51. Optimal Control for Scheduling and Pricing Intra-day Natural Gas Transport on Pipeline Networks
- Author
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Aleksandr Beylin, Xindi Li, Aleksandr M. Rudkevich, Kaarthik Sundar, and Anatoly Zlotnik
- Subjects
Mathematical optimization ,Partial differential equation ,Computer science ,business.industry ,Scheduling (production processes) ,Compressor station ,Fluid Dynamics (physics.flu-dyn) ,FOS: Physical sciences ,Physics - Fluid Dynamics ,02 engineering and technology ,Gas dynamics ,021001 nanoscience & nanotechnology ,Optimal control ,Nonlinear system ,020401 chemical engineering ,Natural gas ,Optimization and Control (math.OC) ,FOS: Mathematics ,0204 chemical engineering ,Temporal discretization ,0210 nano-technology ,business ,Mathematics - Optimization and Control ,Gas compressor ,Differential algebraic equation - Abstract
We formulate an economic optimal control problem for transport of natural gas over a large-scale transmission pipeline network under transient flow conditions. The objective is to maximize economic welfare for users of the pipeline system, who provide time-dependent price and quantity bids to purchase or supply gas at metered locations on a system with time-varying injections, withdrawals, and control actions of compressors and regulators. Our formulation ensures that pipeline hydraulic limitations, compressor station constraints, operational factors, and pre-existing contracts for gas transport are satisfied. A pipeline is modeled as a metric graph with gas dynamics partial differential equations on edges and coupling conditions at the nodes. These dynamic constraints are reduced using lumped elements to a sparse nonlinear differential algebraic equation system. A highly efficient temporal discretization scheme for time-periodic formulations is introduced, which we extend to develop a rolling-horizon model-predictive control scheme. We apply the computational methodology to a pipeline system test network case study. In addition to the physical flow and compressor control solution, the optimization yields dual functions that we interpret as the time-dependent economic values of gas at each location in the network., Comment: To appear in Proc. 58th IEEE Conference on Decision and Control
- Published
- 2019
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