A bi-level peer-to-peer interactive trading optimization model and distributed solution algorithm for rural distributed energy system group based on Stackelberg-Nash game strategy

With the in-depth promotion of Rural Revitalization Strategy and the problem of low utilization of distributed resources, it is becoming increasingly common and intense for rural distributed energy system(RDES) to participate in energy market trading. Therefore, to increase the competitiveness of trading, this paper takes the RDES group, formed by multi-RDES through electricity-carbon-biomass peer-to-peer trading, as a foundational participant in the market, and establishes a Stackelberg game model between RDES group and the energy supplier(ES). Secondly, a lower-level Asymmetric Nash bargaining model combining marginal contribution rate and multi-energy-sharing contribution rate is constructed. Then, an improved distributed solution algorithm is designed to protect the privacy of the systems during trading. Finally, three RDESs in Lankao County, Henan Province, China are taken as an example, multiple scenarios are set up for analysis. The results shows that the bilevel peer-to-peer interactive trading model proposed in this paper reduces cost by 24.91 %, improves the efficiency of renewable energy consumption, environmental benefits and the benefits allocation satisfaction, and realizes connectivity, energy sharing and win-win outcomes among multi-RDES.