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Stochastic pooling problem for natural gas production network design and operation under uncertainty
Authors:Xiang Li  Emre Armagan  Asgeir Tomasgard  Paul I Barton
Affiliation:1. Dept. of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139;2. Dept. of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139;3. Dept. of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Trondheim 7491, Norway
Abstract:Product quality and uncertainty are two important issues in the design and operation of natural gas production networks. This paper presents a stochastic pooling problem optimization formulation to address these two issues, where the qualities of the flows in the system are described with a pooling model and the uncertainty in the system is handled with a multi‐scenario, two‐stage stochastic recourse approach. In addition, multi‐objective problems are handled via a hierarchical optimization approach. The advantages of the proposed formulation are demonstrated with case studies involving an example system based on Haverly's pooling problem and a real industrial system. The stochastic pooling problem is a potentially large‐scale nonconvex Mixed‐Integer Nonlinear Program (MINLP), and a rigorous decomposition method developed recently is used to solve this problem. A computational study demonstrates the advantage of the decomposition method over a state‐of‐the‐art branch‐and‐reduce global optimizer, BARON. © 2010 American Institute of Chemical Engineers AIChE J, 2011
Keywords:natural gas production network  design and operation under uncertainty  pooling problem  stochastic programming  nonconvex MINLP
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