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Voltage Profile and Sensitivity Analysis for a Grid Connected Solar, Wind and Small Hydro Hybrid System

Author

Listed:
  • Noah Serem

    (African Centre of Excellence in Energy and Sustainable Development, University of Rwanda, Kigali P.O. Box 4285, Rwanda)

  • Lawrence K. Letting

    (Department of Electrical and communications Engineering, School of Engineering, Moi University, Eldoret P.O. Box 3900-30100, Kenya)

  • Josiah Munda

    (Department of Electrical Engineering, Tshwane University of Technology, Pretoria X680-0001, South Africa)

Abstract

Due to increase in integration of renewable energy into the grid and power quality issues arising from it, there is need for analysis and power improvement of such networks. This paper presents voltage profile, Q-V sensitivity analysis and Q-V curves analysis for a grid that is highly penetrated by renewable energy sources; solar PV, wind power and small hydro systems. Analysis is done on IEEE 39 bus test system with Wind power injection alone, PV power injection alone, with PV and wind power injection and with PV, wind and micro hydro power injection to the grid. The analysis is used to determine the buses where voltage stability improvement is needed. From the results, it was concluded that injection of the modeled wind power alone helped in stabilizing the voltage levels as determined from voltage profiles and reactive power margins. Replacing some of the conventional sources with PV power led to reduction of voltages for weak buses below the required standards. Injection of power from more than one renewable energy source helped in slightly improving the voltage levels. Distribution Static compensators (D-STATCOMs) were used to improve the voltage levels of the buses that were below the required standards.

Suggested Citation

  • Noah Serem & Lawrence K. Letting & Josiah Munda, 2021. "Voltage Profile and Sensitivity Analysis for a Grid Connected Solar, Wind and Small Hydro Hybrid System," Energies, MDPI, vol. 14(12), pages 1-26, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3555-:d:575219
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    Citations

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    Cited by:

    1. B. Koti Reddy & Amit Kumar Singh, 2021. "Optimal Operation of a Photovoltaic Integrated Captive Cogeneration Plant with a Utility Grid Using Optimization and Machine Learning Prediction Methods," Energies, MDPI, vol. 14(16), pages 1-28, August.
    2. Tianyao Zhang & Weibin Huang & Shijun Chen & Yanmei Zhu & Fuxing Kang & Yerong Zhou & Guangwen Ma, 2023. "The Scheduling Research of a Wind-Solar-Hydro Hybrid System Based on a Sand-Table Deduction Model at Ultra-Short-Term Scales," Energies, MDPI, vol. 16(7), pages 1-18, April.
    3. Yih-Der Lee & Wei-Chen Lin & Jheng-Lun Jiang & Jia-Hao Cai & Wei-Tzer Huang & Kai-Chao Yao, 2021. "Optimal Individual Phase Voltage Regulation Strategies in Active Distribution Networks with High PV Penetration Using the Sparrow Search Algorithm," Energies, MDPI, vol. 14(24), pages 1-22, December.
    4. Joanna Rosak-Szyrocka & Justyna Żywiołek & Maciej Mrowiec, 2022. "Analysis of Customer Satisfaction with the Quality of Energy Market Services in Poland," Energies, MDPI, vol. 15(10), pages 1-24, May.
    5. Raavi Satish & Kanchapogu Vaisakh & Almoataz Y. Abdelaziz & Adel El-Shahat, 2021. "A Novel Three-Phase Power Flow Algorithm for the Evaluation of the Impact of Renewable Energy Sources and D-STATCOM Devices on Unbalanced Radial Distribution Networks," Energies, MDPI, vol. 14(19), pages 1-21, September.

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