{"title":"使用兰伯特 W 方法和经 Harris Hawks 优化训练的分数阶模糊比例积分控制器对基于光伏逆变器的资源进行基于逆变器的新型光伏模拟器控制","authors":"Sadegh Esfandiari;Masoud Davari;Weinan Gao;Yongheng Yang;Kamal Al-Haddad","doi":"10.1109/JESTIE.2024.3396140","DOIUrl":null,"url":null,"abstract":"Photovoltaic (PV) emulators are designed to reproduce the exact current-voltage characteristic of a PV module or array in different ambient conditions. PV emulators are essential for power converter testing in PV systems, particularly for grid-tied PV systems, which are among the most paramount inverter-based resources. Certain factors, such as real-time output and simple implementation with high accuracy, should be considered when designing a PV emulator. Conventional PV emulators utilize traditional PV mathematical models and controllers, like the Newton-Raphson (NR) method and PI controllers, respectively. This matter makes a PV emulator unable to reproduce the curve in different conditions because the PI controller is unable to tolerate changing operating points while drastically preserving robust performance with those alterations. Also, NR requires considerable iterations, leading to an intense computational burden. Accordingly, this article proposes a more effective and simple control methodology to optimize the performance of converter-based PV emulators. In this regard, the PV model is based on the single-diode model with five unknown parameters while considering a simple buck converter. This article utilizes the Lambert \n<italic>W</i>\n method to solve the exponential equation of the PV model, thus changing an “\n<italic>implicit</i>\n” function into an “\n<italic>explicit</i>\n” one. It also reduces the number of iterations; therefore, the computational burden is diminished while maintaining the performance and accuracy of converter-based PV emulators. Also, this article introduces a novel adaptive intelligent fractional-order controller to control converter-based PV emulators. In this strategy, the proposed fuzzy inference system obtains the three coefficients of the controller using Harris hawks optimization and gradient descent algorithm. With an adaptation of the three controller parameters, the performance of the converter-based PV emulator is improved by reducing the tracking error while inducing closed-loop system stability. Comparative simulations and experimental results reveal the effectiveness of the proposed control methodology.","PeriodicalId":100620,"journal":{"name":"IEEE Journal of Emerging and Selected Topics in Industrial Electronics","volume":"5 4","pages":"1493-1507"},"PeriodicalIF":0.0000,"publicationDate":"2024-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Converter-Based PV Emulator Control Using Lambert W Method and Fractional-Order Fuzzy Proportional-Integral Controller Trained by Harris Hawks Optimization for PV Inverter-Based Resources\",\"authors\":\"Sadegh Esfandiari;Masoud Davari;Weinan Gao;Yongheng Yang;Kamal Al-Haddad\",\"doi\":\"10.1109/JESTIE.2024.3396140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Photovoltaic (PV) emulators are designed to reproduce the exact current-voltage characteristic of a PV module or array in different ambient conditions. PV emulators are essential for power converter testing in PV systems, particularly for grid-tied PV systems, which are among the most paramount inverter-based resources. Certain factors, such as real-time output and simple implementation with high accuracy, should be considered when designing a PV emulator. Conventional PV emulators utilize traditional PV mathematical models and controllers, like the Newton-Raphson (NR) method and PI controllers, respectively. This matter makes a PV emulator unable to reproduce the curve in different conditions because the PI controller is unable to tolerate changing operating points while drastically preserving robust performance with those alterations. Also, NR requires considerable iterations, leading to an intense computational burden. Accordingly, this article proposes a more effective and simple control methodology to optimize the performance of converter-based PV emulators. In this regard, the PV model is based on the single-diode model with five unknown parameters while considering a simple buck converter. This article utilizes the Lambert \\n<italic>W</i>\\n method to solve the exponential equation of the PV model, thus changing an “\\n<italic>implicit</i>\\n” function into an “\\n<italic>explicit</i>\\n” one. It also reduces the number of iterations; therefore, the computational burden is diminished while maintaining the performance and accuracy of converter-based PV emulators. Also, this article introduces a novel adaptive intelligent fractional-order controller to control converter-based PV emulators. In this strategy, the proposed fuzzy inference system obtains the three coefficients of the controller using Harris hawks optimization and gradient descent algorithm. With an adaptation of the three controller parameters, the performance of the converter-based PV emulator is improved by reducing the tracking error while inducing closed-loop system stability. 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引用次数: 0
摘要
光伏(PV)仿真器旨在再现不同环境条件下光伏模块或阵列的精确电流-电压特性。光伏仿真器对于光伏系统中的功率转换器测试至关重要,特别是对于并网光伏系统,它是最重要的基于逆变器的资源之一。在设计光伏仿真器时,应考虑某些因素,如实时输出和高精度的简单实现。传统的光伏仿真器使用传统的光伏数学模型和控制器,如牛顿-拉斐森(NR)方法和 PI 控制器。这使得光伏仿真器无法再现不同条件下的曲线,因为 PI 控制器无法承受工作点的变化,同时在这些变化中大幅保持稳健的性能。此外,NR 需要大量的迭代,导致计算负担过重。因此,本文提出了一种更有效、更简单的控制方法,以优化基于转换器的光伏仿真器的性能。在这方面,光伏模型基于具有五个未知参数的单二极管模型,同时考虑了简单的降压转换器。本文利用 Lambert W 方法求解光伏模型的指数方程,从而将 "隐式 "函数变为 "显式 "函数。它还减少了迭代次数;因此,在保持基于转换器的光伏仿真器的性能和精度的同时,也减轻了计算负担。此外,本文还介绍了一种新型自适应智能分数阶控制器,用于控制基于转换器的光伏仿真器。在这一策略中,所提出的模糊推理系统利用 Harris Hawks 优化和梯度下降算法获得控制器的三个系数。对三个控制器参数进行调整后,基于转换器的光伏仿真器的性能得到了改善,在诱导闭环系统稳定性的同时减少了跟踪误差。模拟和实验结果的对比显示了所提控制方法的有效性。
A Novel Converter-Based PV Emulator Control Using Lambert W Method and Fractional-Order Fuzzy Proportional-Integral Controller Trained by Harris Hawks Optimization for PV Inverter-Based Resources
Photovoltaic (PV) emulators are designed to reproduce the exact current-voltage characteristic of a PV module or array in different ambient conditions. PV emulators are essential for power converter testing in PV systems, particularly for grid-tied PV systems, which are among the most paramount inverter-based resources. Certain factors, such as real-time output and simple implementation with high accuracy, should be considered when designing a PV emulator. Conventional PV emulators utilize traditional PV mathematical models and controllers, like the Newton-Raphson (NR) method and PI controllers, respectively. This matter makes a PV emulator unable to reproduce the curve in different conditions because the PI controller is unable to tolerate changing operating points while drastically preserving robust performance with those alterations. Also, NR requires considerable iterations, leading to an intense computational burden. Accordingly, this article proposes a more effective and simple control methodology to optimize the performance of converter-based PV emulators. In this regard, the PV model is based on the single-diode model with five unknown parameters while considering a simple buck converter. This article utilizes the Lambert
W
method to solve the exponential equation of the PV model, thus changing an “
implicit
” function into an “
explicit
” one. It also reduces the number of iterations; therefore, the computational burden is diminished while maintaining the performance and accuracy of converter-based PV emulators. Also, this article introduces a novel adaptive intelligent fractional-order controller to control converter-based PV emulators. In this strategy, the proposed fuzzy inference system obtains the three coefficients of the controller using Harris hawks optimization and gradient descent algorithm. With an adaptation of the three controller parameters, the performance of the converter-based PV emulator is improved by reducing the tracking error while inducing closed-loop system stability. Comparative simulations and experimental results reveal the effectiveness of the proposed control methodology.