Abstract
Abstract
This paper presents a chance-constrained multiobjective optimization framework for the optimal design of gas transmission lines (GTL) in which the total annual cost (TAC) and operability index as the two conflicting objectives are minimized and maximized, respectively. The delivery flow rates are assumed to be random Gaussian variables since the customer demand can be uncertain in the design phase. Accordingly, a robustness measure is introduced in order to quantify the risk of the final design against delivery uncertainties. The proposed model is capable of determining the optimum design variables including the pipeline diameter and thickness along with the location of the compressor stations and their capacities. The effects of design parameters including pipe thickness, pipe diameter and customer demand uncertainty level on the design of a GTL are investigated from economic as well as the robustness point of view. It is shown that the design with the highest nominal pipe size (NPS) and least thickness possible is the optimal design when TAC is considered as the objective function while the design with both the highest NPS and thickness possible shows the highest robustness and flexibility against delivery demand fluctuations. The final decision about the optimal NPS and thickness should be made on the basis of the expected uncertainty of the customer future demand. The results also can quantitatively suggest the required over-design factor that must be considered in the design phase of the GTL for various compressor stations.
Subject
Modelling and Simulation,General Chemical Engineering
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