@article{Luo2026, 
author = {Xi Luo and Mingyue Han and Yanning Zheng and Wenyuan Huang},
title = {Double-layer optimal control of rural centralized-distributed energy storage systems in P2P trading market considering agricultural machinery batteries},
year = {2026},
journal = {Building Simulation},
volume = {19},
number = {7},
pages = {1733-1759},
keywords = {peer-to-peer trading, agricultural machinery batteries, distributed energy storage, centralized energy storage, optimal regulation, revenue distribution},
url = {https://www.sciopen.com/article/10.1007/s12273-026-1434-z},
doi = {10.1007/s12273-026-1434-z},
abstract = {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.}
}