Currently, the centralized optimization regulation strategy for conventional energy storage systems struggles to meet the operational requirements of centralized-distributed energy storage systems in rural areas. To address this challenge, this study examines a typical village in the Central Shaanxi Plain, Shaanxi Province, China, and integrates the usage patterns of agricultural machinery batteries into energy storage regulation. A peer-to-peer （P2P） trading mechanism for distributed energy storage, based on a combinatorial double auction, is proposed. In the trading environment, a double-layer optimal regulation model for rural centralized-distributed energy storage systems is established using a Stackelberg game approach and computationally solves it. The results show that 1）P2P trading are highly influenced by agricultural production patterns in both quantity and time. 2）P2P trading reduces the operating cost of each subject in the centralized-distributed energy storage system by 4.96%, reduces carbon emissions by 10.41%, and increases the PV consumption rate by 18.04%. 3）The annual electricity cost of different types of rural households is reduced by the increase of decentralized energy storage capacity, the reduction is more significant after the introduction of P2P trading, and the cost reduction is especially prominent for rural households with large rooftop PV installations, small electricity demand, and sufficient energy storage resources. Energy storage operator will suffer from the increase in revenue due to the increase in decentralized energy storage capacity, and the revenue will be further reduced after the introduction of P2P trading, but can be compensated for by appropriately charging operation and management fees.

peer to peer trading  /  agricultural machinery batteries  /  distributed energy storage  /  centralized energy storage  /  optimal regulation  /  combinatorial double auction