基于遗传算法的盐穴储气库注气能力方案优化

盐穴储气库作为中国天然气调峰的重要手段之一，承担着战略储备的重要任务。为提高川气东送输气管网的运行优化能力，对金坛盐穴储气库提出合适的注气配产方案以降低压缩机能耗作为当前阶段的首要目标。通过对金坛盐穴储气库的地理环境、管道参数、储气井参数、压缩机能耗等综合因素进行分析后，以该地区十口井注气流程为例，将其配气方案的能耗分析作为主要目标，在满足于储气库总量、单井注气约束条件的情况下，应用遗传算法对注气任务方案进行优化。通过分析了5组遗传算法进行优化的注气配气过程，结果表明当迭代步数达到25步左右时，总能耗达到收敛且平均每组运行时间为4.57 s,进一步分析得出各单井注气量在优化过程中的趋势图。在符合现场条件、满足于注气需求的情况下，最终模拟优化后的配产方案系相比最初配产方案压缩机能耗下降了33%,实际现场压缩机能耗下降普遍在30%～35%,大幅降低了压缩机能耗浪费，对实际生产应用具有一定的指导作用。

Optimization of Gas Injection Capacity Strategy for Salt Cavern Gas Storage Based on Genetic Algorithm

The salt cavern gas storage facility, as one of the crucial means for natural gas peak shaving in our country, is tasked with a strategic reserve role. In order to enhance the operational optimization of the Sichuan-to-East transmission pipeline network in this region, suitable gas injection and production schemes have been proposed for the salt cavern gas storage facility, with the primary objective at this stage being the reduction of compressor energy consumption. Following an analysis of various factors including geographical environment, pipeline parameters, gas storage well parameters, and compressor energy consumption of the salt cavern gas storage facility, the injection process of ten wells in the region is taken as an example. The energy consumption analysis of the distribution scheme is established as the main goal. While adhering to constraints on the total gas storage capacity and individual well injection, a genetic algorithm is employed to optimize the injection task scheme. After evaluating the optimization process using five sets of genetic algorithm iterations, the results indicate that convergence of total energy consumption is achieved at around 25 iterations, with an average runtime of 4.57 seconds per iteration. Further analysis reveals the trend of gas injection volumes for each individual well during the optimization process. In compliance with on-site conditions and injection requirements, the final simulated and optimized production scheme demonstrates a 33% reduction in compressor energy consumption compared to the original scheme. The actual on-site reduction in compressor energy consumption generally falls between 30% and 35%, significantly mitigating energy wastage in compressor operation. This holds substantial significance for practical production applications.