Game-Theoretic Transactive Control Frameworks for Scalable and Privacy-Preserving Energy Storage Management in Renewable-Based Energy Communities

The increasing integration of distributed renewable energy sources and storage technologies within energy communities presents new challenges in coordinating energy flows and ensuring fair resource allocation among diverse participants. These communities, comprising prosumers and independent energy storage providers, necessitate robust, scalable, and privacy-preserving control frameworks to efficiently manage energy transactions. In response to these challenges, this study proposes two novel game-theoretic transactive energy management frameworks, coordinated and uncoordinated, for optimizing distributed energy storage scheduling. The coordinated framework leverages a central entity to facilitate optimized scheduling across the network, while the uncoordinated framework allows autonomous decision-making by agents using local information and market-driven signals. Each approach is designed to minimize overall community costs, ensure fair distribution of storage services, and maintain privacy by limiting the need for extensive data sharing. Extensive simulations conducted under varying renewable energy generation conditions demonstrate the effectiveness of both frameworks in comparison to a traditional centralized control model. Results reveal that under high renewable energy generation, total community costs decrease across all frameworks, with the uncoordinated framework achieving the lowest cost (€192.0723), followed by the coordinated (€194.3668) and centralized (€197.3802) frameworks. Conversely, during low renewable energy periods, costs rise due to greater reliance on storage and external energy procurement, with the centralized framework incurring the highest cost (€250.5042), while the uncoordinated (€205.1685) and coordinated (€220.4236) frameworks offer improved efficiency. Moreover, the proposed Game-Theoretic Augmented Lagrangian (GTALM) method achieves a 20 % cost reduction, demonstrating its capability to enhance economic efficiency while maintaining scalability and robustness. Simulation results show that both frameworks maintain stable performance under varying levels of renewable energy generation. Notably, the uncoordinated framework achieved the lowest community cost (€192.07) during high renewable periods, while the coordinated framework performed more reliably during low renewable conditions, confirming their suitability and scalability for deployment in large, heterogeneous energy communities.