Modeling Power Constraints Using Maps and Field Data in Optimization Problems for Gas Transportation Systems

Abstract

Gas transmission networks have been and continue to be the most efficient method for transporting natural gas. As Hydrogen begins to emerge as one possible solution of renewable energy and starts mixing into gas networks, now more than ever, efficient operation is paramount. Part of the efficient pipeline operation puzzle is knowing how much power is available at a given compressor station, which constrains the head and flow that can be produced. This paper derives and implements driver constraints relating to gas pipeline optimization problems such as throughput maximization and compressor station power minimization at the pipeline level. In the literature the driver is often neglected in implementations of pipeline optimization problems. Often, only the compressor map is considered during the optimization procedure. In this work we develop the necessary physical relations and constraints between the gas compressor and driver. The addition of these constraints ensures that solutions are not only bounded by surge and stonewall curves as well as compressor speed, but also by available power from the driver given current ambient conditions. We also derive a method to fit constraints to observed data. The modified optimization problem results in more accurate solutions of pipeline optimization problems, giving operators more accurate data with which to make business decisions and operate pipelines.