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Optimizing Day-Ahead Energy Trading with Proximal Policy Optimization and Blockchain

arXiv — cs.LG•Tuesday, December 9, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
  • A novel framework has been proposed to optimize day-ahead energy trading by integrating Proximal Policy Optimization (PPO) with blockchain technology. This approach addresses challenges in balancing supply and demand in renewable energy markets, ensuring grid resilience, and maintaining trust in decentralized trading systems. Real-world simulations from the Electricity Reliability Council of Texas (ERCOT) demonstrate the framework's effectiveness in achieving demand-supply balance and minimizing supply costs.
  • The integration of PPO and blockchain technology is significant as it enhances automated trading strategies for prosumers, allowing for more efficient energy management in day-ahead markets. This development is crucial for the growing reliance on renewable energy sources, which require innovative solutions to manage their variability and ensure stable energy supply.
  • This advancement reflects a broader trend in the energy sector towards utilizing artificial intelligence and decentralized technologies to improve operational efficiency. The ongoing exploration of reinforcement learning techniques, such as PPO, alongside blockchain applications, highlights a commitment to addressing the complexities of modern energy markets and the need for reliable, tamper-proof transaction management.
— via World Pulse Now AI Editorial System
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