Application of genetic algorithm to a gas network for compressor speed optimization

This contains codes for determining the optimum speed for six compressors for a gas network, the flow rates were obtained from the first simulation which is the flow simulation, the flow will remain constant during the simulation.

The hypothesis is that compressor speed determines fuel consumption. The speed is encoded as genes and the fuel consumption is the objective function
A genetic algorithm was used to search for the optimum speed for the compressors, that fulfill the objective function.
From the simulation, the data showed that a genetic algorithm can be used to determine the sets of speed that give the minimum fuel consumption and is subjected to the constraint which is the pressure range at the demand point.

本数据集包含用于确定某燃气网络六台压缩机最优运行转速的代码。流量参数取自首次开展的流体流动仿真（Flow Simulation），且仿真全程流量保持恒定。
本研究的核心假设为：压缩机转速直接决定燃料消耗量。研究中将转速编码为基因（Gene），并以燃料消耗量作为目标函数（Objective Function）。
本研究采用遗传算法（Genetic Algorithm）搜索能够满足该目标函数的压缩机最优转速组合。
仿真结果数据表明，遗传算法可用于求解使燃料消耗量最小化的转速组合，且该结果需满足需求点的压力范围约束条件。