Genetic Algorithm-Based Analysis of the Effects of an Additional Damping Controller for a Doubly Fed Induction Generator

Tan, Aiguo; Tang, Zhihan; Sun, Xianbo; Liao, Haiyan; Fang, Haibing

doi:10.1007/s42835-020-00440-7

Cited by 8 publications

(6 citation statements)

References 22 publications

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“…The optimization method is a hybrid algorithm that consists of a genetic set of rules blended with a local search method (Gradient or Simplex) and which acts at the parameters of the regulator [21]. The following Figure illustrates the diagram of this method.…”

Section: Optimization Procedures For the Two Regulatorsmentioning

confidence: 99%

Optimization Using a Genetic Algorithm Based on DFIG Power Supply for the Electrical Grid

2022

IJE

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Section: Optimization Procedures For the Two Regulatorsmentioning

confidence: 99%

Optimization Using a Genetic Algorithm Based on DFIG Power Supply for the Electrical Grid

2022

IJE

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“…To ensure that the PV system operate in the maximum power MPP, it is necessary that the error z of Eq. ( 18) converges to zero, in order to achieve this constraint, we uses the Barbalat's lemma which is proposed by Slotine and Li in the Ref [53], where its conditions are: (26)…”

Section: Crow Search Algorithm (Csa) Based Mpptmentioning

confidence: 99%

“…With the rapid progressing of Genetic Algorithm (GA) in the area of optimization, the controllers designing field with GA has gradually become a significant direction [26]. Sundareswaran et al [27] proposed a GA-P&O technique combining GA with P&O under PSCs; first, they selected six uniformly distributed chromosomes for three iterations in GA and then initialized the duty cycle of P&O to ensure efficient and rapid tracking of GMPP.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Metaheuristic Technique to Control the Maximum Power Point of a Partially Shaded Photovoltaic System Using Crow Search Algorithm (CSA)

Houam

Terki

Bouarroudj

2020

J. Electr. Eng. Technol.

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The field of research in maximum power point tracking (MPPT) methods is experiencing great progress with a wide range of techniques being suggested, ranging from simple but ineffective methods to more effective but complex ones. Therefore, it is very important to propose a strategy that is both simple and effective in controlling the global maximum power point (GMPP) for a photovoltaic (PV) system under changing weather conditions, especially in partial shading cases (PSCs). This paper proposes a new design of an MPPT controller based on a metaheuristic optimization technique called Crow Search Algorithm (CSA) to attenuate the undesirable effects of partial shading on the tracking performances of standalone PV systems. CSA is a nature-inspired method based on the intelligent skills of the crow in the search process of hidden food places. CSA technique combines efficiency and simplicity using only two tuning parameters. The stability analysis of the proposed system is performed using a Lyapunov function. The simulation results for three different partial shading cases that are zero, weak and severe shading confirm the superior performance of CSA compared to PSO and P&O techniques in term of easy implementation, high efficiency and low power loss, decreasing considerably the convergence time by an average of 38.53%.

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“…The use of optimization techniques allows for the design of an effective controller. But in the large‐scale area interconnected power system with more generators, the PSS for SG and POD for WF may sometimes need to sufficiently dampen in local and inter‐area where LFO needs to be suppressed 14–17 . The integration of PSS/POD with a flexible AC Transmission System (FACTS) further enhances the performance of the controller by providing additional damping to the system along with suppress the oscillations and enhance the damping of LFOs to the greatest extent.…”

Section: Introductionmentioning

confidence: 99%

“…But in the large-scale area interconnected power system with more generators, the PSS for SG and POD for WF may sometimes need to sufficiently dampen in local and inter-area where LFO needs to be suppressed. [14][15][16][17] The integration of PSS/POD with a flexible AC Transmission System (FACTS) further enhances the performance of the controller by providing additional damping to the system along with suppress the oscillations and enhance the damping of LFOs to the greatest extent. The proposed approach uses a combination of an artificial neural network and particle swarm optimization, a hybrid algorithm of particle swarm optimization (PSO), an improved artificial bee colony algorithm (ABC), cuckoo search method (CSM), bacterial foraging (BF), modified fruit fly optimization algorithm (MFOA), and genetic algorithm (GA) to optimize the control parameters.…”

Section: Introductionmentioning

confidence: 99%

Enhancing the wind farm‐based power system stability with coordinated tuned supplementary controller

Bhukya

2023

Circuit Theory & Apps

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SummaryThe effects of the wind farm on the low‐frequency oscillations of interconnected power systems have become a significant problem with extensive apprehension. These low‐frequency oscillations are undesirable, malfunctioning and resulting in system instability. This paper studies the influence of various factors on stability, with varying wind penetration, a different combination of controllers, wind farm (WF) integration and replacement of synchronous generators. To enhance the stability, it is integrated and analyzed significance of the controller by considering the power oscillation damper for WF, power system stabilizer for synchronous generators and supplementary controller of flexible AC transmission system devices for the system. The rotor speed deviation is considered an objective function with various constraints for particle swarm optimization to provide the controller's optimized value and combination. The small‐signal and transient stability problems were examined using eigenvalue analysis and time‐domain simulation. The state‐space formulation is derived for eigenvalue analysis for small signal stability assessment with system variables. The nonlinear dynamic simulation results for transient stability analysis are obtained using a three‐phase fault. From stability analysis, coordinated controllers intensify the capability of SGs and WF under extreme disturbances. The effectiveness and robustness of the proposed approaches have been verified using the IEEE‐9 bus test system. All the analysis and simulations are performed using real time digital simulation (RTDS) with interfacing between MATLAB/SIMULINK‐2018a software and RT‐LAB (an OP5600 RT‐LAB).

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Genetic Algorithm-Based Analysis of the Effects of an Additional Damping Controller for a Doubly Fed Induction Generator

Cited by 8 publications

References 22 publications

Optimization Using a Genetic Algorithm Based on DFIG Power Supply for the Electrical Grid

Optimization Using a Genetic Algorithm Based on DFIG Power Supply for the Electrical Grid

An Efficient Metaheuristic Technique to Control the Maximum Power Point of a Partially Shaded Photovoltaic System Using Crow Search Algorithm (CSA)

Enhancing the wind farm‐based power system stability with coordinated tuned supplementary controller

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