A Distributionally Robust Optimization Framework for Stochastic Assessment of Power System Flexibility in Economic Dispatch

Xinyi Zhao, Lei Fan, Fei Ding, Weijia Liu, Chaoyue Zhao

Research output: Contribution to conferencePaper

Abstract

Given the complexity of power systems, particularly the high-dimensional variability of net loads, accurately depicting the entire operational range of net loads poses a challenge. To address this, recent methodologies have sought to gauge the maximum range of net load uncertainty across all buses. In this paper, we consider the stochastic nature of the net load and introduce a distributionally robust optimization framework that assesses system flexibility stochastically, accommodating a minimal extent of system violations. We verify the proposed method by solving the flexibility of the economic dispatch problem on four distinct IEEE standard test systems. Compared to traditional deterministic flexibility evaluations, our approach consistently yields less conservative flexibility outcomes.
Original languageAmerican English
Number of pages5
DOIs
StatePublished - 2024
Event2024 IEEE Power & Energy Society General Meeting - Seattle, Washington
Duration: 21 Jul 202425 Jul 2024

Conference

Conference2024 IEEE Power & Energy Society General Meeting
CitySeattle, Washington
Period21/07/2425/07/24

NREL Publication Number

  • NREL/CP-5D00-92064

Keywords

  • distributionally robust optimization
  • economic dispatch
  • flexibility metric
  • net load uncertainty

Fingerprint

Dive into the research topics of 'A Distributionally Robust Optimization Framework for Stochastic Assessment of Power System Flexibility in Economic Dispatch'. Together they form a unique fingerprint.

Cite this