Optimization of capacity expansion planning for gas transportation networks

This paper presents techniques for solving the problem of minimizing investment costs on an existing gas transportation network. The goal of this program is to find, first, the optimal location of pipeline segments to be reinforced and, second, the optimal sizes (among a discrete commercial list of diameters) under the constraint of satisfaction of demands with high enough pressure for all users.The paper develops new heuristics for solving this large-scale integer NLP problem, based on a two phases approach. The first one solves a continuous relaxation of the problem. A generalized potential formulation of the gas transportation networks including valves and compressor stations is introduced in order to find an initial point of the optimization solver. Phase two consists in choosing discrete values of diameters only among the set of pipes that have been reinforced in the continuous relaxation. A Branch & Bound scheme is then applied to a limited number of values in order to generate good solutions with reasonable computational effort on real-world applications.