Harmonic Amplification Damping Using a DSTATCOM-based Artificial Intelligence Controller

In this paper, the importance of voltage stability is explained, which is a great problem in the EPS. The estimation of VS is made a priority so as to make the power system stable and prevent it from reaching voltage collapse. The power transfer stability index (PTSI) is used as a predictor utilized in a PSN to detect the instability of voltages on weakened buses. A PSI is used to obtain a voltage assessment of the PSNs. Two hybrid algorithms are developed. The (CA-NN) and the (PSO-NN). After developing algorithms, they are compared with the actual values of PTSI NR method. The algorithms installed on the 24 bus Iraqi PS. The actual values of PTSI are the targets needed. They are obtained from the NR algorithm when the input data is Vi, δi, Pd, Qd for the algorithm. The results indicate that a weak bus that approaches voltage collapse and all results were approximately the same. There is a slight difference with the actual results and demonstrated classical methods are slower and less accurate than the hybrid algorithms. It also demonstrates the validation and effectiveness of algorithms (CA-NN, and PSO-NN) for assessing voltage-prioritizing algorithms (CA-NN). The MATLAB utilized to obtain most of the results.

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“…Weighted numbers are utilized to weight the acceleration. In (9) presents the velocity vector [24,25].…”

Section: Hybrid Algorithm Particle Swarm Optimization-neural Network (Pso-nn) For Ptsimentioning

confidence: 99%

Assessment of voltage stability based on power transfer stability index using computational intelligence models

Ghadban

Salman

Hussein

2021

IJECE

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“…One of the forms of power quality issues is the harmonics problem [13]. A DSTATCOM controller based on discrete-time multilayer neural networks was described.…”

Section: Introductionmentioning

confidence: 99%

Improving Power Quality by DSTATCOM Based DQ Theory with Soft Computing Techniques

Nandagopal¹,

Damodhar²,

Vijayapriya³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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The development of non-linear loads at consumers has significantly impacted power supply systems. Since, the poor power quality has been found in the three-phase distribution system due to unbalanced loads, harmonic current, undesired voltage regulation, and extreme reactive power demand. To overcome this issue, Distributed STATicCOMpensator (DSTATCOM) is implemented. DSTATCOM is a shunt-connected Voltage Source Converter (VSC) that has been utilized in distribution networks to balance the bus voltage in terms of enhancing reactive power control and power factor. DSTATCOM can provide both rapid and continuous capacitive and inductive mode compensation. A rectified resistive and inductive load eliminates current harmonics in a three-phase power supply. The synchronous fundamental DQ frame is a time-domain approach developed from three-phase system space vector transformations has been designed using MATLAB/Simulink. The DQ theory is used to produce the reference signal for the Pulse Width Modulation (PWM) generator. In addition, a traditional Proportional Integral Derivative (PID) controller is designed and compared with proposed soft computing approaches such as Fuzzy-PID and Artificial Neural Network (ANN-PID) and compared accurate reference current determination for Direct Current (DC) bus through DC link. An Analytical explores the proposed control strategies given to establish superior outcomes. Finally, total harmonic distortion analysis should be taken for performance analysis of the proposed system with IEEE standards.

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“…In [10], FACTS devices were utilised to improve power system operation control, and PMU was used as a monitor to improve the capability of state estimation systems and full observable systems. The stability of a power system is a crucial area of research to describe the harmonics problem, and many studies employ FACT devices, such as DSTATCOM, as shown in [11,12]. State estimation is extremely important in a power distribution system for determining the variable state in a system network, as shown in [13].…”

Section: Introductionmentioning

confidence: 99%

Application of computational methods for harmonic state estimation of power system networks

Naji

Hussein

2021

IJEECS

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In this study, a novel technique is used to estimate the power system harmonic state, as one of the biggest risks in a power system network. Nonlinear loads are widely used, which inject harmonics into a system. Such injected harmonics make networks unstable and increase power loss. The main objective of this work is to develop a new harmonic state estimator system to increase power system accuracy, stability and the wall operation state. Three computational methods are used in this study, that is, the i) proposed particle swarm optimisation-recursive least squares (PSO-RLS) algorithm, which is developed, presented and compared with the ii) discrete fourier transform (DFT) and iii) PSO algorithms. The three algorithms are tested on an IEEE 14-bus system, and simulation results show that the new PSO-RLS algorithm is more accurate than the other two algorithms (i.e. DFT and PSO algorithms), with a lower error percentage. The proposed algorithm is tested to prove its validity and effectiveness in power system networks. The capability of the PSO-RLS algorithm is apparent in the error percentage compared with that of the other two computational methods, which can be used to provide an excellent prediction rate for measurement errors in system buses.

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Harmonic Amplification Damping Using a DSTATCOM-based Artificial Intelligence Controller

Cited by 4 publications

References 11 publications

Assessment of voltage stability based on power transfer stability index using computational intelligence models

Assessment of voltage stability based on power transfer stability index using computational intelligence models

Improving Power Quality by DSTATCOM Based DQ Theory with Soft Computing Techniques

Application of computational methods for harmonic state estimation of power system networks

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