 _gRCR |
|
| 856 | 4 | _uhttps://doi.org/10.1016/j.seta.2022.102150 | |
| 942 | _cCF | ||