Power Quality Assessment of Perturbed Power System Implementing Fuzzy Logic and Discrete Wavelet Transform
S.Mishra1, S.C.Swain2, P.Sinha3, A.Pradhan4, L.Nanda5
1Dr. Sarat Ch.Swain, Professor, School of Electrical Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India.
2Sanhita Mishra, Assistant Professor, KIIT Deemed to be University, Bhubaneswar, Odisha, India.
3Dr Pampa Sinha, Assistant Professor, KIIT University, Bhubaneswar, Odisha, India.
4Dr. Arjyadhara Pradhan, Assistant Professor, School of Electrical Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India.
Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 4711-4717 | Volume-9 Issue-1, November 2019. | Retrieval Number: A5037119119/2019©BEIESP | DOI: 10.35940/ijitee.A5037.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A novel power quality index (PQI) is determined in this paper which helps in determining the power quality under non-sinusoidal condition. Power quality monitoring is important due to exponential growth of non linear loads in electric power system. As non linear loads creates the distortion level in distribution system so it is highly necessary to measure power quality index. The innovative power quality index has been found out by considering three component such as Representative quality factor(RQPF), Detailed pollution factor(DPF), Total harmonic Distortion(THD). When total harmonic distortion of voltage(THDV) and Total harmonic distortion of current(THDI ) amalgamation occur then THD has been formed using fuzzy inference system. An experimental model has been developed to verify the PQI under different cases by measuring voltage and current both on the source side and utility side . The measured voltage and current are reformulated as wavelet function using discrete wavelet transform (DWT) to calculate referred power quality factors . This new power quality index has been validated through hardware model to justify its importance under different non-sinusoidal conditions.
Keywords: Fuzzy Inference System, Power Quality Index, Total Harmonic Distortion Wavelet Packet Transform
Scope of the Article: Fuzzy Logics