Online risk-based security assessment

TLDR

Power system operators increasingly face high‑stress conditions in bulk transmission, prompting the development of online risk‑based security assessment that rapidly quantifies security levels by integrating contingency likelihood and severity into probabilistic risk indices. Applying these risk indices in control‑room decision making enhances detection of overloads, cascading overloads, low voltages, and voltage instability, and tests on large‑scale transmission models from a U.S.

Abstract

The work described in this paper was motivated by a perceived increase in the frequency at which power system operators are encountering high stress in bulk transmission systems and the corresponding need to improve security monitoring of these networks. Online risk-based security assessment provides rapid online quantification of a security level associated with an existing or forecasted operating condition. One major advantage of this approach over deterministic online security assessment is that it condenses contingency likelihood and severity into indices that reflect probabilistic risk. Use of these indices in control room decision making leads to increased understanding of potential network problems, including overload, cascading overload, low voltages, and voltage instability, resulting in improved security-related decision making. Test results on large-scale transmission models retrieved from the energy-management system of a U.S. utility company are described.