Study On Optimization Of Low Energy Consumption Operation Of Gas Compressor Station In Gas Transmission Pipeline

With the continuous development and expansion of the natural gas industry chain,the safe,stable,scientific and efficient operation of the gas transmission pipeline network as an intermediate link has become the key and difficult point of production management,it is the breakthrough point for the pipeline transportation enterprises to reduce cost and increase efficiency,and it is also the essential condition to ensure the normal gas use by downstream users.Optimizing the energy consumption of long-distance pipelines can effectively guide the low-cost operation of stations,and it is also the focus of the research on energy conservation and consumption reduction in major gas industries.Based on the data of the operation system of the SHAANXI PROVINCIAL NATURAL GAS CO.,LTD,this paper firstly analyzes the economic problems in the actual operation of the natural gas pipeline network,and finally takes the amount of natural gas consumed by the operation of the compressor and the electricity consumed as the economic optimization indexes.Secondly,the steady state operation of the Pipeline network is simulated in this paper,and the steady state of the circumferential branch Pipeline network is programmed and solved.The result is checked with the offline operation model of the SHAANXI PROVINCIAL NATURAL GAS CO.,LTD Pipeline network established by Pipeline Studio,and the error meets the engineering requirements.Then,the rotation speed,flow rate and burnup of the reciprocating and centrifugal compression of each field station are calculated by fitting,which have certain linear relationship,so as to determine the objective function.Finally,taking the pressure of each station and the compressor as the optimal variables,the Whale Swarm Algorithm and particle swarm optimization algorithm are used to solve the optimization,and the optimal starting scheme is obtained.Through the research of this paper,it is found that in the process of linear and quadratic fitting of the capacity and Burnup,the square deviation of the error is close,and the fitting degree of the centrifugal compressor is higher than that of the reciprocating compressor.Secondly,Cetacean Swarm Algorithm and particle swarm algorithm can solve the model very well,and both of them have high iterative speed.From the result,Particle Swarm Algorithm is premature convergence,easy to fall into local optimum.