A mixed integer nonlinear programming model for optimal design of natural gas storage surface double-pipe network

Abstract With the continuous increase of energy demand, the importance of natural gas storage has gradually increased. Underground natural gas storage (UNGS) has the characteristics of large capacity and low gas storage cost, and it is usually used as the main storage and peak shaving method for natural gas. As an important part of the surface engineering of UNGSs, the surface gathering and transportation system is responsible for gas injection and production and has a significant impact on the economic benefits of the entire surface engineering. Therefore, the optimization of the entire surface system has a great impact on improving economic benefits. However, there is no relevant article on the optimization of the dual-pipe injection-production pipeline network for the surface system of UNGSs. This paper considers the dual-pipe injection-production pipeline network of underground gas storage and establishes a Mixed-Integer Nonlinear Programming (MINLP) model. The goal of this model is to minimize the total cost of pipelines, platforms, and central stations. Constraints are considered in the model, such as the connection mode, facility/well number, length, flow balance, capacity, pressure, flow rate, pipe diameter, wall thickness, and variable value. The GAMS/IPOPT solution algorithm is adopted to find the best topology of the model, including the position of the platform and the central station, pipe diameter, wall thickness, and gas pressure and flow rate. Finally, two cases are used to compare the single and dual-pipe network systems to verify the effectiveness of the proposed model and the accuracy of the algorithm. The optimal results show that the mathematical model can reduce the total investment, and it can also guide the design and construction of the ground engineering of UNGSs.