loading page

Unreliability Tracing of Power Systems with Reservoir Hydropower Based on a Temporal Recursive Model
  • +1
  • Yunjie Bai,
  • Kaigui Xie,
  • changzheng Shao,
  • Bo Hu
Yunjie Bai
Chongqing University
Author Profile
Kaigui Xie
Chongqing University

Corresponding Author:[email protected]

Author Profile
changzheng Shao
Chongqing University
Author Profile
Bo Hu
Chongqing University
Author Profile


Power system unreliability tracing model allocates the system’s reliability index to individual components, identifying potential weaknesses. This study expands its scope by considering the impact of storage resources. Unreliable factors leading to load shedding are categorized into two groups: objective factors inherent to the component and insufficient storage resources. The latter requires a retrospective analysis of other components that caused unreliability previously. When allocating responsibility for load shedding at a certain time, it begins by allocating it among components based on differences between fixed expected output and actual supply. Expected output insufficiency is considered the unreliable factor. This insufficiency due to insufficient storage resources is then decomposed into segments, each caused by excessive output in earlier instances of the same component. The expected output excess is attributed to the expected output insufficiency of other components in previous times, for which responsibility has been allocated to each component. Consequently, the expected output insufficiency at a particular time can be traced back based on a temporal recursive model, with the load shedding further allocated to components before that time. Case studies based on several systems demonstrate that the proposed model’s allocation results are reasonable and more accurate than the traditional model.
31 Jan 2024Submitted to IET Generation, Transmission & Distribution
15 Feb 2024Assigned to Editor
15 Feb 2024Submission Checks Completed
22 Feb 2024Reviewer(s) Assigned
12 Mar 2024Review(s) Completed, Editorial Evaluation Pending
12 Mar 2024Editorial Decision: Revise Major