Impact of Renewable Sources on Electrical Power System

Document Type : Research paper

Authors

1 Department of EEE, VLITS, Vadlamudi, Guntur. Dt, AP 522213, India

2 Department of EEE, VVIT, Nambur, Guntur. Dt, AP 522508, India

3 EEE Department, UCEK, JNTUK, Kakinada, E.G.Dt, AP 533003, India

Abstract

In this paper, Renewable energy sources (RES) are incorporated into the electricity grid. A real-time Andhra Pradesh 14 bus system is considered in which, windy and sunny locations are identified for this study. A new algorithm called Persistence - Extreme Learning Machine (P-ELM) is suggested. The suggested methodology is used to predict wind speed and solar insolation in the selected regions across the short-term and long-term time period horizons. The load flow problem is handled in 12 distinct by penetrating the wind and solar power into the system. The research findings are examined in terms of voltage variation and active power loss. The results obtained observed as, with wind and solar integration, the voltage variation is higher in both the short and long-term time frames, but the active power losses are lower than in the other cases.

Keywords

References

  1. R. Bergen, V. Vittal, Power Systems Analysis. Pearson/Prentice Hall, 2000.
  2. D. Glover, T. Overbye, M.S. Sarma, Power System Analysis and Design. 2016 Cengage Learning.
  3. Heydt, S. Oren, M. Ilic, P. Sen, T. Mount, S. Meliopoulos, J. Momoh, P. Sauer, J. McCalley, M. Kezunovic, and A. Bose, Challenges in Integrating Renewable Technologies into an Electric Power System. 2010, PSERC Executive Committee, PSERC Document.
  4. Subramani, C. Vijayalakshmi, “Design and analysis of Lagrangian algorithm for power flow system using renewable energy resources”, Indonesian J. Electr. Eng. Computer Sci., vol. 7, no. 2, pp. 348–355, 2017.
  5. D. Le, N.T.A. Nguyen, V.D. Ngo, Alberto Berizzi, “Advanced probabilistic power ow methodology for power systems with renewable resources”, Turkish J. Electri. Eng. Comput. Sci., vol. 25, no. 2, pp.1154–1162, 2017.
  6. Muruganantham, R. Gnanadass, N.P. Padhy, “Unbalanced load flow analysis for distribution network with solar PV integration”, in National Power Sys. Conf. (NPSC), Bhubaneswar, India, pp. 19–21, 2016.
  7. R. Kumar, A. Jain, “A load flow algorithm for radial systems having renewable energy generation sources”, in 7th Int. Con. Info. Autom. Sustainability (ICIAS), 2014, Colombo, Sri Lanka, 2014.
  8. Nikmehr and S. Najafi Ravadanegh, “Solving probabilistic load flow in smart distribution grids using heuristic methods”, J. Renewable Sustainable Energy, vol. 7, no. 4, pp. 1–15, 2015.
  9. Moriarty, D. Honner, “Feasibility of a 100% global renewable energy system”, Energies, vol. 13, no. 21, pp. 1–16, 2020.
  10. R. Gomaa, H. Rezk, R.J. Mustafa, M. Al-Dhaifalla, “Evaluating the environmental impacts and energy performance of a wind farm system utilizing the lifecycle assessment method: A practical case study”, Energies, vol. 12, pp. 1–25, 2019.
  11. Sohani, M.H. Shahverdian, H. Sayyaadi, S. Hoseinzadeh, S. Memon, “Enhancing the renewable energy payback period of a photovoltaic power generation system by water flow cooling”, Int. J. Solar Therm. Vac. Eng., vol. 3, pp. 73-85, 2021.
  12. W. Chisale, P. Mangani, “Energy audit and feasibility of solar PV energy system: case of a commercial building”, J. Energy, vol. 2021, pp. 1–9, 2021.
  13. R. Behnamfar, H. Barati and M. Karami, "Antlion optimization algorithm for optimal self-scheduling unit commitment in power system under uncertainties", J. Oper. Auto. Power Eng., vol. 9, no. 3, pp: 226–241, 2021.
  14. Ghaedi, H. Gorginpour and E. Noroozi, "Operation studies of the power systems containing combined heat and power plants," J. Oper. Auto. Power Eng., vol. 9, No.2, pp. 160–171, 2021.
  15. Zhang, Y. Wei, Z. Tan, W. Ke and W. Tian, “A hybrid method for short-term wind speed forecasting”, Sustainability, vol. 9, no. 4, pp. 1–10, 2017.
  16. V. Lahari and H.V.K. Shetty, “Integration of grid connected PMG wind energy and solar energy systems using different control strategies”, in “Int. Conf. Power Adv. Control Eng. (ICPACE),” 2015, pp. 23–27.
  17. Roberto Cardenas, Marcelo A. Perez, Jon C. Clare, “Control and grid integration of MW-range wind and solar energy conversion systems”, IEEE Trans. Ind. Electron., vol. 64, no. 11, pp. 8786–8789, 2017.
  18. Peng, J. Zou, Z. Zhang, L. Han, M. Liu, “An ultra-shortterm pre-plan power curve based smoothing control approach for grid-connected wind-solar-battery hybrid power system”, IFAC papers online, vol. 50, no 1, pp. 7711–7716, 2017.
  19. E. Lotfy, T. Senjyu, M.A. Farahat, A.F. Abdel-Gawad, L. Lei and M. Datta, “Hybrid genetic algorithm fuzzy-based control schemes for small power system with high-penetration wind farms”, Appl. sci., vol. 8, no. 3, pp. 1–20, 2018.
  20. Sekar, V Duraisamy, “Efficient energy management system for integrated renewable power generation system”, J. sci. Ind. research, vol. 74, pp. 325 – 329, 2015.
  21. Ackermann, Wind power in power systems. 2nd Ed., 2012, John Willey & Sons Ltd.
  22. R. Patel, Wind and Solar Power Systems: Design, Analysis, and Operation. 2nd Ed., 2005, U.S. Merchant Marine Academy Kings Point, New York, CRC Press.
  23. Khaligh, O.C. Onar, Energy Harvesting: Solar, Wind, and Ocean Energy Conversion Systems. 2017, CRC Press.
  24. S. Syed, C.V. Suresh and S. Sivanagaraju, “Optimal Power Flow Solution in the Presence of Renewable Energy Sources,” Iranian J. Sci. Technol. Trans. Electr. Engi., vol. 45, no. 1, pp. 61-79, 2021.
  25. S. Syed, C.V. Suresh and S. Sivanagaraju, “Short term solar insolation prediction: P-ELM approach,” International Journal of parallel, emergent and distributes system, vol. 33, no. 6. pp. 663-674, 2017.
Journal of Operation and Automation in Power Engineering
Volume 12, Issue 3
August 2024
Pages 261-268

Files

History

  • Receive Date: 03 February 2022
  • Revise Date: 18 January 2023
  • Accept Date: 10 February 2023
  • First Publish Date: 18 June 2023

Share

How to cite

Statistics