A Multiagent Framework Coordinating One-to-Many Concurrent Composite Negotiations in a Multistage Postpaid P2P Energy Trading Model

Abstract

Fast-growing distributed energy resources, prosumers, and electric vehicles risk overloading the grid and would require costly infrastructure expansion. In this respect, local energy markets seem to be a promising solution that enables the participation of prosumers and consumers in peer-to-peer energy transactions. However, most existing solutions require substantial computational resources and detailed real-time data, limiting practical deployment on edge devices and in large-scale environments. Conventional negotiation frameworks are mainly synchronous and prepaid, lacking lightweight, scalable, postpaid, and concurrent negotiation protocols to streamline transactions and minimize communication overhead. To address these gaps, we present an advanced three-stage multiagent model for peer-to-peer energy trading within the context of local energy markets, designed for simplicity and ease of integration in resource-constrained settings. This model is strategically engineered to optimize market participation and grid support by orchestrating a one-to-many concurrent composite negotiation strategy that supports postpaid transactions. Empowered by the smart Python multiagent development environment, which harnesses the instant extensible messaging and presence communication protocol, our model ensures seamless execution of peer-to-peer energy transactions with minimal computational burden. Furthermore, the methodology presented is extremely simple and generic compared to other procedures in the literature, facilitating scalable implementation on edge devices and supporting wide real-world adoption.