Through Each Arc Discharge Pressure Compressor

Units

 

V V

V v

V

V

V V

v V V V

V V V

V

V

^wu et al. [22] Cobos-Zaleta and Rios- Mercado [23]

Borraz-Sanchez and Rios-Mercado [4J Mora and Ulieru [24]

Rios-Mercado et al. [6]

^bbaspour et al. [18] "orraz-Sanchez and Rios-Mercado [7J ^hebouba et al. [29]

information system (GIS). Among investment projects with sequencing, budget and timing limitations, the model made a trade-off to maximize the expected net present value (NPV) and minimize the variance among NPVs. This model consid­ers both the revenues and cost while selecting the best expansion project with the aim of taking a decision support system to present the revenue of serving new cus­tomers and related costs to constructions as well as considering the uncertainties. It was solved by rollout heuristic algorithms to improve the solution quality. In this case, GIS helps to identify opportunities in potential network expansion, data col­lection, and perception made because of the developed model. Kabirian and Hemmati [16| developed a model with the aim of least discounted operating and capital cost to plan for the natural gas transmission network.

Minimizing the Cash-Out Penalties of the Shipper

In drawing a contract between the shipper and a pipeline company to deliver a cer­tain volume of gas among several points, a problem may occur in marketing natural gas because of the differences among the promised amount of gas and the real amount actually delivered along a transmission network. In those cases where imbalances occur, pipeline companies penalize shippers by imposing a cash-out penalty policy, which is a function of daily imbalance. Therefore, the problem, which should be solved optimally, is making decisions for shippers to minimize their incurred penalty by carrying out their daily imbalances [25].

Table 19.4 presents a summary for some of the reviewed papers that have focused on optimization problems in the natural gas industry.