Enhancing decentralized community energy systems through an auction-theoretic transactive market framework for efficient demand response and renewable integration

Efficient demand response management and real-time energy trading are essential for achieving stable, cost-effective, and sustainable integration of distributed energy resources within decentralized community energy systems. This study proposes a comprehensive auction-theoretic transactive market framework that enables dynamic, decentralized energy exchange between prosumers and consumers while optimizing market efficiency, fairness, and grid resilience. The framework integrates uniform-price, discriminatory-price, and continuous double auction mechanisms to realize adaptive market clearing and real-time price formation. Through detailed mathematical modeling and simulation, the proposed system demonstrates a 25% reduction in grid dependency, 30% improvement in market efficiency, and 20% enhancement in fairness of energy allocation, alongside average participant cost savings of 15% and peak demand reduction of 18%. Unlike conventional transactive energy models that assume static markets or rely on centralized optimization, the proposed approach introduces a unified market–operations layer that jointly determines energy trades and demand response schedules under network constraints. The continuous double auction mechanism ensures continuous bid–ask matching and adaptive pricing, improving market liquidity and stability, while Vickrey auctions guarantee strategy-proof bidding and allocative efficiency. Realistic data from smart meters, advanced metering infrastructure, supervisory control and data acquisition systems, and historical price records were employed to validate system performance under varying renewable generation and load conditions. The results confirm the framework’s scalability, computational efficiency, and robustness under dynamic market conditions, demonstrating its suitability for community-scale deployment and future integration with artificial intelligence and blockchain technologies for autonomous trading and secure settlements. By combining auction theory, real-time demand responses optimization, and renewable integration, this research establishes a sustainable and economically viable model for next-generation decentralized energy markets aligned with global energy transition and net-zero emission goals. • Auction-theoretic framework for decentralized energy systems. • Multi-auction design for real-time adaptive energy trading. • Unified market clearing with demand response integration. • Achieves 25% grid reduction and 30% efficiency improvement. • Scalable framework with AI and blockchain readiness.