Research & Papers
Accepted
Edge-Intelligence-Enhanced Proximal Policy Optimization (EIF-PPO) for Real-Time Power Balancing in Distributed Energy Microgrids
PPO actor–critic control deployed in a hierarchical edge architecture for microgrid power balancing.
- When
- Jul 2025 – Jun 2026
- Role
- Sole author
- Venue
- Informatica
- Authors
- Peilin Li
- Headline result
- −62.5% inference latency
- Formulated real-time microgrid power balancing as a sequential decision problem and developed EIF-PPO to address power mismatch, frequency deviation, and battery instability under renewable intermittency and cloud-communication delays.
- Deployed a PPO actor–critic controller within a hierarchical edge architecture, transforming asynchronous PV, BESS, and load-bus telemetry into decentralized dispatch actions; constructed LMOD-based stochastic environments to emulate generation, demand, and communication uncertainty.
- Achieved a 62.5% reduction in inference latency and a 41% improvement in battery SoC stability relative to cloud-based control, independently completing framework design, simulation, benchmarking, analysis, and manuscript development.
Tech stack
- Reinforcement Learning
- PPO
- Edge Computing
- Power Systems