Document Type : Research paper

Authors

1 Department of Electrical Engineering, Dariun Branch, Islamic Azad University, Dariun, Iran.

2 Department of Electrical Engineering, Beyza Branch, Islamic Azad University, Beyza, Iran.

3 Department of Electrical Engineering, Apadana Institute of Higher Education, Shiraz, Iran.

Abstract

In many different nations around the world, renewable energy sources are increasingly being used to generate electricity. It is because renewable resources are sustainable, have no operating costs, and are environmentally friendly. Wind power develops quickly among renewable units, and nowadays, several wind farms with large installed capacity are operating in the world. However, the erratic property of wind velocity causes generated power of wind parks to vary, which has an impact on various parts of electric network connected to wind parks and needs to be studied using new methods. In order to address reliability-based operation studies of electric network in presence of wind parks, the current research suggests a method taking into account both probabilistic and deterministic approaches for reserve scheduling. The PJM method has been modified for this reason, for incorporating wind production into the electric network. For wind farms, a several-state reliability presentation that considers hazard of assembled elements and change in produced power is developed at first stage. The appropriate amount of spinning reserve is then computed using matrix multiplication method through modified PJM methodology. Numerical simulations related to reliability test networks are provided for assessing efficacy of suggested methodology. It is concluded from numerical outcomes that the wind farms lead to the reduction of required spinning reserve. However, due to the variation of output power of wind farms arisen from variation of wind velocity, the impact of wind units in reduction of spinning reserve is less than the conventional units with the same capacity. Besides, spinning reserve calculated by well-being approach of wind farms that combines the probabilistic and deterministic indices is more accurate than the value obtained by risk indices.

Keywords

Main Subjects

  1. L. Hao, J. Ji, D. Xie, H. Wang, W. Li, and P. Asaah, “Scenario-based unit commitment optimization for power system with large-scale wind power participating in primary frequency regulation,” J. Mod. Power Syst. Clean Energy, vol. 8, no. 6, pp. 1259–1267, 2020.
  2. O. A. Ansari, Y. Gong, W. Liu, and C. Y. Chung, “Data-driven operation risk assessment of wind-integrated power systems via mixture models and importance sampling,” J. Mod. Power Syst. Clean Energy, vol. 8, no. 3, pp. 437–445, 2020.
  3. Q. Yao, J. Liu, and Y. Hu, “Optimized active power dispatching strategy considering fatigue load of wind turbines during de-loading operation,” IEEE Access, vol. 7, pp. 17439– 17449, 2019.
  4. K. Das, F. Guo, E. Nuño, and N. A. Cutululis, “Frequency stability of power system with large share of wind power under storm conditions,” J. Mod. Power Syst. Clean Energy, vol. 8, no. 2, pp. 219–228, 2020.
  5. S. Xia, Z. Ding, T. Du, D. Zhang, M. Shahidehpour, and T. Ding, “Multitime scale coordinated scheduling for the combined system of wind power, photovoltaic, thermal generator, hydro pumped storage, and batteries,” IEEE Trans. Ind. Appl., vol. 56, no. 3, pp. 2227–2237, 2020.
  6. J. Zhao, Y. Ma, Q. Liu, L. Wen, C. Jia, and Y. Fang, “A multi-source coordinated optimal operation model considering the risk of nuclear power peak shaving and wind power consumption,” IEEE Access, vol. 8, pp. 189702–189719, 2020.
  7. Z. Zhou, L. Ge, et al., “Operation of stand-alone microgrids considering the load following of biomass power plants and the power curtailment control optimization of wind turbines,” IEEE Access, vol. 7, pp. 186115–186125, 2019.
  8. A. Cerejo, S. J. Mariano, P. M. Carvalho, and M. R. Calado, “Hydro-wind optimal operation for joint bidding in day-ahead market: storage efficiency and impact of wind forecasting uncertainty,” J. Mod. Power Syst. Clean Energy, vol. 8, no. 1, pp. 142–149, 2019.
  9. X. Yang, Y. Yang, Y. Liu, and Z. Deng, “A reliability assessment approach for electric power systems considering wind power uncertainty,” IEEE Access, vol. 8, pp. 12467– 12478, 2020.
  10. L. Ma, Z. Wang, Z. Lu, X. Lu, and F. Wan, “Integrated strategy of the output planning and economic operation of the combined system of wind turbines-pumped-storage-thermal power units,” IEEE Access, vol. 7, pp. 20567–20576, 2019.
  11. F. Babaei, A. Safari, J. Salehi, and H. Shayeghi, “Static security assessment of integrated power systems with wind farms using complex network theory,” J. Oper. Autom. Power Eng., 2023.
  12. M. Behnamfar and M. Abasi, “Uncertainty management in short-term self-scheduling unit commitment using harris hawks optimization algorithm,” J. Oper. Autom. Power Eng., vol. 12, no. 4, pp. 280–295, 2024.
  13. A. Ghaedi, M. Mahmoudian, and R. Sedaghati, “Reliability analysis of power system considering renewable resources, chp units, energy storage devices and demand response program,” J. Oper. Autom. Power Eng., 2023.
  14. A. Ghaedi, H. Gorginpour, and E. Noroozi, “Operation studies of the power systems containing combined heat and power plants,” J. Oper. Autom. Power Eng., vol. 9, no. 2, pp. 160–171, 2021.
  15. H. Li and Z. Chen, “Overview of different wind generator systems and their comparisons,” IET Renewable Power Gener., vol. 2, no. 2, pp. 123–138, 2008.
  16. A. Ghaedi, A. Abbaspour, M. Fotuhi-Firuzabad, and M. Moeini-Aghtaie, “Toward a comprehensive model of large-scale dfig-based wind farms in adequacy assessment of power systems,” IEEE Trans. Sustainable Energy, vol. 5, no. 1, pp. 55–63, 2013.
  17. M. Mirzadeh, M. Simab, and A. Ghaedi, “Reliability modeling of reservoir-based tidal power plants for determination of spinning reserve in renewable energy-based power systems,” Electr. Power Compon. Syst., vol. 47, no. 16-17, pp. 1534– 1550, 2019.
  18. “The Wind speed historical statistics in IRAN [Online], howpublished = https://www.satba.gov.ir/, note = Accessed:.”
  19. R. Billinton and R. N. Allan, Reliability assessment of large electric power systems. Springer Science & Business Media, 2012.
  20. R. Billinton and S. Jonnavithula, “A test system for teaching overall power system reliability assessment,” IEEE Trans. Power Syst., vol. 11, no. 4, pp. 1670–1676, 1996.
  21. C. Grigg, P. Wong, P. Albrecht, R. Allan, M. Bhavaraju, R. Billinton, Q. Chen, C. Fong, S. Haddad, S. Kuruganty, et al., “The ieee reliability test system-1996. a report prepared by the reliability test system task force of the application of probability methods subcommittee,” IEEE Trans. Power Syst., vol. 14, no. 3, pp. 1010–1020, 1999.