Implementation of artificial neural network based controller for a five-level converter based UPQC

Vinnakoti, Sudheer; Kota, Venkata Reddy

doi:10.1016/j.aej.2017.03.027

Cited by 30 publications

(15 citation statements)

References 15 publications

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“…Nevertheless, the strategy is applicable where load periodicity is not constant. A Multi-level diode clamped converter (DCC) ANN-based UPQC has been evaluated with distorted supply voltage and unbalanced non-linear loads in [17,18] to eliminate the mathematical model and complex controllers. An ANN-based controller for current control of shunt APF has been presented in [3] to replace the PI controller over the ANN controller to encounter voltage related issues.…”

Section: Introductionmentioning

confidence: 99%

Implementation of ANN Controller Based UPQC Integrated with Microgrid

et al. 2022

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This study discusses how to increase power quality by integrating a unified power quality conditioner (UPQC) with a grid-connected microgrid for clean and efficient power generation. An Artificial Neural Network (ANN) controller for a voltage source converter-based UPQC is proposed to minimize the system’s cost and complexity by eliminating mathematical operations such as a-b-c to d-q-0 translation and the need for costly controllers such as DSPs and FPGAs. In this study, nonlinear unbalanced loads and harmonic supply voltage are used to assess the performance of PV-battery-UPQC using an ANN-based controller. Problems with voltage, such as sag and swell, are also considered. This work uses an ANN control system trained with the Levenberg-Marquardt backpropagation technique to provide effective reference signals and maintain the required dc-link capacitor voltage. In MATLAB/Simulink software, simulations of PV-battery-UPQC employing SRF-based control and ANN-control approaches are performed. The findings revealed that the proposed approach performed better, as presented in this paper. Furthermore, the influence of synchronous reference frame (SRF) and ANN controller-based UPQC on supply currents and the dc-link capacitor voltage response is studied. To demonstrate the superiority of the suggested controller, a comparison of percent THD in load voltage and supply current utilizing SRF-based control and ANN control methods is shown.

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Section: Introductionmentioning

confidence: 99%

Implementation of ANN Controller Based UPQC Integrated with Microgrid

et al. 2022

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“…Nonetheless, they require a lot of time and effort to be implemented in order to avoid the overfitting of the data while maintaining a good accuracy. [41][42][43][44] For the case in which EV chargers are used as APFs, [45][46][47][48] they success in reducing harmonic content but they also involve a high development cost, even more if they are designed for both reducing harmonics and giving grid support. 49,50 Many control strategies focus on selective harmonic elimination (SHE) algorithms, [51][52][53][54] but most are based on multilevel converters, which despite their better harmonic response are more expensive in cost, and require more volume and weight as they consist of more elements.…”

Section: Introductionmentioning

confidence: 99%

Vehicle‐to‐grid charging control strategy aimed at minimizing harmonic disturbances

et al. 2021

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This paper presents the design and implementation of a control for an electric vehicle charger to provide vehicle to grid (V2G) services while reducing the current total harmonic distortion (THD). The control is composed of two current loops. The main one controls the active and reactive powers in a decoupled way, and the second one, focuses on the reduction of the fifth order harmonic component. After explaining the mathematical modelling, the meth-

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“…A UPQC (Yavari et al , 2018; Vinnakoti and ReddyKota, 2018; Li et al , 2015; GowthamShobhaShankar, 2018; González and Valla, 2015) includes series and shunt inverter, in which the shunt inverter grants the compensation of harmonic as well as reactive power via injecting the shunt current to the load. Further, the utilization of series inverter is more crucial in the voltage mitigation-associated issues such as sag and swells in supply voltage, and that are through the injection of controllable series voltage.…”

Section: Introductionmentioning

confidence: 99%

Optimal location of UPQC for power quality improvement: novel hybrid approach

Gaddala¹,

Raju²

2020

JEDT

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Purpose In general, the optimal reactive power compensation could drastically enhance the performance of distributed network by the reduction of power loss and by enhancement of line loadability and voltage profile. Till now, there exist various reactive power compensation models including capacitor placement, joined process of on-load tap changer and capacitor banks and integration of DG. Further, one of the current method is the allocation of distribution FACTS (DFACTS) device. Even though, the DFACTS devices are usually used in the enhancement of power quality, they could be used in the optimal reactive power compensation with more effectiveness. Design/methodology/approach This paper introduces a power quality enhancement model that is based on a new hybrid optimization algorithm for selecting the precise unified power quality conditioner (UPQC) location and sizing. A new algorithm rider optimization algorithm (ROA)-modified particle swarm optimization (PSO) in fitness basis (RMPF) is introduced for this optimal selections. Findings Through the performance analysis, it is observed that as the iteration increases, there is a gradual minimization of cost function. At the 40th iteration, the proposed method is 1.99 per cent better than ROA and genetic algorithm (GA); 0.09 per cent better than GMDA and WOA; and 0.14, 0.57 and 1.94 per cent better than Dragonfly algorithm (DA), worst solution linked whale optimization (WS-WU) and PSO, respectively. At the 60th iteration, the proposed method attains less cost function, which is 2.07, 0.08, 0.06, 0.09, 0.07 and 1.90 per cent superior to ROA, GMDA, DA, GA, WS-WU and PSO, respectively. Thus, the proposed model proves that it is better than other models. Originality/value This paper presents a technique for optimal placing and sizing of UPQC. To the best of the authors’ knowledge, this is the first work that introduces RMPF algorithm to solve the optimization problems.

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Implementation of artificial neural network based controller for a five-level converter based UPQC

Cited by 30 publications

References 15 publications

Implementation of ANN Controller Based UPQC Integrated with Microgrid

Implementation of ANN Controller Based UPQC Integrated with Microgrid

Vehicle‐to‐grid charging control strategy aimed at minimizing harmonic disturbances

Optimal location of UPQC for power quality improvement: novel hybrid approach

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