Li Yilong Smart Microgrid

Review of Smart Microgrid Platform Integrating AI and Deep

Smart microgrids are emerging as a pivotal solution within this framework, offering localized energy management that aligns with sustainability goals. These systems leverage diverse distributed energy
A Smart Microgrid Platform Integrating AI and Deep Reinforcement

This paper presents SmartGrid AI, a platform integrating deep reinforcement learning (DRL) and neural networks to optimize energy consumption, predict demand, and facilitate peer-to
An energy IoT-driven multi-dimension resilience methodology of smart

A multi-layer performance model for smart microgrids was constructed. The model driven by operation missions reveals the multi-layer performance characteristics of smart microgrids through
‪Yilong Li‬

Yilong Li PhD, Stanford University Verified email at cs.stanford operating systems distributed systems datacenter computing networking
Yilong Li''s Webpage

My research interests span networked and wireless systems, efficient on-device inference for large language models (LLMs), and mobile & wearable devices.
yilongli (Yilong Li) · GitHub

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Power Management of Inverter Interfaced Autonomous Microgrid

Both simulation and experimental results are provided in this paper. This paper presents the power management scheme for a power electronics based low voltage microgrid in islanding
Li YILONG | PhD Student | Doctor of Philosophy

Li Yilong currently works at the Department of functional nanocomposites and blends, Leibniz Institute of Polymer Research Dresden.
Intelligent Multi-Microgrid Energy Management Based on Deep Neural

Title: Intelligent Multi-Microgrid Energy Management Based on Deep Neural Network and Model-Free Reinforcement Learning
A systematic review of reinforcement learning-based control for

This article provides systematic review to follow a thorough evaluation of the present status of research on reinforcement learning (RL)-based microgrid control. The description of