Value chain optimization in large scale gas network considering elevation and transmission direction

A large Chinese energy company operates the largest gas pipe network in China, spanning some 40 thousand kilometres of pipelines and encompassing 119 compressor stations across 650 cities. The company determines the quantity of gas purchased or extracted from various gas sources and transmits them to demand nodes across the network by controlling the pressure levels of the compression stations. The whole process is the major value chain of the company. Because of large seasonal change in the demand, the transmission directions of the pipes are also part of the operational problem. Transmission of gas along pipes need to follow some complex physical relations between pressure and flow quantity, typically captured using the famous Weymouth equation. Because of the large geographic spread of the network, elevation cannot be ignored in our case. We use a modified Weymouth equation with elevation. In this equation, the coefficients in front of the pressure terms of the start node and end node are different. Since the transmission direction is part of the decision, the resulting problem is a large-scale, non-linear, non-convex mixed integer problem. The company solves this single-period problem and uses the solution as the operation basis for the next month. We propose an algorithm based on sequential linear programming, which we test on the company's network. Numeric experiments demonstrate the method's efficiency in generating high-quality solutions for the optimization problem.