4.4 Article

Identification of critical lines for enhancing disaster resilience of power systems with renewables based on complex network theory

Journal

IET GENERATION TRANSMISSION & DISTRIBUTION
Volume 14, Issue 20, Pages 4459-4467

Publisher

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-gtd.2019.1853

Keywords

disasters; renewable energy sources; network theory (graphs); power grids; power transmission reliability; complex networks; power system security; optimisation; power transmission lines; load flow; disaster resilience; complex network theory; power system resilience; power supply reliability; critical transmission lines; critical line identification approach; CSN; power source nodes; critical lines identification; Guangdong Provincial Power System; Zhejiang Provincial Power System; core skeleton network; renewable energy sources; RES

Funding

  1. National Key R&D Program of China [2016YFB0900100]
  2. National Natural Science Foundation of China [51777185]
  3. Zhejiang Provincial Natural Science Foundation of China [LY17E070003]

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Natural disasters, such as typhoons and earthquakes, pose great challenges to power system resilience and power supply reliability. It is widely acknowledged that critical transmission lines play a significant role in enhancing the resilience and reliability of power systems under severe natural disasters. In order to improve the disaster resilience of power systems with renewables, a critical line identification approach is proposed in this work based on the complex network theory. Firstly, the concept of core skeleton network (CSN) of power systems with renewables is introduced and a two-step strategy is presented to optimise the CSNs of the concerned power system considering the variable outputs of renewables. Then, a statistical salience method incorporating edge salience and the state-of-the-art null model in complex network theory is proposed to identify critical lines of each CSN and the concerned power system with renewables. Finally, the effectiveness of the proposed critical lines identification approach is verified by simulations on the modified IEEE 118-bus system with renewables, Guangdong Provincial Power System (GPPS) and Zhejiang Provincial Power System (ZPPS) in China. Simulation results show that by using the proposed approach, the critical transmission lines can be effectively identified, not requiring a predefined number of critical lines.

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