Energy Trading Strategy for Prosumer Alliances with Dynamic Structures in Cloud-Edge-End Collaborative Systems

Due to the variability of renewable energy generation and the time-varying nature of load demand, it is challenging to achieve full local consumption of renewable energy by prosumers through cooperative game in the form of a fixed alliance to participate directly in electricity market transactions. Additionally, the increasing number of prosumers significantly escalates the computational demands for transaction strategy formulation. To address these issues, this paper proposes a cloud-edge-end distributed energy trading system architecture to reduce the computational complexity associated with a large number of prosumers. Dynamic partitioning of prosumers into optimal coalitions through a coalition game approach based on the strengthen elitist genetic algorithm (SEGA), aiming to maximize the complementarity between supply and demand. Case studies demonstrate that the dynamic coalition structure formed under the cloud-edge-end collaboration exhibits superior performance in compensating for computational deficiencies, enhancing overall energy utilization, and increasing individual prosumer profits.