[1]张 洁,罗俊杰.基于 TS-FOA 算法的光伏组件参数辨识[J].计算机技术与发展,2022,32(06):15-20.[doi:10. 3969 / j. issn. 1673-629X. 2022. 06. 003]
　ZHANG Jie,LUO Jun-jie.Parameter Identification of Photovoltaic Modules Based on TS-FOA[J].,2022,32(06):15-20.[doi:10. 3969 / j. issn. 1673-629X. 2022. 06. 003]
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基于 TS-FOA 算法的光伏组件参数辨识()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年06期
页码:
15-20
栏目:
人工智能
出版日期:
2022-06-10

文章信息/Info

Title:
Parameter Identification of Photovoltaic Modules Based on TS-FOA
文章编号:
1673-629X(2022)06-0015-06
作者:
张 洁; 罗俊杰
南京邮电大学 计算机学院,江苏 南京 210023
Author(s):
ZHANG Jie;  LUO Jun-jie
School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
关键词:
光伏组件; 参数辨识; 功率预测; 禁忌搜索算法; 果蝇算法
Keywords:
photovoltaic component; parameter identification; power prediction; tabu search algorithm; fruit fly optimization algorithm
分类号:
TP391. 9
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 06. 003
摘要:
基于参数辨识技术对光伏组件进行辨识可以快速准确地得到光伏组件的模型情况,这对光伏阵列的功率计算、最大功率点跟踪和故障排除等都具有十分积极的作用,然而光伏组件数据的监控测点多、数据大且复杂,传统的参数辨识方法在搜索过程中灵活度较差,难以满足精确度需求。 基于光伏组件数学模型,针对传统智能算法精确度低和易陷入局部最优解等问题,提出禁忌搜索算法和果蝇算法结合( TS-FOA)的参数辨识方法。 TS-FOA 算法进行了两种算法的融合:引入 FOA 算法,保证前期全局搜索能力,实现初期搜索的快速迭代;引入 TS 概念对传统 FOA 算法进行优化,进一步减少迭代时间,并可以避免迭代后期陷入局部最优解的问题,提升寻优效率。 在算例分析中,使用光伏电站测试数据,验证该算法在实际工程中的适用性,同时与其他基础算法进行多方面对比,结果表明 TS-FOA 相较于传统算法能提供更加精准、快速的参数辨识效果。
Abstract:
The identification of photovoltaic modules based on parameter identification technology can quickly and accurately get the model of photovoltaic module,which 　plays a positive role in photovoltaic array power calculation,maximum power point tracking and troubleshooting. However,the monitoring and measuring points of photovoltaic component data are many,large and complicated,the traditional parameter identification method has poor flexibility in the search process and is difficult　 to meet the requirements of accuracy.Based on the mathematical model of photovoltaic component,a parameter identification method combining Tabu Search Algorithm and Fruit Fly Algorithm ( TS-FOA) is proposed to solve the problems of low accuracy of traditional intelligent algorithm and easy to fall into local optimal solution. TS-FOA algorithm is the fusion of the two algorithms:FOA algorithm is introduced to ensure the global search ability in the early stage and realize the rapid iteration of the initial search. The concept of TS is introduced to optimize the traditional FOA algorithm,which further reduces the iteration time and avoids the problem of falling into local optimal solution at the later stage ofiteration,thus improving the optimization efficiency. In the example analysis,the test data of photovoltaic power station is used to verify the applicability of this algorithm in practical engineering. At the same time,it is compared with other basic algorithms in many aspects.The results show that TS-FOA can provide more accurate and fast parameter identification effect compared with the traditional algorithm.
更新日期/Last Update: 2022-06-10