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Boosted backtracking search optimization with information exchange for photovoltaic system evaluation

التفاصيل البيبلوغرافية
العنوان: Boosted backtracking search optimization with information exchange for photovoltaic system evaluation
المؤلفون: Xuemeng Weng, Yun Liu, Ali Asghar Heidari, Zhennao Cai, Haiping Lin, Huiling Chen, Guoxi Liang, Abdulmajeed Alsufyani, Sami Bourouis
المصدر: Energy Science & Engineering, Vol 11, Iss 1, Pp 267-298 (2023)
بيانات النشر: Wiley, 2023.
سنة النشر: 2023
المجموعة: LCC:Technology
LCC:Science
مصطلحات موضوعية: metaheuristics, parameter extraction, photovoltaic models, solar cell, swarm intelligence, Technology, Science
الوصف: Abstract The determination of photovoltaic (PV) parameters is of great importance for the reliability of solar system operation, continuity of the load power consumption, and control management of the energy source. Therefore, this study proposes an advanced backtracking search optimization algorithm (BSA) equipped with teaching and learning‐based optimization (TLBO), named TLBOBSA, to accurately simulate the PV model. During the evaluation of the proposed algorithm, the concept of teaching from TLBO is introduced into the BSA to guide optimal individuals, thus improving the convergence rate of the algorithm. The learning behavior among individuals in the student phase of TLBO facilitates interindividual learning and provides beneficial information for its evolution, which is introduced into the BSA to ensure the diversity of the population. The comprehensive test results of different PV module models in different environmental conditions show that the proposed algorithm is more advantageous for parameter extraction than other existing algorithms. This can be seen in the simulation experiments of two commercial PV models, where the simulated current is consistent with the measured current at each measured voltage. This demonstrates that the proposed TLBOBSA is an accurate and reliable tool for evaluating unknown parameters of PV models.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2050-0505
Relation: https://doaj.org/toc/2050-0505
DOI: 10.1002/ese3.1329
URL الوصول: https://doaj.org/article/e249434ee5d342249b0217861e8eb2b8
رقم الأكسشن: edsdoj.249434ee5d342249b0217861e8eb2b8
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20500505
DOI:10.1002/ese3.1329