Grid-Aware Smart Charging Algorithms Using Predictive Energy Models

Abstract

Author(s): Elena Sato, Liam Garcia, Fatima Wang. This study explores grid-aware smart charging algorithms using predictive energy models with a focus on practical engineering trade-offs in modern cloud-native environments. We present an implementation-driven methodology, reference architectures, and evaluation criteria that teams can adopt in applied ai for energy programs. Results highlight measurable improvements in reliability, security posture, and end-user performance when the proposed practices are applied.