Abstract
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.