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Babaei, Farshad, Safari, Amin, Salehi, Javad, Shayeghi, Hossein. (1404). Static Security Assessment of Integrated Power Systems with Wind Farms Using Complex Network Theory. سامانه مدیریت نشریات علمی, 13(2), 165-173. doi: 10.22098/joape.2023.13644.2044
Farshad Babaei; Amin Safari; Javad Salehi; Hossein Shayeghi. "Static Security Assessment of Integrated Power Systems with Wind Farms Using Complex Network Theory". سامانه مدیریت نشریات علمی, 13, 2, 1404, 165-173. doi: 10.22098/joape.2023.13644.2044
Babaei, Farshad, Safari, Amin, Salehi, Javad, Shayeghi, Hossein. (1404). 'Static Security Assessment of Integrated Power Systems with Wind Farms Using Complex Network Theory', سامانه مدیریت نشریات علمی, 13(2), pp. 165-173. doi: 10.22098/joape.2023.13644.2044
Babaei, Farshad, Safari, Amin, Salehi, Javad, Shayeghi, Hossein. Static Security Assessment of Integrated Power Systems with Wind Farms Using Complex Network Theory. سامانه مدیریت نشریات علمی, 1404; 13(2): 165-173. doi: 10.22098/joape.2023.13644.2044

Static Security Assessment of Integrated Power Systems with Wind Farms Using Complex Network Theory

Journal of Operation and Automation in Power Engineering
مقاله 7، دوره 13، شماره 2، 2025، صفحه 165-173    اصل مقاله (851.33 K)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2023.13644.2044
نویسندگان
Farshad Babaei1؛ Amin Safari* 1؛ Javad Salehi1؛ Hossein Shayeghi2
1Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran.
2Department of Electrical Engineering, University of Mohaghegh Ardabili, Ardabil, Iran.
چکیده
Although the presence of clean energy resources in power systems is required to reduce greenhouse gas emissions, system security faces severe challenges due to its increased intelligence and expansion, as well as the high penetration of renewable energy resources. According to new operating policies, power systems should withstand subsequent single contingencies. Also, the effect of electrical and structural characteristics must be considered in power system security assessment. Thus, this paper introduces a comprehensive risk-based approach that quantifies the impact of contingency-induced variation in topology by using complex network theory metrics. Then, it identifies elements that surpass security limitations and eliminates them to execute cascading outage analysis via AC power flow. Lastly, wind power uncertainty and contingency probability are multiplied by the linear combination of electrical and structural consequences, and security status is assigned to each contingency based on its risk value. Additionally, simulations are carried out on modified 118 and 300 bus IEEE systems, and the extensive results are utilized to demonstrate the effectiveness of the proposed methodology. 
کلیدواژه‌ها
Cascading failure؛ complex network theory؛ security assessment؛ risk index؛ wind farm
مراجع
  1. Limouzadeh and A. Rabiee, “Security constrained reactive power scheduling considering n-1 contingency of transmission lines,” J. Oper. Autom. Power Eng., vol. 10, no. 1, pp. 66–70, 2022.
  2. Z. A. Bhuiyan, G. J. Anders, J. Philhower, and S. Du, “Review of static risk-based security assessment in power system,” IET Cyber-Phys. Syst.: Theor. Appl., vol. 4, no. 3, pp. 233–239, 2019.
  3. S. Kumar, H. Quan, K. Y. Wen, and D. Srinivasan, “Probabilistic risk and severity analysis of power systems with high penetration of photovoltaics,” Sol. Energy, vol. 230, pp. 1156–1164, 2021.
  4. Li and Z. Qi, “Impact of cascading failure based on line vulnerability index on power grids,” Energy Syst., vol. 13, no. 4, pp. 893–918, 2022.
  5. Wang, P. Ju, F. Wu, S. Lei, and X. Pan, “Sequential steady-state security region-based transmission power system resilience enhancement,” Renewable Sustainable Energy Rev., vol. 151, p. 111533, 2021.
  6. Ding, K. Yu, C. Wang, and W.-J. Lee, “Transmission line overload risk assessment considering dynamic line rating mechanism in a high-wind-penetrated power system: A datadriven approach,” IEEE Trans. Sustainable Energy, vol. 13, no. 2, pp. 1112–1122, 2022.
  7. Yin, T. Liu, L. Wu, C. He, and Y. Liu, “Day-ahead riskconstrained stochastic scheduling of multi-energy system,” J. Mod. Power Syst. Clean Energy, vol. 9, no. 4, pp. 720–733, 2021.
  8. Li, Z. Yang, P. Guo, and J. Cheng, “An intelligent transient stability assessment framework with continual learning ability,” IEEE Trans. Ind. Inf., vol. 17, no. 12, pp. 8131–8141, 2021.
  9. Wu, H. Chu, and C. Xu, “Risk assessment of windphotovoltaic-hydrogen storage projects using an improved fuzzy synthetic evaluation approach based on cloud model: A case study in china,” J. Energy Storage, vol. 38, p. 102580, 2021.
  10. Li, X. Zhang, L. Wu, P. Lu, and S. Zhang, “Transmission line overload risk assessment for power systems with wind and load-power generation correlation,” IEEE Trans. Smart Grid, vol. 6, no. 3, pp. 1233–1242, 2015.
  11. Mehdizadeh, R. Ghazi, and M. Ghayeni, “Power system security assessment with high wind penetration using the farms models based on their correlation,” IET Renewable Power Gener., vol. 12, no. 8, pp. 893–900, 2018.
  12. Yorino, M. Abdillah, Y. Sasaki, and Y. Zoka, “Robust power system security assessment under uncertainties using bi-level optimization,” IEEE Trans. Power Syst., vol. 33, no. 1, pp. 352–362, 2017.
  13. Nangrani and S. Bhat, “Smart grid security assessment using intelligent technique based on novel chaotic performance index,” J. Intell. Fuzzy Syst., vol. 34, no. 3, pp. 1301–1310, 2018.
  14. K. Tiwary, J. Pal, and C. K. Chanda, “Ann-based faster indexing with training-error compensation for mw security assessment of power system,” in Energy Syst. Drives Autom.: Proc. ESDA 2019, pp. 35–46, Springer, 2020.
  15. L. Cremer and G. Strbac, “A machine-learning based probabilistic perspective on dynamic security assessment,” Int. J. Electr. Power Energy Syst., vol. 128, p. 106571, 2021.
  16. Zang, S. Gao, T. Huang, X. Wei, and T. Wang, “Complex network-based transmission network vulnerability assessment using adjacent graphs,” IEEE Syst. J., vol. 14, no. 1, pp. 572–581, 2019.
  17. Guo, C. Liang, A. Zocca, S. H. Low, and A. Wierman, “Line failure localization of power networks part i: Noncut outages,” IEEE Trans. Power Syst., vol. 36, no. 5, pp. 4140–4151, 2021.
  18. Alonso, J. Turanzas, H. Amaris, and A. T. Ledo, “Cyber-physical vulnerability assessment in smart grids based on multilayer complex networks,” Sens., vol. 21, no. 17, p. 5826, 2021.
  19. Yang, W. Chen, X. Zhang, and W. Yang, “A graphbased method for vulnerability analysis of renewable energy integrated power systems to cascading failures,” Reliab. Eng. Syst. Saf., vol. 207, p. 107354, 2021.
  20. Beyza, E. Garcia-Paricio, and J. M. Yusta, “Ranking critical assets in interdependent energy transmission networks,” Electr. Power Syst. Res., vol. 172, pp. 242–252, 2019.
  21. Dedousis, G.           Stergiopoulos,        G.           Arampatzis,           and D. Gritzalis, “A security-aware framework for designing industrial engineering processes,” IEEE Access, vol. 9, pp. 163065–163085, 2021.
  22. Almaleh and D. Tipper, “Risk-based criticality assessment for smart critical infrastructures,” Infrastruct., vol. 7, no. 1, p. 3, 2021.
  23. D. Hines, I. Dobson, and P. Rezaei, “Cascading power outages propagate locally in an influence graph that is not the actual grid topology,” IEEE Trans. Power Syst., vol. 32, no. 2, pp. 958–967, 2016.
  24. Nakarmi, M. Rahnamay Naeini, M. J. Hossain, and M. A. Hasnat, “Interaction graphs for cascading failure analysis in power grids: A survey,” Energ., vol. 13, no. 9, p. 2219, 2020.
  25. Chen, S. Ma, K. Sun, X. Yang, C. Zheng, and X. Tang, “Mitigation of cascading outages by breaking inter-regional linkages in the interaction graph,” IEEE Trans. Power Syst., vol. 38, no. 2, pp. 1501–1511, 2022.
  26. -L. Fan, X.-F. He, Y.-Q. Xiao, and Q.-Y. Li, “Vulnerability analysis of power system by modified h-index method on cascading failure state transition graph,” Electr. Power Syst. Res., vol. 209, p. 107986, 2022.
  27. Li, K. Liu, and M. Wang, “Robustness of the chinese power grid to cascading failures under attack and defense strategies,” Int. J. Crit. Infrastruct. Prot., vol. 33, p. 100432, 2021.
  28. Xie, X. Tian, L. Kong, and W. Chen, “The vulnerability of the power grid structure: A system analysis based on complex network theory,” Sens., vol. 21, no. 21, p. 7097, 2021.
  29. Zhang, L. Jia, J. Ning, Y. Ye, H. Sun, and R. Shi, “Power grid structure performance evaluation based on complex network cascade failure analysis,” Energ., vol. 16, no. 2, p. 990, 2023.
  30. Bose, C. K. Chanda, and A. Chakrabarti, “Vulnerability assessment of a power transmission network employing complex network theory in a resilience framework,” Microsyst. Technol., vol. 26, no. 8, pp. 2443–2451, 2020.
  31. F. Gharibeh, L. M. Khiavi, M. Farrokhifar, A. Alahyari, and D. Pozo, “Capacity value of variable-speed wind turbines,” in 2019 IEEE Milan PowerTech, pp. 1–5, IEEE, 2019.
  32. Hosseini, A. Safari, and M. Farrokhifar, “Cloud theory-based multi-objective feeder reconfiguration problem considering wind power uncertainty,” Renewable Energy, vol. 161, pp. 1130–1139, 2020.
  33. Song, Y. Wang, L. Zhao, K. Qin, L. Liang, Z. Yin, and W. Tao, “Study on thermal load capacity of transmission line based on ieee standard,” J. Inf. Process. Syst., vol. 15, no. 3, pp. 464–477, 2019.
  34. Khan and M. Ghassemi, “A probabilistic approach for analysis of line outage risk caused by wildfires,” Int. J. Electr. Power Energy Syst., vol. 139, p. 108042, 2022.
  35. Sreedevi, G. Chethan, and P. L. Rao, “Voltage stability analysis of ieee118 bus system with wind penetration,” Power Res.-A J. CPRI, pp. 17–21, 2022.
  36. Texas Reliability Entity, “Assessment of reliability performance for the texas interconnection,” tech. rep., 2021.
  37. Pandiarajan and C. Babulal, “Fuzzy ranking based nondominated sorting genetic algorithm-ii for network overload alleviation,” Arch. Electr. Eng., vol. 63, no. 3, 2014.
  38. Yuan, “A study on wide-area measurement-based approaches for power system voltage stability,” phD diss, 2016.
  39. Nesti, J. Nair, and B. Zwart, “Temperature overloads in power grids under uncertainty: A large deviations approach,” IEEE Trans. Control Network Syst., vol. 6, no. 3, pp. 1161– 1173, 2019.
  40. Chen, S. M. Mazhari, C. Chung, S. O. Faried, and B. C. Pal, “Rotor angle stability prediction of power systems with high wind power penetration using a stability index vector,” IEEE Trans. Power Syst., vol. 35, no. 6, pp. 4632–4643, 2020.
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