AI-Based Electricity Grid Management for Sustainability, Reliability, and Security
Jia-Hao Syu, Jerry Chun‐Wei Lin, Gautam Srivastava
Abstract
Greenhouse gas emissions are critical issues for mankind, especially from the viewpoint of electricity consumption. The smart grid is an emerging issue in terms of efficiency, sustainability, reliability, and security. This article proposes a concept for an AI-based electricity management system that includes prediction, anomaly detection, grid management, and market equalization modules. The prediction module predicts electricity supply and demand, and the anomaly detection module detects potential attacks and failures for security considerations. Based on prediction and detection, the grid management module determines sustainable subsidies and reliable operating reserve. Finally, the market equilibrium model balances electricity supply and demand.