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Sequential steady-state security region-based transmission power system resilience enhancement

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  • Wang, Chong
  • Ju, Ping
  • Wu, Feng
  • Lei, Shunbo
  • Pan, Xueping

Abstract

The increased high-impact and low-probability extreme weather events have posed unprecedented impacts on power system operation, and it is necessary to have appropriate methods to analyze the impacts. In this paper, a sequential steady-state security region (SSSR) is proposed to better describe the operational region impacted by sequential weather events, and SSSR is a polytope describing a region, where the operational constraints are satisfied. Based on SSSR with uncertain topology changes because of extreme weather events, a bi-level programming model is proposed. By means of Karush–Kuhn–Tucker conditions, the lower-level optimization model is equivalently transformed into a set of linear constraints, which are included in the upper-level optimization model. System topology scenarios are generated with the Monte Carlo method to avoid the curse of dimensionality caused by numerous uncertain topology scenarios. The generated system topology scenarios are mapped into the binary variables, representing line states, by means of the recursive McCormick (RMC) envelopes. Two test systems validate the proposed model. The results show that the proposed SSSR can well describe the feasible sequential region with regard to extreme weather events.

Suggested Citation

  • Wang, Chong & Ju, Ping & Wu, Feng & Lei, Shunbo & Pan, Xueping, 2021. "Sequential steady-state security region-based transmission power system resilience enhancement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    • Handle: RePEc:eee:rensus:v:151:y:2021:i:c:s136403212100811x
    DOI: 10.1016/j.rser.2021.111533
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    1. Saniye Maihemuti & Weiqing Wang & Jiahui Wu & Haiyun Wang & Muladi Muhedaner, 2022. "New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm," Energies, MDPI, vol. 15(24), pages 1-17, December.
    2. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    3. Liu, Hanchen & Wang, Chong & Ju, Ping & Li, Hongyu, 2022. "A sequentially preventive model enhancing power system resilience against extreme-weather-triggered failures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).

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