A Smart Microgrid Platform Integrating AI and Deep Reinforcement Learning for Sustainable Energy Management

Badr Lami (), Mohammed Alsolami, Ahmad Alferidi and Sami Ben Slama
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Badr Lami: Department of Electrical Engineering, College of Engineering, Taibah University, Madinah 41411, Saudi Arabia
Mohammed Alsolami: Department of Electrical Engineering, College of Engineering, Taibah University, Madinah 41411, Saudi Arabia
Ahmad Alferidi: Department of Electrical Engineering, College of Engineering, Taibah University, Madinah 41411, Saudi Arabia
Sami Ben Slama: The Applied College, King Abdulaziz University, Jeddah 22254, Saudi Arabia

Energies, 2025, vol. 18, issue 5, 1-30

Abstract: Smart microgrids (SMGs) have emerged as a key solution to enhance energy management and sustainability within decentralized energy systems. 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-peer (P2P) energy trading. The platform dynamically adapts to real-time energy demand and supply fluctuations, achieving a 23% reduction in energy costs, a 40% decrease in grid dependency, and an 85% renewable energy utilization rate. Furthermore, AI-driven P2P trading mechanisms demonstrate that 18% of electricity consumption is handled through efficient decentralized exchanges. The integration of vehicle-to-home (V2H) technology allows electric vehicle (EV) batteries to store surplus renewable energy and supply 15% of household energy demand during peak hours. Real-time data from Saudi Arabia validated the system’s performance, highlighting its scalability and adaptability to diverse energy market conditions. The quantitative results suggest that SmartGrid AI is a revolutionary method of sustainable and cost-effective energy management in SMGs.

Keywords: deep reinforcement learning; electric vehicles; peer-to-peer energy trading; renewable energy integration; smart microgrid; SmartGrid AI (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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