Assessment method and metrics of power system resilience after disasters. Issue 16 (24th January 2019)

• Record Type: Journal Article
• Authors: Zhang, Han; Bie, Zhaohong; Li, Gengfeng; Lin, Yanling
• Is Part Of: Journal of engineering. Volume 2019:Issue 16(2019)
• Page Start: 880
• Page End: 883
• Publication Date: 2019-01-24
• Subjects: business continuity -- load flow -- power engineering computing -- maintenance engineering -- distributed power generation -- power transmission economics -- disasters; assessment method -- power system resilience -- disasters -- power supply -- important load -- research existing -- load loss -- clear methodologies -- power system post‐disaster recovery strategy -- assessment metrics -- load nodes -- given the repair strategies -- load recovery procedure -- corresponding metrics -- different restoration strategies -- system decision makers -- 14‐bus system; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2018.8661
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : How to restore the load of power system after disasters, especially to guarantee the power supply of the important load, is a significant segment of the research on power system resilience. Nowadays, quantities of research existing has been done to reduce the load loss after disasters. However, there is no clear methodologies or metrics available to evaluate the effects of restoration strategies. Here, a method for evaluating the recovery and economic efficiency of the power system post‐disaster recovery strategy is explored, and assessment metrics related are defined. The method considers the repair and recovery process of transmission lines, generators, and the distributed generation at load nodes. After given the repair strategies, components state sampling and system power flow calculation will be conducted to analyse the running state of the system, then simulate the component repair and the load recovery procedure, and finally calculate corresponding metrics. This novel method can obtain and compare the expected effects of different restoration strategies in advance, providing more reliable reference information for system decision makers. Finally, the proposed method is applied to IEEE 14‐bus system and verifies its effectiveness and application value.