Real-Time LFO Damping Enhancement in Electric Networks Employing PSO Optimized ANFIS

Pathan, Ilius Hasan; Rana, Juel; Shahriar, Mohammad Shoaib; Shafiullah, Md; Zahir, Md. Hasan; Ali, Amjad

doi:10.3390/inventions5040061

Cited by 10 publications

(4 citation statements)

References 44 publications

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“…However, damping controller design is an optimization-centered process that requires the exploitation of various optimization algorithms [32]. The damping of power system oscillations with damping controllers mostly depends on the tuning strategy adopted in obtaining the optimal parameters [33]. Time integral performance criteria for calculating the integral error of the damping controller [32] and the eigenvalue-based stability analysis on the multi-machine test system are employed to evaluate the performance of damping controllers.…”

Section: Offshore Platformmentioning

confidence: 99%

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

et al. 2022

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Massive growth in global electrical energy demand has necessitated a genuine exploration and integration of solar and wind energy into the electrical power mix. This incorporation goes a long way in improving the cumulative generated power capacity of the power system. However, wind and solar photovoltaic (PV) are intermittent in nature, making the provisioning of a good maximum power tracking (MPPT) scheme necessary. Furthermore, the integration is characterized by synchronization challenges and introduces various modes of power system oscillations as it is converter-driven. This greatly affects the overall stability of the integrated power mix. Consequently, various technological models have been designed to address these challenges ranging from MPPT schemes, phase-lock loop (PLL), virtual synchronous generator (VSG), power system stabilizers (PSS), flexible AC transmission system (FACTS), coordinated control and artificial intelligence (AI). In this work, a multi-machine power system model is reviewed for integration stability studies. Various technical solutions associated with the integration are also reviewed. MPPT, PLL, VSG, PSS, FACTS, coordinated control, and various optimization technique schemes used for damping controller design are discussed.

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Section: Offshore Platformmentioning

confidence: 99%

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

et al. 2022

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“…Moreover, FLC struggle when dealing with highly complex and nonlinear systems, which can be a limitation when trying to control the dynamic behaviour of power systems with UPFC. The newly generated real-time dynamics were controlled using an intelligent control approach, specifically the adaptive neuro fuzzy inference system (ANFIS) technique [37]. ANFIS models lack transparency, making it difficult to understand the reasoning behind control decisions, which can be a concern for critical systems like UPFC.…”

Section: Introductionmentioning

confidence: 99%

Mitigation of power quality disturbances in wind energy conversion systems with fed unified power flow controllers using cascaded adaptive neuro-fuzzy inference system controller

2023

IJATEE

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Power flow optimization is a critical aspect of power and control system design, aiming to minimize running costs while ensuring control variable tolerances and maximizing power delivery. The utilization of flexible alternating current transmission system (FACTS) particularly unified power flow controllers (UPFCs), enhances a system's power transfer capacity. UPFCs offer versatile adjustments for active and reactive power lines and voltage levels simultaneously, contributing to improved system performance and stability. A novel approach for enhancing flexibility and control in a doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) was proposed. The technique involved the integration of a fuzzy-based control strategy for UPFC and the utilization of a cascaded adaptive neuro fuzzy inference system (ANFIS) to manage UPFC's series and shunt converters. Additionally, an improved butterfly optimization algorithm (IBOA) was introduced to ensure stability for DFIG-WECS. The methods were implemented and validated through simulations using MATLAB software. The effectiveness of the proposed approach was demonstrated through experimental results. The integration of cascaded ANFIS-based UPFC control and IBOA with WECS resulted in increased system power quality and stability. The total harmonic distortion (THD) of the system is reduced by 1.8%, indicating an enhancement in power quality. The application of UPFC and innovative control methodologies results in optimal power flow (OPF), maintaining stringent control variable tolerances in power systems. This research presents a systematic approach to enhancing flexibility and control in a DFIG-based WECS through the innovative use of UPFC and advanced control techniques. The proposed fuzzy-based UPFC control, in conjunction IBOA, significantly improves power quality and stability, thereby enhancing the overall efficiency of the system.

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“…NN controller was used to replace PSSs and AVR on a SMIB test power system for control of LFOs (Abdulgabbar and Ahmed, 2017). ANFIS controllers-based PSO have been implemented for real-time LFO damping improvement in Pathan et al (2020), where the ANFIS controllers were found to be able to sustain the dynamic stability of the multi-machine test systems successfully. Type-2 fuzzy PID-PSSs (Shokouhandeh and Jazaeri, 2018) was developed to improve the stability of multi-machine power systems.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, input MF of the T2FLS is three Gaussian MFs. The authors in Pathan et al (2020) studied the role of a prominent machine learning family member, PSO to optimized ANFIS for real-time improvement of LFOs on SMIB test system. These AIs structures and configurations are usually not model-free designed; as such, these will cause a very high computational cost for operating the controller on a large scale test power system.…”

Section: Introductionmentioning

confidence: 99%

Application of a neuro-fuzzy controller for single machine infinite bus power system to damp low-frequency oscillations

Sabo

Wahab

Othman

et al. 2021

Transactions of the Institute of Measurement and Control

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Generally, power systems experience a variety of disturbances that can result in low frequency electromechanical oscillations. These low frequency oscillations (LFOs) take place among the rotors of synchronous generators connected to the power system. These oscillations may sustain and grow to cause system separation if no adequate damping is provided. Power system stabilizers (PSSs) are one of the alternative devices used to solve this rotor oscillation problem. The major limitation of using PSSs at the excitation system of synchronous machine is that the conventional PSS is a permanent parameter type operating under a particular system operating condition, and its parameters are acquired through trial and error. An efficient way of operating the PSS has been by designing the PSS parameters using a powerful optimization procedure. However, designing PSS damping controller is a cumbersome task as it needs a comprehensive test system modeling and a heavy computational burden on the system. In this research, a novel, model-free neuro-fuzzy controller (NFC) is designed as the LFOs’ damping controller to substitute the traditional PSS system making the power system simple without complications in PSS design and parameter optimization. The proposed controller application implements the LFOs’ control without a linearized mathematical model of the system, as such it makes the system less complex and bulky. Single machine infinite bus (SMIB) test system was simulated in SIMULINK domain with the PSSs and with the proposed controller to compare the NFC effectiveness. The simulation outcome for the eigenvalue study with NFC stabilizer yields steady eigenvalues that enhanced the damping status of the system greater than 0.1 with decreased overshoots and time to rise via the proposed NFC process than with the conventional FFA-PSS. Similarly, the generator transient reaction also presents the ω and δ based on the time to settle was improved by 64.66% and 28.78%, respectively, via the proposed NFC process than with the conventional FFA-PSS. Finally, the conventional PSS was found to be complicated in its design, parameter optimization and less effective than the proposed controller for the LFOs’ control.

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Real-Time LFO Damping Enhancement in Electric Networks Employing PSO Optimized ANFIS

Cited by 10 publications

References 44 publications

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

Solar, Wind and Their Hybridization Integration for Multi-Machine Power System Oscillation Controllers Optimization: A Review

Mitigation of power quality disturbances in wind energy conversion systems with fed unified power flow controllers using cascaded adaptive neuro-fuzzy inference system controller

Application of a neuro-fuzzy controller for single machine infinite bus power system to damp low-frequency oscillations

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