Reliability Analysis of Power System Considering Renewable Resources, CHP Units, Energy Storage Devices and Demand Response Program

Document Type : Research paper

Authors

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

2 Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran

3 Department of Electrical Engineering, Beyza Branch, Islamic Azad University, Beyza, Iran

Abstract

In recent years, due to rising social welfare, the reliability has become one of most important topics of modern power network and electricity companies try to provide the electric power to the consumers with minimal interruptions. For this purpose, the electricity companies to improve the reliability of the power system can utilize different techniques. In this paper, new developments occurred in electricity industry including integration of large-scale renewable resources, integration of large capacity energy storage systems, integration of combined heat and electricity units into power network and demand side response plans are taken into account, and these events impact on power network reliability is assessed. Power networks are affected with integration of renewable resources. Multi-state reliability models for renewable generation plants are obtained, in the paper. Suitable number of states in the proposed reliability model is selected by calculating XB index. Besides, fuzzy c-means clustering approach is utilized for determining probability of states. For study impact of energy storage systems with large capacity on power network reliability, load model is modified. To investigate effect of combined heat and power plants on power network reliability, failure of composed elements and produced thermal power are considered in reliability model of these plants. To evaluate demand side response impact on reliability of power network, the load model is modified. The effectiveness of the proposed techniques on the reliability enhancement of power network is satisfied using numerical results performed on reliability test systems based on the suggested methods.

Keywords

Main Subjects

References

  1. Fan, K. Sun, D. Lane, W. Gu, Z. Li, and F. Zhang, “A novel generation rescheduling algorithm to improve power system reliability with high renewable energy penetration,” IEEE Trans. Power Syst., vol. 33, no. 3, pp. 3349–3357, 2018.
  2. Kumar, R. Saket, D. K. Dheer, J. B. Holm-Nielsen, and P. Sanjeevikumar, “Reliability enhancement of electrical power system including impacts of renewable energy sources: a comprehensive review,” IET Gener. Transm. Distrib., vol. 14, no. 10, pp. 1799–1815, 2020.
  3. Gao and R. Billinton, “Adequacy assessment of generating systems containing wind power considering wind speed correlation,” IET Renewable Power Gener., vol. 3, no. 2, pp. 217–226, 2009.
  4. A. Ansari, N. Safari, and C. Chung, “Reliability assessment of microgrid with renewable generation and prioritized loads,” in 2016 IEEE Green Energy Syst. Conf. (IGSEC), pp. 1–6, IEEE, 2016.
  5. Billinton et al., “Impacts of energy storage on power system reliability performance,” in Can. Conf. Electr. Comput. Eng., 2005., pp. 494–497, IEEE, 2005.
  6. I. A. Raihan, “Impact of energy storage devices on reliability of distribution system,” in 2016 2nd Int. Conf. Electr. Comput. Telecommun. Eng. (ICECTE), pp. 1–4, IEEE, 2016.
  7. Xu and C. Singh, “Adequacy and economy analysis of distribution systems integrated with electric energy storage and renewable energy resources,” IEEE Trans. power syst., vol. 27, no. 4, pp. 2332–2341, 2012.
  8. R. Tur, “Reliability assessment of distribution power system when considering energy storage configuration technique,” IEEE Access, vol. 8, pp. 77962–77971, 2020.
  9. Ol,ekšijs and O. Linkevics, “Failure simulation model forĖ‡ evaluation of chp electrical equipment reliability,” in 57th Int. Sci. Conf. Power Electr. Eng. Riga Tech. Uni. (RTUCON), pp. 1–4, IEEE, 2016.
  10. Pazouki, A. Mohsenzadeh, S. Ardalan, and M.-R. Haghifam, “Optimal place, size, and operation of combined heat and power in multi carrier energy networks considering network reliability, power loss, and voltage profile,” IET Gener. Transm. Distrib., vol. 10, no. 7, pp. 1615–1621, 2016.
  11. Qi, Z. Ji, H. Wu, J. Zhang, and L. Wang, “Shortterm reliability assessment of generating systems considering demand response reliability,” IEEE Access, vol. 8, pp. 74371– 74384, 2020.
  12. Kamruzzarnan and M. Benidris, “Demand response based power system reliability enhancement,” in IEEE Int. Conf. Probab. Methods Appl. Power Syst. (PMAPS), pp. 1–6, IEEE, 2018.
  13. Mosayebian, “A new approach for modeling wind power in reliability studies,” J. Oper. Autom. Power Eng., vol. 11, no. 2, pp. 144–150, 2023.
  14. 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. Kumar, S. Dahiya, and K. Singh Parmar, “Multi-objective economic emission dispatch optimization strategy considering battery energy storage system in islanded microgrid,” J. Oper. Autom. Power Eng., 2023.
  16. Baherifard, R. Kazemzadeh, A. Yazdankhah, and M. Marzband, “Improving the effect of electric vehicle charging on imbalance index in the unbalanced distribution network using demand response considering data mining techniques,” J. Oper. Autom. Power Eng., vol. 11, no. 3, pp. 182–192, 2023.
  17. Benyaghoob Sani, M. Sedighizadeh, D. Sedighizadeh, and R. Abbasi, “Risk averse optimal operation of coastal energy hub considering seawater desalination and energy storage systems,” J. Oper. Autom. Power Eng., vol. 10, no. 2, pp. 90–104, 2022.
  18. Salehi, F. Gazijahani, and A. Safari, “Stochastic simultaneous planning of interruptible loads, renewable generations and capacitors in distribution network,” J. Oper. Autom. Power Eng., vol. 10, no. 2, pp. 113–121, 2022.
  19. Naderi, A. Dejamkhooy, S. Seyedshenava, and H. Shayeghi, “Milp based optimal design of hybrid microgrid by considering statistical wind estimation and demand response,” J. Oper. Autom. Power Eng., vol. 10, no. 1, pp. 54–65, 2022.
  20. Shayeghi and M. Alilou, “Multi-objective demand side management to improve economic and environmental issues of a smart microgrid,” J. Oper. Autom. Power Eng., vol. 9, no. 3, pp. 182–192, 2021.
  21. B. Shahmars, J. Salehi, and N. T. Kalantari, “Bi-level unit commitment considering virtual power plants and demand response programs using information gap decision theory,” J. Oper. Autom. Power Eng., vol. 9, no. 2, pp. 88–102, 2021.
  22. Halve, A. Koshti, and R. Arya, “A sampling method based on system state transition for distribution system adequacy assessment using distributed generation,” J. Oper. Autom. Power Eng., vol. 11, no. 4, pp. 249–257, 2023.
  23. Shahbazi, H. Moradi CheshmehBeigi, H. Abdi, and M. Shahbazitabar, “Probabilistic optimal allocation of electricvehicle charging stations considering the uncertain loads by using the monte carlo simulation method,” J. Oper. Autom. Power Eng., vol. 11, no. 4, pp. 277–284, 2023.
  24. Afraz, B. Rezaeealam, S. SeyedShenava, and M. Doostizadeh, “Generation scheduling of active distributionnetwork with renewable energy resources considering demand response management,” J. Oper. Autom. Power Eng., vol. 9, no. 2, pp. 132–143, 2021.
  25. N. Allan et al., Reliability evaluation of power systems. Springer Science & Business Media, 2013.
  26. Tang, F. Sun, and Z. Sun, “Improved validation index for fuzzy clustering,” in Proc. Am. Cont. Conf., 2005., pp. 1120–1125, IEEE, 2005.
  27. Nayak, B. Naik, and H. Behera, “Fuzzy c-means (fcm) clustering algorithm: a decade review from 2000 to 2014,” in Comput. Intell. Data Min.-Vol. 2: Proc. Int. Conf. CIDM, 20-21 December 2014, pp. 133–149, Springer, 2015.
  28. Billinton and D. Huang, “Test systems for reliability and adequacy assessment of electric power systems,” Proc. IEEE Gen. Meet.(PES), pp. 8–14, 2015.
  29. Barrows, A. Bloom, A. Ehlen, J. Ikäheimo, J. Jorgenson, D. Krishnamurthy, J. Lau, B. McBennett, M. O’Connell, D. Preston, “The ieee reliability test system: A proposed 2019 update,” IEEE Trans. Power Syst., vol. 35, no. 1, pp. 119–127, 2019.
Journal of Operation and Automation in Power Engineering
Volume 13, Issue 2
2025
Pages 157-164

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History

  • Receive Date: 07 February 2023
  • Revise Date: 24 May 2023
  • Accept Date: 26 May 2023
  • First Publish Date: 08 November 2023

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