Work

AI and ML Methods for Enhancing Power System Operations

Year: 2025

Type: article

Abstract: With the growing scale and complexity of modern power grids, recent advances in computing technologies, together with the availability of plenty of heterogeneous data, open the door for applying state-of-the-art machine learning approaches to solve critical power system operation and control problems. This Perspective discusses major data-driven machine learning methods and their potential applicability in integrating with physical model-driven approaches to reshape operational practices across modern power systems, followed by the introduction of five contributed articles in the Inaugural Issue of “AI and ML Methods for Enhancing Power System Operations”.

Source: AI Engineering

DOI: 10.53941/aieng.2025.100007

Authors: Xianbang Chen, Lei Wu

Institution: Stevens Institute of Technology

Language: English

Topic: Power System Optimization and Stability

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: hybrid

OpenAlex ID: W7117728041