کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5012730 | 1462817 | 2017 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization
ترجمه فارسی عنوان
شناسایی پارامترهای مدل های فتوولتائیک با استفاده از خودپنداره بهینه سازی آموزش مبتنی بر یادگیری
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کلمات کلیدی
مدل فتوولتائیک، شناسایی پارامتر، بهینه سازی آموزش مبتنی بر یادگیری، استراتژی یادگیری،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی (عمومی)
چکیده انگلیسی
Parameters identification of photovoltaic (PV) model based on measured current-voltage characteristic curves plays an important role in the simulation and evaluation of PV systems. To accurately and reliably identify the PV model parameters, a self-adaptive teaching-learning-based optimization (SATLBO) is proposed in this paper. In SATLBO, the learners can self-adaptively select different learning phases based on their knowledge level. The better learners are more likely to choose the learner phase for improving the population diversity, while the worse learners tend to choose the teacher phase to enhance the convergence rate. Thus, learners at different levels focus on different searching abilities to efficiently enhance the performance of algorithm. In addition, to improve the searching ability of different learning phases, an elite learning strategy and a diversity learning method are introduced into the teacher phase and learner phase, respectively. The performance of SATLBO is firstly evaluated on 34 benchmark functions, and experimental results show that SATLBO achieves the first in ranking on the overall performance among nine algorithms. Then, SATLBO is employed to identify parameters of different PV models, i.e., single diode, double diode, and PV module. Experimental results indicate that SATLBO exhibits high accuracy and reliability compared with other parameter extraction methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy Conversion and Management - Volume 145, 1 August 2017, Pages 233-246
Journal: Energy Conversion and Management - Volume 145, 1 August 2017, Pages 233-246
نویسندگان
Kunjie Yu, Xu Chen, Xin Wang, Zhenlei Wang,