Abstract
Underground natural gas storage (UNGS) is an important infrastructure to overcome the imbalance between supply and demand of natural gas. During the gas injection period, gas is compressed aboveground and then transported to injection wells for injection into the underground reservoir. Reasonably formulating the compressor operation scheme and injection scheduling scheme is a crucial step. However, “Compressor-pipeline-injection well-reservoir" constitutes a synergistic whole. More efficient and practical operation schemes can only be proposed through the establishment of an optimization method that coordinates the entire gas injection process. A novel two-layer multi-objective collaborative optimization method is proposed to optimize the monthly operation scheme during the injection period. The upper-layer model focuses on optimizing injection volume allocation to minimize reservoir pressure deviation and total compressor energy consumption. The under-layer model optimizes the compressor operation scheme by considering the multi-stage compression (MC) and clearance adjustment (CA) equipped in reciprocating compressors. The synergistic relationship during the injection process is integrated into the traditional model through the interlayer iteration method. Furthermore, a high accuracy and efficiency proxy model based on machine learning algorithms (ML) is developed to predict compressor performance. The results of the case study indicate that, compared with traditional optimization method and the two-stage co-optimization method, the proposed method achieves an average energy consumption reduction of 9.54 × 106 kWh (10.79%) and 2.12 × 106 kWh (2.4%) respectively. The effective utilization of CA and MC can significantly alleviate the deviations between displacement and processing requirements, eliminating 22,120.5 × 104 Nm3(85.62%). The two-layer co-optimization method effectively integrates the aboveground and underground parts of UNGS, providing a solution for safe and efficient operation during the injection period.
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