Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

A Branch-independence-based Reliability Assessment Approach for Transmission Systems
Author:
Affiliation:

1. Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin, China 2. School of Electrical Engineering, Beijing Jiaotong University, Beijing, China 3. State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing, China4. State Grid Tianjin Electric Power Research Institute, Tianjin, China

Fund Project:

This work was supported by the China Postdoctoral Science Foundation (No. 2020TQ0222).

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
    Abstract:

    This paper proposes a branch-independence-based reliability assessment approach for transmission systems. The approach consists of branch decoupling and state-space partition techniques. By integrating an impact-increment-based reliability index calculation model and the proposed branch decoupling technique, a proportion of sampled contingency states no longer need to be analyzed using the time-consuming optimal power flow (OPF) algorithm. In this way, the technique speeds up the calculation of reliability indices. Since first-order contingency states have a high probability of being sampled, we propose a state-space partition technique to replace first-order contingency state simulation with first-order contingency state enumeration. Consequently, the calculation of reliability indices is further accelerated by avoiding a large amount of repetitive OPF analyses during simulation process without affecting reliability index accuracy. The validity and applicability of our approach are verified using the IEEE 118-bus and IEEE 145-bus systems. Numerical results indicate that the proposed approach can improve computational efficiency without decreasing accuracy.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:April 28,2021
  • Revised:August 02,2021
  • Adopted:
  • Online: March 25,2023
  • Published: