Low carbon operation optimization of underground gas storage systems with embedded differential pressure generation based on user demand uncertainty

Abstract

Underground gas storage (UGS) reservoirs operate with a large pressure difference between the injection-production pressure and the delivery pressure. To recover this residual pressure, this study proposes integrating natural gas pressure differential power generation technology (NGPDPGT) to UGS. Meanwhile, as a critical facility for natural gas storage and peak shaving, UGS must accommodate fluctuations in user demand. Therefore, this study establishes a low carbon operation optimization model of gas storage system with embedded differential pressure generation based on demand uncertainty (DPGC-Model). After preprocessing the uncertainty of user demand (UUD), the model is solved using a heuristic cycle optimization algorithm process. The optimization model is verified using UGS from a depleted gas reservoir in China (W-UGS), which proves that the carbon emissions are significantly reduced after the integration of differential pressure generator set (DPGS). The study investigates the changes in pressure and temperature at each well site after embedding DGPS and analyzes the operation of the UGS system under UUD. The results show that as the standard deviation and confidence level increase, both total operating carbon emissions and carbon reduction from differential pressure generation (DPG) increase. This study not only has significant implications for energy recovery and achieving low-carbon operations in UGS systems but also provides support for the application of NGPDPGT.