Deep-Learning-Enhanced Static Risk-Oriented Security Assessment under Uncertainty

• Published in: 2024 IEEE Power & Energy Society General Meeting (PESGM) pp. 1 - 5
• Main Authors: Masoumi, Amin, Korkali, Mert
• Format: Conference Proceeding
• Language: English
• Published: IEEE 21.07.2024
• Subjects: Accuracy; Complexity theory; Computer architecture; Contingency management; deep learning; generation (resource) adequacy; Power system reliability; Reliability; Scalability; Security; Simulation; Static security assessment; Uncertainty; uncertainty and contingency modeling

A power system's ability to supply resources to maintain continuous service to demand, known as generation (resource) adequacy, is an essential constituent of power system planning. Tools and methods to quantify adequacy are fundamental to launching emergency control actions beforehand. As the...