Power Quality and Enhancement Techniques: Research Gaps and Current Trends

Sandhya, P; R*, Nagaraj

doi:10.35940/ijitee.b7025.129219

Cited by 3 publications

(1 citation statement)

References 26 publications

(52 reference statements)

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“…Pedepenki et al [21], [22] present a neuro fuzzy-based controlling mechanism for H-APF, which is compared with the conventional PI-based controller with THD improvements. Sandhya and Nagaraj [23] discuss the contribution to the study of power quality enhancement and various aspects of power quality and current trends. Sahu and Mahapatra [24] present all-on-chip-based distribution static synchronous compensator (DSTATCOM) control-based power quality improvement using virtex-5 field-programmable gate array (FPGA).…”

Section: Review On Related Researchmentioning

confidence: 99%

Modeling of hybrid active power filter using artificial intelligence controller: hardware and software prospective

Sandhya¹,

Nagaraj

2021

IJPEDS

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<span lang="EN-US">The power factor is a significant concern in power systems. The significant power loss occurred due to electronic and electrical equipment damages affected by the deviation of physical characteristics, including voltage, current, and frequency parameters.The power loss and quality issues were resolved by introducing filtering techniques in electronic and electrical equipment. Many filtering techniques include passive filtering (PF), Active power filter (APF), and many hybrid approaches are already available. Most of these methods use proper compensation controlling approaches and failed to minimize the total harmonic distortion (THD), and harmonic mitigation in power systems has its best. In this article, an efficient Hybrid-APF using Artificial-Neuro Fuzzy interface system (ANFIS) for software and hardware perspective is designed. The proposed approach uses hybrid controlling strategies which include PI with artificial intelligence (ANFIS) controller, to control the power losses for H-APF. Additionally, current compensation is achieved by PQ-theory, followed by Hysteresis-Current- Controller (HCC). The hardware architecture of ANFIS with HCC is designed to improve the chip-area for real-time power applications.The present work analyzed by simulating the voltage and current waveform. The proposed-H-APF using ANFIS controller, both software and hardware approaches, is compared with other control techniques like H-APF with PI and Fuzzy logic controller by concerning THD,Reactive power, and Different Harmonics and loads improvements.</span>

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Section: Review On Related Researchmentioning

confidence: 99%

Modeling of hybrid active power filter using artificial intelligence controller: hardware and software prospective

Sandhya¹,

Nagaraj

2021

IJPEDS

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Power Quality Improvement in Wind, Solar, and DG Based Islanded Microgrid by using DVR

Yadav

Singh

Yadav

et al. 2022

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)

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A comparative study of fuzzy logic based UPQC and D-STATCOM for mitigation of power quality problem

Yisfalem,

Yeshitela

2024

JPS

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This paper begins by investigating a power quality problem in the case study area using monthly energy consumption data, the peak and minimum load of the substation, a fault summary, and the RMS voltage profile of the case study area. The content of the paper comprises three parts: the first involves MATLAB design and simulation of D-STATCOM with a fuzzy logic controller for the selected case study area. The second part entails MATLAB design and simulation of the DVR with a fuzzy logic controller. The final part presents a hybrid of the DVR and the D-STATCOM back-to-back using a DC link capacitor to implement a more recent and effective power quality improvement technique, namely UPQC. In the case of a three-phase fault, the voltage sag in the case study area is 0.6PU, with the remaining 0.4PU drop-down voltage requiring injection using the proposed FACT device for compensation. All proposed power quality problem mitigation techniques inject the required voltage and compensate for the voltage sag in the substation. For instance, D-STATCOM compensates the RMS voltage from 9KV to 14KV, DVR compensates the RMS voltage from 9KV to 14.7 KV, and UPQC compensates the value to 14.9KV. Due to the three-phase fault, the rise in reactive power of the existing outgoing feeder is 13MW. This unexpected rise in reactive power is reduced to 2.6 MW using D-STATCOM, DVR reduces it to 1.2 MW, and UPQC reduces the value below 1MW. The existing power factor of the case study area without any mitigation technique is 0.68. All proposed techniques improve the existing power factor to a more acceptable value. For instance, D-STATCOM improves the power factor from 0.68 to 0.83, DVR improves the value to 0.88, and UPQC, the more accurate power quality mitigation technique, improves the power factor to 0.93. Finally, the results are compared based on the simulation results.

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Power Quality and Enhancement Techniques: Research Gaps and Current Trends

Cited by 3 publications

References 26 publications

Modeling of hybrid active power filter using artificial intelligence controller: hardware and software prospective

Modeling of hybrid active power filter using artificial intelligence controller: hardware and software prospective

Power Quality Improvement in Wind, Solar, and DG Based Islanded Microgrid by using DVR

A comparative study of fuzzy logic based UPQC and D-STATCOM for mitigation of power quality problem

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