Mitigation of low frequency oscillations in power systems based on Mamdani fuzzy inference

Gao, Hongliang; Zhan, Xisheng; Yuan, Yi-Ran; Pan, Zijie; Yuan, Guo-Long

doi:10.1177/0142331219826668

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…In the study of power system stability, a novel design of an Interval Type-2 Fuzzy–based Wide Area Power System Stabilizer is proposed to damp the inter-area mode of oscillations in Sreedivya et al (2021) to improve the stability of the power system very well. In addition, a novel PID controller based on the Mamdani fuzzy inference (MFPID) is proposed in Gao et al (2019), which has a better mitigation effect for low-frequency oscillations in power systems after disturbances. In the study of power quality problems, Naderipour et al (2020) proposed a fuzzy logic controller (FLC) to optimize the susceptance function to improve the voltage profile further and reduce static var compensator capacitance.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy adaptive tuning control of power system based on moth-flame optimization algorithm

Gao

Xiong

et al. 2023

Transactions of the Institute of Measurement and Control

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Since low-frequency oscillation seriously threatens the safe operation of the power system, the power system stabilizer (PSS) can effectively suppress the oscillation. In this paper, a hybrid parameter optimization method combining the moth-flame optimization (MFO) algorithm and fuzzy logic controller (FLC) is proposed to address the problem of poor adaptability of the parameter tuning method in the conventional power system stabilizer (CPSS). This method can optimize the parameters of PSS in different processes. Initially, the optimal parameters of PSS under the current perturbation are given by the MFO algorithm. During the online operation of the system, as perturbation changes, the parameters of the PSS will also be adaptively tuned by the FLC in real-time when the system operating conditions change. According to this method, a fuzzy adaptive proportional–integral–differential (FPID) controller is designed based on the moth-flame optimization algorithm (MFO-FPID), and it is used as PSS to improve dynamic stability performance during oscillation. Moreover, its parameters can be adaptively adjusted in different perturbation scenarios. The designed MFO-FPID controller is applied to the single machine infinite bus (SMIB) power system to compare the dynamic performance with other controllers, that is, proportional–integral–differential (PID) and CPSS. The result shows that the MFO-FPID controller can suppress the oscillation very well, and the control effect is the best.

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Section: Introductionmentioning

confidence: 99%

Fuzzy adaptive tuning control of power system based on moth-flame optimization algorithm

Gao

Xiong

et al. 2023

Transactions of the Institute of Measurement and Control

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“…e stability of the system has always been a key issue in the design of control systems, and its application range is extremely wide. For example, the consistency of multiagent systems and the improvement of power systems are closely related to stability issues [1][2][3][4][5]. In the research of nonlinear systems such as aircrafts, inverted pendulums, and timevarying state-delay systems, some scholars have also conducted in-depth studies on their stability.…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control of the Vehicle Speed System Based on LMIs

Gao

Zhang

2021

Complexity

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Due to the nonlinear characteristics of the vehicle speed system, its stability is difficult to control. This paper analyzes the stability and traceability of the vehicle speed system under nonlinear characteristics. A sliding mode control method of the nonlinear system state observation based on linear matrix inequalities (LMIs) is proposed. In the proposed control method, Lyapunov function is used as the control function to track the position and speed of the vehicle speed system in real time. In the design process of the controller, the successive scaling method (SSM) is designed to improve the tracking accuracy. The simulation results demonstrate that the sliding mode control can effectively track the position of the vehicle speed system, which has better stability and traceability for the nonlinear vehicle speed system.

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“…The hybrid controller provides the robust control during disturbances and recovers the steady-state condition in short duration by adopting the switch control approach. The stability analysis of a system for certain power system issues are discussed (Gao et al, 2019). The harmonic estimation technique of numerous measured parameters for a time varying signal is discussed.…”

Section: Introductionmentioning

confidence: 99%

Real time assessment of power quality issues in 11 kV/440 V distribution feeder using distribution static synchronous compensator

Srinivasan¹,

Krishnamoorthy

Pongiannan

et al. 2020

Transactions of the Institute of Measurement and Control

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The effects of power quality (PQ) issues in a distribution feeder occur due to abnormal load condition. In this paper, first, the real time PQ issues in an 11 kV/440 V distribution feeder are measured and analyzed by PQ analyzers. The sudden load fluctuations in the distribution system result in different PQ issues such as voltage sag/swell, transient, flicker and harmonics. Then, an improved interactive distribution static synchronous compensator (D-STATCOM) is installed in distribution feeder to mitigate the PQ issues. A novel control algorithm will operate the interactive D-STATCOM in voltage control mode (VCM) or current control mode (CCM). At normal operating conditions, the D-STATCOM operates in CCM, during abnormal condition the D-STATCOM will operates in VCM to mitigates the PQ issues. The D-STATCOM is modeled and simulated in MATLAB-SIMULINK environment. The field programmable gate array (FPGA)-based laboratory prototype D-STATCOM has been developed to validate the function of the controller.

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Mitigation of low frequency oscillations in power systems based on Mamdani fuzzy inference

Cited by 5 publications

References 20 publications

Fuzzy adaptive tuning control of power system based on moth-flame optimization algorithm

Fuzzy adaptive tuning control of power system based on moth-flame optimization algorithm

Sliding Mode Control of the Vehicle Speed System Based on LMIs

Real time assessment of power quality issues in 11 kV/440 V distribution feeder using distribution static synchronous compensator

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