SAPF Parameter Optimization with the Application of Taguchi SNR Method

Sao, Jitendra Kumar; Naayagi, R. T.; Panda, Gayadhar; Patidar, R. D.; Swain, Sushree Diptimayee

doi:10.3390/electronics11030348

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…It is essential to fine-tune the PI controller's values for optimum performance. The conventional approach to tuning the PI-controller gains relies on linear modeling, which typically yields inadequate settings for the gains [13,14]. To this end, many different met heuristic optimization strategies are used in PI-controller tuning.…”

Section: Fig 1 Pv Integrated Sapf In a Distribution Systemmentioning

confidence: 99%

TLBO trained an ANN-based DG integrated Shunt Active Power Filter to Improve Power Quality

Venkata Anjani Kumar Gaddam,

Manubolu Damodar Reddy

2024

ARASET

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In terms of power quality, the rising number of nonlinear loads in modern use has caused warning signs for power system and power engineering professionals. Every day, utilities have to deal with harmonic distortion caused by a growing number of non-linear power electronic equipment. To keep the system's power supply in good condition, a shunt active filter is used to filter out unwanted harmonics in the signal. This study presents a practical and low-cost method for reducing harmonics and enhancing distribution network power quality by means of the use of PV-integrated Shunt Active Power Filters (SAPF). With a teaching-learning-based optimized artificial neural network controller (TLBO-ANN) and the required DC power is extracted from the PV module. SAPF's TLBO-ANN algorithms are intended to increase system performance by reducing total harmonic distortion (THD). Here, the research work was performed in three stages to mitigate grid current harmonics. The first-stage SAPF system comprises a three-prong voltage source converter and uses DC power derived from photovoltaic panels. The P&O algorithm is used to get the maximum power out of a photovoltaic array. In the second stage, the BBO algorithm is used to fine-tune a conventional PI controller, resulting in values for and that increase the controller's performance. Furthermore, it is intended to use the BBO-PI controller's input and output values as training data for the ANN controller. This ANN controller is currently being tuned with the TLBO algorithm to find optimal values for the weight and bias parameters. In the third stage, the converter in PV-SAPF will inject the active power required by the load by using active current control theory, which means the inverter of SAPF is working like DG as well as the active power filter. Employing MATLAB simulations, we concluded that the proposed method is extremely adaptable and highly efficient in lowering harmonic currents that are brought on by non-linear loads.

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Section: Fig 1 Pv Integrated Sapf In a Distribution Systemmentioning

confidence: 99%

TLBO trained an ANN-based DG integrated Shunt Active Power Filter to Improve Power Quality

Venkata Anjani Kumar Gaddam,

Manubolu Damodar Reddy

2024

ARASET

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“…Harmonic mitigation is handled by the PI-controllers found in Sinusoidal PQ-theory and PLL circuits, so, the gains of PI-controllers Kp and Ki levels must be carefully optimized. The traditional approach of setting the PI-controller gains requires linear modeling, which results in non-optimal gain tuning [21,22]. For PI-controller tuning, many metaheuristic optimization techniques are applied.…”

Section: Literature Review and Paper Contributionmentioning

confidence: 99%

Dynamic Performance Optimization of Shunt Active Power Filter to Eliminate Total Harmonic Distortion

Eid

Soliman

Mehanna

2023

Journal of Al-Azhar University Engineering Sector

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In this paper, a proposed efficient solution for an important power quality problem focused on harmonic distortion in the source current is introduced by using Shunt Active Power Filter (SAPF) controlled by the sinusoidal source current control strategy which is based on the instantaneous active and reactive power theory (Sinusoidal PQ-theory). As a part of this controller, there is PI-Controller which enhances the APF controller performance when tuning its proportional and integral gains. The gains of the PI-Controller are optimized in this article based on an effective metaheuristic optimization algorithm known as Mayfly Optimization Algorithm (MOA), and its effectiveness is clear when compared with other algorithms such as Particle Swarm Optimization (PSO), Artificial Hummingbird Algorithm (AHA) and Archimedes Optimization Algorithm (AOA). The performance of the optimized controller is evaluated under load variation and distorted source voltage conditions. The results obtained using MATLAB/SIMULINK prove the ability of the MOA to get the optimal PI-Controller gains which lead to enhancement of the APF controller performance to reduce the total harmonic distortion in the drawing source current with minimum and acceptable values according to (IEEE-519) harmonics standard.

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“…The Genetic Algorithms (GAs) technique incorporates fuzzy logic into the power supply current compensation time control via the SAPF controller, with the overall sinusoidal current control strategy (SCC) and total harmonics distortion control (THD) of current and voltage sources [71]. However, the results are limited compared to the method using CIPC; the result for SCC is THD i is 0.41% and THD v is 0.34%, and response time is 0.0032 s compared to for constant when applying GA-Fuzzy is THD i is 0.41% and THD v is 0.62%, and the response time is 0.0040 s [72]. The optimal value of the inductors in the SAPF filter is searched and determined by Gas [73,74].…”

Section: Genetic Algorithms (Gas) Algorithms For Sapfmentioning

confidence: 99%

“…The GAs technique applied to SAPF control in a three-phase PI factor control circuit seeks the optimal value of the dc-link capacitor and the optimal value of the inductor coupling (Figure 6). The processing system depends on the SAPF controller values, which are the dc link capacitor parameter values, the coupled inductor parameter values, the current controller parameter values, and the voltage source of the power circuit [71,72]. Taking a lot of time to process parameter adjustment in SAPF, GAs also has some benefits such as ease of understanding, ease of design and ease of implementation.…”

Section: Genetic Algorithms (Gas) Algorithms For Sapfmentioning

confidence: 99%

Harmonic Mitigation Using Meta-Heuristic Optimization for Shunt Adaptive Power Filters: A Review

Duc,

Hlavaty,

Bilik

et al. 2023

Energies

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Shunt Adaptive Power Filter (SAPF) is widely used in the performance of power quality improvement activities in the power supply industry for processing industries or civil power sources in the world today based on its simplicity, transparency, high reliability, efficiency, and reliability, and their powerful compensating current-providing nature. The PI controller integrated into the SAPF operation mechanism works with extra high efficiency in selecting the current to compensate for the lost current generated in the power supply due to harmonics generated by the parameter values. The system operates by the PWM method for bridge rectifier circuits that perform the function of selecting the appropriate compensating current, providing correct compensation for the amount of current loss in the power supply. Adjusting the parameter to reach the optimal value by different methods is a promising and popular research direction at present. The parameter serves the right purpose for the PI controller to generate enough PWM pulses to excite the bridge rectifiers to generate just the right amount of compensating current and enough current to be compensated on the power supply. The commonly used parameter adjustment methods include the Ziegler Nichols closed-loop vibration method, the P-Q theoretical method, and several other methods. This study conducts a comprehensive review of the literature on modern strategies for adjusting theparameters in the PI controller in the SAPF suite by using the meta-heuristic optimization method. This study performs classification according to the operation mode of meta-heuristic optimization methods to adjust the parameter to control the PI to select the correct PWM frequency to activate bridge rectifiers to select the most optimal compensation current to compensate for the loss of current on the power supply to meet the goal of improving power quality in accordance with IEEE 519-2022 standard, leading to the total harmonic distortion (THD) value is below 5%. The study presents in detail some meta-heuristic optimization algorithms, including applications, mathematical equations, and implementation of flow charts for SAPF and provides some open problems for future research. The main objective of this study is to provide an overview of applying meta-heuristic optimization algorithms to the parameter tuning of PI controllers.

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SAPF Parameter Optimization with the Application of Taguchi SNR Method

Cited by 5 publications

References 15 publications

TLBO trained an ANN-based DG integrated Shunt Active Power Filter to Improve Power Quality

TLBO trained an ANN-based DG integrated Shunt Active Power Filter to Improve Power Quality

Dynamic Performance Optimization of Shunt Active Power Filter to Eliminate Total Harmonic Distortion

Harmonic Mitigation Using Meta-Heuristic Optimization for Shunt Adaptive Power Filters: A Review

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