Optimizing natural gas pipeline transmission with nonuniform elevation: A new initialization approach

Abstract

In this paper, we develop an iterative piecewise linear approximation approach with a novel initialization method to solve natural gas pipeline transmission problems with the nonuniform network elevation. Previous approaches, such as energy minimization methods, cannot be applied to solve problems with the nonuniform network elevation because they exclude pressure range constraints, and thus provide solutions far from optimum. We propose a new initialization model that considers pressure range constraints and improves the optimality of the solutions and the computational efficiency. Furthermore, we extend the energy minimization methods and provide the necessary conditions under which the extended methods operate in networks with the nonuniform elevation. We test the performances of the methods with previously reported pipeline networks from the literature, with the open data set GasLib, and with our industrial collaborator. The initialization approach is shown to be more efficient than the method with fixed initial breakpoints. The newly proposed initialization approach generates solutions with a higher accuracy than the extended energy minimization methods, especially in large‐size networks. The proposed method has been applied to natural gas transmission planning by the China National Petroleum Corporation and has brought a direct profit increase of 330 million U.S. dollars in 2015‐2017.

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“…Therefore, the second term of (A.6) is constant, and the terms in (A.7) including the pipeline height h are less challengeable. One can refer to [75]- [77] for modeling and solving the gas dynamic models with inclined pipelines.…”

“…With the same sequence, a primal-dual IPM with the Newton-Raphson approach are employed in [156], and the MINOS solver is utilized in [172], considering the wind speed uncertainties [16]. The dynamic-state gas model is solved by SQP method [173], general purpose global optimization [67] or iterative algorithms [75], where the gas nonlinearities are relaxed into MILP to find a suitable integer variables, then NLP or SQP tackled the original formulation.…”

“…(1) In fact, during this conducted research, novel approaches are proposed to tackle the nonlinearity and non-convexity of the IEGS problems. For example, an iterative PLA algorithm is designed in [75] to dynamically update the breakpoints instead of the fixed ones. Comparing and/or adopting with such up-to-date studies, are our subsequent works.…”