Adaptive fuzzy based optimized
            <scp>proportional‐integral</scp>
            controller to mitigate the frequency oscillation of
            <scp>multi‐area photovoltaic</scp>
            thermal system

To ensure the full benefits from wind generation systems, an effective maximum power point tracking (MPPT) technique should be implemented. In this article, an adaptive fuzzy logic controller (AFLC) is presented as a control methodology for producing the peak power from a permanent magnet synchronous generator (PMSG)-based wind turbine (WT). Regardless of the importance and significance of modeling and simulation processes, experimental studies occupy the most important aspect and remain a big challenge. The first part of this article is devoted to the simulation and modeling of PMSG along with the control system by MATLAB/Simulink ® package to develop the control system. To justify the simulation results, experimental validation tests are presented under the same status of wind speed profile and run period. The experimental validation is conducted using the DSPACE DS1104 control board and is compared with simulation results. Moreover, for a realistic response, actual wind speed data is utilized in this research depending on measured data from Ras Ghareb wind farm in the Gulf of Suez, Egypt. The obtained results confirm the superiority of AFLC compared with fuzzy logic controller and conventional PI control schemes. In addition, good tracking with high accuracy is obtained regarding experimental and simulations results. Moreover, an evaluation indices are employed for WT performance based on gross system efficiency and integral of the absolute error (IAE). These indices are used to demonstrate the feasibility of the AFLC methodology compared with traditional approaches under the same wind turbine status.

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“…The AFLC's output is a product with KP and KI. As shown in Equation (14), "e" product with these gains to satisfy the PI controller [30][31][32]…”

Section: Adaptive Fuzzy-logic Mppt Controlmentioning

confidence: 99%

Implementation and Validation of an Adaptive Fuzzy Logic Controller for MPPT of PMSG-Based Wind Turbines

et al. 2021

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“…It is generally built on the load side. is power generation way reduces the problems of voltage loss, power mass defect, power oscillation [5], and power shortage caused by long-distance power transmission [6]. ere must be a large number of electronic interface devices in the microgrid [7], such as inverter [8,9].…”

Section: Introductionmentioning

confidence: 99%

An Improved Fuzzy Voltage Compensation Control Strategy for Parallel Inverter

Song

Liu

Tian

et al. 2022

International Transactions on Electrical Energy Systems

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With the rapid development of microgrids, voltage drop has become one of the focuses on the research of microgrid stability and grid-connected operation. In this article, an improved fuzzy voltage compensation control strategy (FVCC) is proposed to solve the bus voltage drop problem. This method takes the influence of feeder impedance into account, and there is no need to accurately measure the feeder impedance value. Since droop control and feeder impedance can lead to voltage drop and bus voltage instability, fuzzy control is applied to compensate bus voltage. Specifically, aiming at the voltage drop caused by droop control, an adaptive fuzzy controller is designed to automatically find suitable gain parameters to reduce the voltage difference. In addition, bus voltage gain module is added to compensate the voltage consumed by feeder impedance. The compensation only needs to measure the voltage at both ends of the line, without testing the line parameters. Finally, the simulation results show that the control strategy achieves the expected effect.

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“…Consequently, the power system under control cannot perform desirably over a wide range of disturbances. Therefore, novel and near‐optimum methods are strongly needed to provide a balanced, efficient, and robust frequency control 21‐24 . Also, the robustness of area control error systems against intermittent renewable energy integrated grid has not been thoroughly evaluated in the literature.…”

Section: Introductionmentioning

confidence: 99%

Improving frequency regulation of wind‐integrated multi‐area systems using LFA‐fuzzy PID control

Kheshti

Ding

Abyaneh

et al. 2021

Int Trans Electr Energ Syst

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Summary Due to the complexity and importance of the electricity grid stability, sophisticated control systems and computational approaches are essentially required to solve dynamical system frequency problems in multi‐area systems. Participation of wind turbines in power system frequency control in the form of stepwise inertial control in the presence of a proposed adequately tuned fuzzy‐PID load‐frequency control is investigated in this paper. A two‐area power system is studied in which it is linked through tie‐line and equipped with fuzzy‐PID control systems. To increase the energy transition and flexibility of the entire system against frequency events and parameters uncertainties, the fuzzy‐PID controllers are first tuned using lightning flash algorithm (LFA). The tuned controllers are then used in each area to optimally counterbalance the frequency deviations and the tie‐line power of the interconnected areas against varying load disturbances, wind power fluctuations, and to keep the renewable integrated system in a stable state. The sensitivity analysis is also conducted with a wide range of system parameter variations, uncertainties, and disturbances. Furthermore, the LFA‐tuned fuzzy‐PID load‐frequency control is also tested in a two‐area isolated microgrid, comprising wind turbine, PV panels, fuel cells, micro‐turbine, and diesel engine generator. The results obtained using the proposed approach are compared with other state‐of‐the‐arts algorithms and control systems in the literature. The compared results show the efficiency and robustness of the proposed optimization‐based controller for better frequency control in multi‐area power systems and isolated microgrids. The results also demonstrate that a finely tuned automatic generation controller gives a significant boost to grid frequency control when wind turbines participate in the inertial control, suggesting migration from conventional PID‐based automatic generation control to more adaptive control approaches.

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Adaptive fuzzy based optimized proportional‐integral controller to mitigate the frequency oscillation of multi‐area photovoltaic thermal system

Cited by 37 publications

References 22 publications

Implementation and Validation of an Adaptive Fuzzy Logic Controller for MPPT of PMSG-Based Wind Turbines

Implementation and Validation of an Adaptive Fuzzy Logic Controller for MPPT of PMSG-Based Wind Turbines

An Improved Fuzzy Voltage Compensation Control Strategy for Parallel Inverter

Improving frequency regulation of wind‐integrated multi‐area systems using LFA‐fuzzy PID control

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