Evaluating Benefits of Rolling Horizon Model Predictive Control for Intraday Scheduling of a Natural Gas Pipeline Market

This paper analyzes a mechanism for clearing a physical market for intra-day schedules of receipts and deliveries of a natural gas pipeline. The Gas Balancing Market (GBM) is implemented to trade deviations from previously confirmed ratable nominations by solving a rolling horizon model predictive control (MPC) optimization formulation. The GBM mechanism operates by accepting quantity/price offers and bids from sellers and buyers of gas and producing an economically optimal schedule while guaranteeing its physical feasibility. The GBM’s solution engine is based on a strict mathematical representation of engineering factors of transient pipeline hydraulics and compressor station operations. The GBM’s settlement of cleared transactions is based on Locational Trade Values (LTVs) of natural gas that are fully consistent with the physics of energy flow. In this paper we provide numerical results of simulating a hypothetical GBM market operation using historical SCADA data for an actual pipeline system operation during the Polar Vortex period of February – March 2014. Based on these simulations, we quantify the potential deliverability and economic benefits of the GBM utilizing transient optimization of pipeline operations