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Power quality recognition in distribution system with solar energy penetration using S-transform and Fuzzy C-means clustering

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  • Mahela, Om Prakash
  • Shaik, Abdul Gafoor

Abstract

This paper presents a technique to recognize the power quality (PQ) disturbances associated with solar energy penetration in distribution network. The voltage signal is analysed with the help of Stockwell's transform (S-transform) then its features are utilized to recognize power quality events with the help of Fuzzy C-means clustering (FCM). The operations considered for PQ assessment include grid synchronization and outage of solar photovoltaic (PV) system. The PQ events associated with sudden change in solar insolation have also been investigated. The proposed study is carried out using a standard IEEE-13 bus test system modified by incorporating the solar PV system. The effect of increase in solar energy penetration in terms of power quality assessment has also been investigated with solar PV systems of capacities 100kW, 500kW and 1MW using the proposed power quality index, maximum deviations in frequency and total harmonics distortions of voltage and current. The study has been carried out using MATLAB/Simulink and simulation results are compared with the real time results obtained using real time digital simulator (RTDS) for validating the effectiveness of proposed study.

Suggested Citation

  • Mahela, Om Prakash & Shaik, Abdul Gafoor, 2017. "Power quality recognition in distribution system with solar energy penetration using S-transform and Fuzzy C-means clustering," Renewable Energy, Elsevier, vol. 106(C), pages 37-51.
    • Handle: RePEc:eee:renene:v:106:y:2017:i:c:p:37-51
    DOI: 10.1016/j.renene.2016.12.098
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    References listed on IDEAS

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    1. Ram, J. Prasanth & Babu, T. Sudhakar & Rajasekar, N., 2017. "A comprehensive review on solar PV maximum power point tracking techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 826-847.
    2. Rampinelli, Giuliano A. & Gasparin, Fabiano P. & Bühler, Alexandre J. & Krenzinger, Arno & Chenlo Romero, Faustino, 2015. "Assessment and mathematical modeling of energy quality parameters of grid connected photovoltaic inverters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 133-141.
    3. Mahela, Om Prakash & Shaik, Abdul Gafoor & Gupta, Neeraj, 2015. "A critical review of detection and classification of power quality events," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 495-505.
    4. Mahela, Om Prakash & Shaik, Abdul Gafoor, 2017. "Comprehensive overview of grid interfaced solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 316-332.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Atul Kulshrestha & Om Prakash Mahela & Mukesh Kumar Gupta & Neeraj Gupta & Nilesh Patel & Tomonobu Senjyu & Mir Sayed Shah Danish & Mahdi Khosravy, 2020. "A Hybrid Fault Recognition Algorithm Using Stockwell Transform and Wigner Distribution Function for Power System Network with Solar Energy Penetration," Energies, MDPI, vol. 13(14), pages 1-25, July.
    2. Michał Jasiński & Tomasz Sikorski & Paweł Kostyła & Zbigniew Leonowicz & Klaudiusz Borkowski, 2020. "Combined Cluster Analysis and Global Power Quality Indices for the Qualitative Assessment of the Time-Varying Condition of Power Quality in an Electrical Power Network with Distributed Generation," Energies, MDPI, vol. 13(8), pages 1-21, April.
    3. Li, Yang & Wang, Jinlong & Zhao, Dongbo & Li, Guoqing & Chen, Chen, 2018. "A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making," Energy, Elsevier, vol. 162(C), pages 237-254.
    4. Igual, R. & Medrano, C., 2020. "Research challenges in real-time classification of power quality disturbances applicable to microgrids: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    5. Li, Yang & Li, Yahui & Li, Guoqing & Zhao, Dongbo & Chen, Chen, 2018. "Two-stage multi-objective OPF for AC/DC grids with VSC-HVDC: Incorporating decisions analysis into optimization process," Energy, Elsevier, vol. 147(C), pages 286-296.
    6. Tut Haklıdır, Füsun S., 2020. "The importance of long-term well management in geothermal power systems using fuzzy control: A Western Anatolia (Turkey) case study," Energy, Elsevier, vol. 213(C).
    7. Khosravi, Nima, 2025. "Enhancing operational efficiency through a control-based approach for hydrogen and battery energy storage systems integration in renewable energy networks," Renewable Energy, Elsevier, vol. 248(C).
    8. Govind Sahay Yogee & Om Prakash Mahela & Kapil Dev Kansal & Baseem Khan & Rajendra Mahla & Hassan Haes Alhelou & Pierluigi Siano, 2020. "An Algorithm for Recognition of Fault Conditions in the Utility Grid with Renewable Energy Penetration," Energies, MDPI, vol. 13(9), pages 1-22, May.
    9. Sheesh Ram Ola & Amit Saraswat & Sunil Kumar Goyal & Virendra Sharma & Baseem Khan & Om Prakash Mahela & Hassan Haes Alhelou & Pierluigi Siano, 2020. "Alienation Coefficient and Wigner Distribution Function Based Protection Scheme for Hybrid Power System Network with Renewable Energy Penetration," Energies, MDPI, vol. 13(5), pages 1-25, March.

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