含水层
压缩空气储能
石油工程
磁导率
多孔性
多孔介质
环境科学
地质学
机械
储能
土壤科学
岩土工程
地下水
热力学
化学
功率(物理)
生物化学
物理
膜
作者
Yi Li,Yi Li,Yaning Liu
标识
DOI:10.1016/j.est.2021.103837
摘要
Compressed air energy storage in aquifers has been considered to be a potential solution to overcoming the scale limitation of air storage space in the CAES technology and making use of intermittent renewable energy in a highly efficient way. Layered heterogeneity commonly exists in deep aquifers and influences the air-water-heat flow, especially in the typical frequent injection-production cyclic operation scheme in CAESA, and remains an insufficiently researched topic. Aimed at the multiphase fluid and non-isothermal processes in an aquifer, a layered heterogeneous model based on the drilling data from the Iowa plant is constructed and simulated for both initial gas bubble formation and cycle processes using T2Well/EOS3. When a closed surrounding geological boundary exists, the simulation results show that the air flow strongly depends on the heterogeneity distribution and multi-fingering occurs in the aquifer due to the preferential flow path. In comparison with the weighted average effective homogeneous model, the cyclic pressure fluctuation is smaller with a 0.2 MPa difference and the defined energy efficiency is slightly larger with an additional 32 MJ produced in 200 days in the heterogeneous aquifer. In addition, a two-layer heterogeneous sequence model is discussed to facilitate the evaluation of candidate sites. It is found that the case where the layer with high porosity and permeability is located on the top is more advantageous than the one where the layers are arranged in the other way around. The more stable pressure and smaller fluctuation with 0.35 MPa as the system continues, as well as an additional energy recovery of 114 MJ during 200 cycles due to the concentrated air area in the upper aquifer are beneficial. The research on the layered heterogeneity system will deepen the understanding of the role of the target aquifer and help evaluate candidate sites for compressed air energy storage in aquifers.
科研通智能强力驱动
Strongly Powered by AbleSci AI