Operation optimization of natural gas pipelines has received increasing attentions, due to such advantages as maximizing the operating economic benefit and the gas delivery amount. This paper provides a review on the most relevant research progress related to the steady-state operation optimization models of natural gas pipelines as well as corresponding solution methods based on stochastic optimization algorithms. The existing operation optimization model of the natural gas pipeline is a mixed-integer nonlinear programming (MINLP) model involving a nonconvex feasible region and mixing of continuous, discrete, and integer optimization variables, which represents an extremely difficult problem to be solved by use of optimization algorithms. A survey on the state of the art demonstrates that many stochastic algorithms show better performance of solving such optimization models due to their advantages of handling discrete variables and of high computation efficiency over classical deterministic optimization algorithms. The essential progress mainly with regard to the applications of the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Simulated Annealing (SA) algorithms, and their extensions is summarized. The performances of these algorithms are compared in terms of the quality of optimization results and the computation efficiency. Furthermore, the research challenges of improving the optimization model, enhancing the stochastic algorithms, developing an online optimization technology, researching the transient optimization, and studying operation optimization of the integrated energy network are discussed.

The leakage process simulation of a Natural Gas Liquid (NGL) storage tank requires the simultaneous solution of the NGL’s pressure, temperature and phase state in the tank and across the leak hole. The methods available in the literature rarely consider the liquid/vapor phase transition of the NGL during such a process. This paper provides a comprehensive pressure-temperature-phase state method to solve this problem. With this method, the phase state of the NGL is predicted by a thermodynamic model based on the volume translated Peng-Robinson equation of state (VTPR EOS). The tank’s pressure and temperature are simulated according to the pressure-volume-temperature and isenthalpic expansion principles of the NGL. The pressure, temperature, leakage mass flow rate across the leak hole are calculated from an improved Homogeneous Non-Equilibrium Diener-Schmidt (HNE-DS) model and the isentropic expansion principle. In particular, the improved HNE-DS model removes the ideal gas assumption used in the original HNE-DS model by using a new compressibility factor developed from the VTPR EOS to replace the original one derived from the Clausius-Clayperon equation. Finally, a robust procedure of simultaneously solving the tank model and the leak hole model is proposed and the method is validated by experimental data. A variety of leakage cases demonstrates that this method is effective in simulating the dynamic leakage process of NGL tanks under critical and subcritical releasing conditions associated with vapor/liquid phase change.