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

TL;DR

This paper introduces a distributionally robust optimization framework to evaluate power system flexibility under uncertain net loads, providing less conservative and more accurate assessments than traditional methods.

Contribution

It presents a novel stochastic assessment method for power system flexibility that accounts for load variability and system violations, improving upon existing deterministic approaches.

Findings

The proposed method reduces conservativeness in flexibility evaluation.

It effectively handles high-dimensional load uncertainties.

Validated on four IEEE test systems with promising results.

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 real-time economic dispatch problem on four IEEE standard test systems. Compared to traditional deterministic flexibility evaluations, our approach consistently yields less conservative flexibility outcomes.