Double-layer optimal control of rural centralized-distributed energy storage systems in P2P trading market considering agricultural machinery batteries

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. A revenue distribution mechanism based on the Shapley value method is introduced to ensure a reasonable distribution of revenue among alliance participants. The results showed that: (ⅰ) P2P trading can reduce the annual carbon emissions of centralized-distributed energy storage systems by 10.41% and increase photovoltaic energy consumption by 18.04%. (ⅱ) The annual electricity costs of different types of rural households decrease by 3.08% to 18.26% due to P2P trading, whereas the energy storage operators experience a 7.67% revenue loss. (ⅲ) Implementing the Shapley value-based revenue distribution mechanism effectively compensates for this loss, resulting in energy storage operators’ revenue being 5.22% higher than in the scenario without P2P trading. Although different types of rural households contribute 2.08% to 7.46% of their revenue share to compensate energy storage operators, the total annual electricity cost of rural households remains lower than in the scenario without P2P trading.