부산대학교 도서관

Rural areas currently exhibit characteristics of multifunctional regional differentiation, with significant differences in energy utilization among different regions and issues such as low renewable energy utilization and unreasonable consumption structures. This paper initially constructs a multiple regional integrated energy systems (MRIES) in rural areas and introduces the Power to ammonia-anaerobic fermentation (P2A-AF) coupled system to enhance the accommodation rate of renewable energy and operational efficiency. Subsequently, random fuzzy modeling is employed to address the random fuzzy uncertainties associated with renewable energy. Then, the MRIES co-optimization model based on peer-to-peer (P2P) energy trading is constructed and solved. After that, the conditional value at risk (CVaR) value of net load deviation is introduced to measure the risk level of each RIES, and the improved Shapley value revenue allocation model is constructed. Finally, the simulation yields: compared to standalone operation, the MRIES co-optimization model improves the system economy and the local accommodation of renewable energy by 13.16 % and 9.37 %. The deviations in wind turbine and photovoltaic output characterized by random fuzzy simulation, compared to considering randomness alone, are reduced by 4.33 % and 9.31 %, respectively. The improved Shapley profit distribution model has allocated 41.28 %, 44.66 %, and 14.06 % of the profit to RIES1-3, respectively, ensuring fairness while addressing risk variations. The results demonstrate that the proposed MRIES collaborative optimization model can significantly improve the low-carbon characteristics and economic efficiency of rural energy use. It is suggested that future research consider the source-load characteristics of rural areas in different regions to develop more applicable energy strategies for various rural RIES, providing new insights for global rural energy use.