ANN Based DC Link Control of STATCOM in Wind Integrated Distribution System for Power Quality Conditioning

Rani, Shweta; Prabakaran, S.

doi:10.48084/etasr.3630

Cited by 4 publications

(3 citation statements)

References 29 publications

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“…Wind Energy Generation Systems (WEGS) with double-fed IG are used in power generation due to their low cost and variable speed constant frequency operation [3]. However, since wind power is typically located far from consumers, it is necessary to provide shunt compensation at Points of Common Coupling (PCC) [4], while Multi Terminal Load (MTL) connected to the wind farm at PCC produces power quality issues such as frequency variations and voltage sags/swells [5]. Voltage flickers are abrupt frequency changes for short durations due to load switching and integration of compensatory devices [6].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, various compensators with filters have been adopted to mitigate these power quality problems [9][10][11][12]. Many power quality conditioners have been implemented to address power quality issues in distribution networks, such as UPQC, DVR, and DSTATCOM [4,9,13,14]. Among the different FACTS controllers, SVC and STATCOM play an important role in reactive power compensation [12,16].…”

Section: Introductionmentioning

confidence: 99%

“…However, when selecting a FACTS device, the performance of different types of shunt compensators should be examined based on fast response, reactive power compensator range, switching losses, resonance problems, energy source requirements, and DC link capacitor value [13]. Various control techniques have been proposed for the operating performance of various shunt compensators, such as nonlinear control, Lyapunov function-based control [17], instantaneous p-q theory [18], negative and zero sequence control [6,[19][20], instantaneous d-q theory [13], backpropagation control [4], and the instantaneous id-iq method [7,16]. Hybrid structures were introduced in [7,21] to improve STATCOM operation with lower current rating APFs and PPFs.…”

Section: Introductionmentioning

confidence: 99%

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Power Quality Enhancement in a Wind Farm Connected Grid with a Fuzzy-based STATCOM

Adware

Chandrakar

2023

Eng. Technol. Appl. Sci. Res.

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Integrating wind farms with electricity transmission networks presents several problems, and power quality plays a vital role among these. This study proposed a novel fuzzy logic controller to reduce the effect of power quality issues in such applications and investigated two different FACTS (Flexible AC Transmission System) devices, the Static Var Compensator (SVC) and the Static Synchronous Compensator (STATCOM). The fuzzy logic controller was designed as a voltage controller to improve power quality. Detailed analysis was carried out to investigate the successful mitigation of voltage sag/swell, active and reactive power improvement, and voltage flickers control by two controllers in a Multi-Terminal Load (MTL) system consisting of wind generators. The results were verified in MATLAB simulations, and a comparison was performed between the proposed shunt controllers. Furthermore, the design of a fuzzy interference system based on Vref (reference voltage) and the voltage measured at STATCOM location signals was investigated and compared with the SVC in terms of voltage sag, voltage swell, voltage flickers, and Total Harmonic Distortions (THD). The proposed fuzzy system was compared with a PI-based STATCOM and SVC. The power quality issues were exacerbated when using Multi-Terminal Load (MTL) in the transmission network.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Power Quality Enhancement in a Wind Farm Connected Grid with a Fuzzy-based STATCOM

Adware

Chandrakar

2023

Eng. Technol. Appl. Sci. Res.

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Deep CNN–LSTM-Based DSTATCOM for Power Quality Enhancement in Microgrid

Kandasamy¹,

Kumar²,

Natarajan

et al. 2022

J CIRCUIT SYST COMP

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Power quality issues and their effective mitigation invariably play a crucial role in a microgrid system. Such power quality problems are often resolved by employing multiple power electronics-based components in the utility grid. This paper is focused on the optimal enhancement of power quality under islanded mode of operation in a microgrid, with a deep Convolutional Neural Network (CNN) with Long Short-term Memory (LSTM) algorithm using distribution static compensator (DSTATCOM). The objective of the research is centered on the reactive power control in DSTATCOM using deep CNN with LSTM for voltage enhancement, minimization of current distortion and reduction of harmonics on a microgrid. This objective can be achieved by the proposed Simulink design model of DSTATCOM intended for improving the power quality in a microgrid. The renewable energy-based power compensator is used for an enhanced and effective control strategy like voltage and current control of the microgrid circuit and uses LSTM-based deep CNN for achieving superior time consumption indicators. Due to varying loads in the microgrid, the reactive power and harmonic voltage and current may be distorted. This problem can be rectified by controlling the microgrid using the LSTM-based deep CNN. This approach consequently reduces the negative-sequence frequency range with the aid of this filtering method in the proposed microgrid circuit. The microgrid is thereafter subjected to different testing conditions and the corresponding simulation results are discussed in relation to existing approaches. The proposed framework was observed to have successfully accomplished harmonic substance and voltage profile enhancement.

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Robust Speed Control of a Three Phase Induction Motor Using Support Vector Regression

Mugheri

Keerio

Chandio

et al. 2021

Eng. Technol. Appl. Sci. Res.

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The Three Phase Induction Motor (TIM) is one of the most widely used motors due to its low price, robustness, low maintenance cost, and high efficiency. In this paper, a Support Vector Regression (SVR) based controller for TIM speed control using Indirect Vector Control (IVC) is presented. The IVC method is more frequently used because it enables better speed control of the TIM with higher dynamic performance. Artificial Neural Network (ANN) controllers have been widely used for TIM speed control for several reasons such as their ability to successfully train without prior knowledge of the mathematical model, their learning ability, and their fast implementation speed. The SVR-based controller overcomes the drawbacks of the ANN-based controller, i.e. its low accuracy, overfitting, and poor generalization ability. The speed response under the proposed controller is faster in terms of rising and settling time. The dynamic speed response of the proposed controller is also superior to that of the ANN-PI controller. The performance of the proposed controller was compared for TIM speed control with an ANN-PI controller via simulations in SIMULINK.

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ANN Based DC Link Control of STATCOM in Wind Integrated Distribution System for Power Quality Conditioning

Cited by 4 publications

References 29 publications

Power Quality Enhancement in a Wind Farm Connected Grid with a Fuzzy-based STATCOM

Power Quality Enhancement in a Wind Farm Connected Grid with a Fuzzy-based STATCOM

Deep CNN–LSTM-Based DSTATCOM for Power Quality Enhancement in Microgrid

Robust Speed Control of a Three Phase Induction Motor Using Support Vector Regression

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