Quantitative operation risk assessment method for power grid with large-scale distributed new energy
CSTR:
Author:
Affiliation:

Clc Number:

TM732

Fund Project:

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

    The large-scale integration of massive heterogeneous distributed new energy has brought great challenges to the safe and stable operation of power system. It is of great significance to carry out research on operational risk assessment considering the uncertainty of distributed new energy. Firstly, the key influencing factors of the dynamic response characteristics of the distributed new energy equivalent model are analyzed, and the online dynamic equivalent modeling method of distributed new energy is proposed to determine the comprehensive load model and the state of distributed new energy that meet the requirements of online risk assessment. Then, according to the output characteristics of distributed new energy and multiple types of security and stability impact factors, clusters are divided, and the number of deterministic scenarios participating in safety and stability analysis is reduced by reducing the dimensionality of uncertainty variables. On this basis, the control measures and risk indicators that meet the requirements of safe and stable operation are calculated for different confidence intervals, and the different consequences of high probability low loss and low probability high loss scenarios on the power system are quantitatively evaluated. Finally, the application case results of actual power grid show that the risk assessment method proposed in this paper not only improves the risk assessment accuracy and calculation efficiency of the power grid with distributed new energy, but also can more comprehensively reflect the real-time operation risk characteristics of the system.

    Reference
    Related
    Cited by
Get Citation
Related Videos

Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:September 15,2024
  • Revised:December 02,2024
  • Adopted:
  • Online: August 01,2025
  • Published: July 28,2025
Article QR Code