Scholarlink

<p>Adaptive and robust control methods are utilized in power regulation and energy management of hybrid renewable energy systems such as photovoltaic (PV) systems into power grids. We propose a new control method based on a non-singleton Type-3 fuzzy logic system hybridized with a non-singular sliding surface controller for battery-PV power regulation. The proposed method deals with the modeling uncertainties and nonlinearities in hybrid battery storage and PV generation components. The design of a non-singleton Type-3 fuzzy logic system helps to robustify subject to measurement errors and external disturbances and delivers user-defined power delivery. Furthermore, our suggested method contributes to maintaining the needed voltage magnitude and improve the efficiency of the PV-battery system by optimizing power flow between the PV array and the battery storage. Moreover, in this study, a projection operator in the control scheme is utilized to deal with parameter uncertainties. The effectiveness of the proposed control method was evaluated in comparison with studies under a range of operating conditions, including changes in solar irradiance and load demand. The study outcomes demonstrated that the suggested method considerably increased power regulation and energy efficiency. In particular, simulation results indicated that our suggested method could deliver with a rapid convergence a maximum power of 31.25 W under <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(750 \mathrm {~W} / \textrm{m}^2\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>750</mn> <mrow> <mspace width="3.33333pt" /> <mi mathvariant="normal">W</mi> </mrow> <mo stretchy="false">/</mo> <msup> <mtext>m</mtext> <mn>2</mn> </msup> </mrow> </math></EquationSource> </InlineEquation> irradiance. Additionally, it was seen that the suggested closed-loop system significantly performed better than traditional methods in terms of reducing power regulation RMSE to 0.85 <i>W</i>, and improving PV current and load voltage tracking with RMSEs of 0.63 <i>A</i> and 1.35 <i>V</i>, respectively.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Adaptive Finite-Time Control with Non-Singleton Type-3 Fuzzy Logic System for Maximum Power Tracking in Hybrid PV-Battery Systems

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月30日

查看全文
  • Hadi Taghavifar,
  • Hamid Taghavifar,
  • Ardashir Mohammadzadeh

摘要

Adaptive and robust control methods are utilized in power regulation and energy management of hybrid renewable energy systems such as photovoltaic (PV) systems into power grids. We propose a new control method based on a non-singleton Type-3 fuzzy logic system hybridized with a non-singular sliding surface controller for battery-PV power regulation. The proposed method deals with the modeling uncertainties and nonlinearities in hybrid battery storage and PV generation components. The design of a non-singleton Type-3 fuzzy logic system helps to robustify subject to measurement errors and external disturbances and delivers user-defined power delivery. Furthermore, our suggested method contributes to maintaining the needed voltage magnitude and improve the efficiency of the PV-battery system by optimizing power flow between the PV array and the battery storage. Moreover, in this study, a projection operator in the control scheme is utilized to deal with parameter uncertainties. The effectiveness of the proposed control method was evaluated in comparison with studies under a range of operating conditions, including changes in solar irradiance and load demand. The study outcomes demonstrated that the suggested method considerably increased power regulation and energy efficiency. In particular, simulation results indicated that our suggested method could deliver with a rapid convergence a maximum power of 31.25 W under \(750 \mathrm {~W} / \textrm{m}^2\) 750 W / m 2 irradiance. Additionally, it was seen that the suggested closed-loop system significantly performed better than traditional methods in terms of reducing power regulation RMSE to 0.85 W, and improving PV current and load voltage tracking with RMSEs of 0.63 A and 1.35 V, respectively.