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Parameter extraction of solar photovoltaic models with an either-or teaching learning based algorithm

机译：基于或教学学习算法的太阳能光伏模型参数提取

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摘要

This paper presents an advanced variant of teaching learning based algorithm (TLBO) called either-or teaching learning based algorithm (EOTLBO) to extract accurate and reliable parameters of solar photovoltaic (PV) models. EOTLBO synergizes three enhanced strategies to accelerate the convergence rate and boost the search efficiency of TLBO. (i) A median learner based teacher phase excluding the mean position used in the original TLBO is designed to avoid infeasible and inefficient learners and to form a rational and advisable moving mechanism around the teacher. (ii) A higher-achieving learner based learner phase using three sorted learners is devised to directionally guide the target learner to jump out of local optima and to move towards a more promising region. (iii) A chaotic map based either-or teaching-learning strategy is developed to give each dimension of each learner a chance to go through either the median learner based teacher phase or the higher-achieving learner based learner phase. EOTLBO is applied to three PV cells/modules including seven cases. Compared with the original TLBO, four non-TLBO variants, and five TLBO variants, experimental results verify the superior performance of EOTLBO in terms of both the quality of final solutions and the convergence speed on all cases. In addition, the current-voltage characteristics yielded by EOTLBO agree well with the measured data independently of different PV models at different operating conditions.
机译：本文介绍了基于教学的算法（TLBO）的高级变体，称为基于或教学学习算法（Eotlbo），以提取太阳能光伏（PV）模型的准确可靠参数。 Eotlbo协调三种增强的策略，以加速收敛速度并提高TLBO的搜索效率。 （i）除了原始TLBO中使用的平均位置的基于中位的学习者的教师阶段旨在避免不可行和低效的学习者，并在老师周围形成一个理性和可取的移动机制。 （ii）设计使用三个分类学习者的基于学习者的学习者阶段，方向定向指导目标学习者以跳出当地的最佳活动并迈向更有前途的地区。 （iii）基于或教学 - 学习策略的混沌图是制定的，为每个学习者提供每个学习者的每个维度，有机会经历基于中位的学习者的教师阶段或更高达到的学习者的学习者阶段。 Eotlbo应用于三种PV电池/模块，包括七种情况。与原始TLBO，四种非TLBO变体和五个TLBO变体相比，实验结果验证了ETLBO的优越性，在所有情况下最终解决方案的质量和收敛速度。此外，Eotlbo所产生的电流电压特性与在不同操作条件下独立于不同的PV型号的测量数据同意。

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  • 来源
    《Energy Conversion & Management》 |2020年第11期|113395.1-113395.12|共12页
  • 作者

    Xiong Guojiang; Zhang Jing; Shi Dongyuan; Zhu Lin; Yuan Xufeng;

  • 作者单位

    Guizhou Univ Coll Elect Engn Guizhou Key Lab Intelligent Technol Power Syst Guiyang 550025 Peoples R China;

    Guizhou Univ Coll Elect Engn Guizhou Key Lab Intelligent Technol Power Syst Guiyang 550025 Peoples R China;

    Huazhong Univ Sci & Technol State Key Lab Adv Electromagnet Engn & Technol Wuhan 430074 Peoples R China;

    Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA;

    Guizhou Univ Coll Elect Engn Guizhou Key Lab Intelligent Technol Power Syst Guiyang 550025 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Parameter extraction; Photovoltaic; Teaching learning based algorithm;

    机译：参数提取;光伏;基于教学的算法;

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