Real-Time Energy Management Strategies for Community Microgrids

2025/06/28 by Moslem Uddin, Uddin, Moslem, Huadong Mo +3
Engineering · #Microgrid Control and Optimization #Smart Grid Energy Management #Integrated Energy Systems Optimization

paper · pdf · doi:10.48550/arxiv.2506.22931

Abstract

This study presents a real-time energy management framework for hybrid community microgrids integrating photovoltaic, wind, battery energy storage systems, diesel generators, and grid interconnection. The proposed approach formulates the dispatch problem as a multi-objective optimization task that aims to minimize operational costs. Two control strategies are proposed and evaluated: a conventional rule-based control (RBC) method and an advanced deep reinforcement learning (DRL) approach utilizing proximal policy optimization (PPO). A realistic case study based on Australian load and generation profiles is used to validate the framework. Simulation results demonstrate that DRL-PPO reduces operational costs by 18%, CO₂ emissions by 20%, and improves system reliability by 87.5% compared to RBC. Beside, DRL-PPO increases renewable energy utilization by 13%, effectively reducing dependence on diesel generation and grid imports. These findings demonstrate the potential of DRL-based approaches to enable cost-effective and resilient microgrid operations, particularly in regional and remote communities.

Citations

• Integrated Energy Management for Operational Cost Optimization in Community Microgrids
• Cost-Effective Design of Grid-tied Community Microgrid
• A review of hybrid renewable energy systems: Solar and wind-powered solutions: Challenges, opportunities, and policy implications
• Providing Privacy, Safety, and Security in IoT-Based Transactive Energy\n Systems using Distributed Ledgers

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