Session: 20-06 Optimization I - Upstream O&G Operation & Design

Paper Number: 126805

126805 - Techno-Economic Optimisation of Gas Compressor Station Location As a Decision Variable 

An efficient and reliable natural gas transportation will require the lowest capital and operating expenditures over its lifecycle. To attain these conditions, it is imperative for the designers and investors to estimate the number of compressor stations that are needed along the pipeline route. More so is the need to determine their optimised locations at various pipeline segments along the pipeline. This study considers the techno-economic optimisation of the compressor station and pipeline system, making up the proposed Trans-Saharan Gas Pipeline (TSGP) project. A SIMULINK model is developed in terms of the techno-economic and environmental risk analysis (TERA) framework. The model is incorporated with an optimiser that enables an economic analysis of the TERA framework. The inclusion of the optimiser affects the outcome of the TERA in terms of the lifecycle cost.

The mathematical optimisation utilised by the optimisation tool is based on a gradient descent optimisation method with a sequential quadratic programming algorithm. The optimisation problems are formulated considering the compressor station location as the decision variable. The lifecycle cost of the compressor stations and pipeline system is the objective function. A scenarios-based techno-economic optimisation study is performed to mimic the standard compressor station and pipeline system network configurations in the real world. Sensitivity analyses were carried out to determine the effect of the discount rate on the net present value.

The outcome of the analyses reveals that the results obtained are consistent with the genetic algorithm optimisation procedure. They show the same number of compressor station locations and lifecycle cost estimation for each scenario. The results show 12 numbers of compressor station locations along the pipeline route with a reduction in the lifecycle cost from $22.24 billion in the baseline case to $19.36 billion in scenario 4 assuming a discount rate of 15%. The optimised compressor station locations are at 1, 38, 76, 113, 150, 186, 222, 260, 296, 332, 368, and 408 segments of the pipeline. The results obtained for the net present value analysis revealed that at a 15% discount rate scenario 4 has the highest net present value of $28.77 billion among the considered scenarios. Findings on the sensitivity analyses of the scenarios-based techno-economic optimisation show investors' preference for scenario 4 with the highest net present value and lowest lifecycle cost among all the scenarios. Hence, this study shows the potential of the TERA modelling and optimisation method utilized in this research in guiding decision-makers on the ultimate selection of engine configurations that will give the optimal lifecycle cost at the optimised compressor station locations along the pipeline route.

Presenting Author: Oluwatayo Babatope Ojo Cranfield University

Presenting Author Biography: Oluwatayo Babatope Ojo obtained his Bachelor of Science (Honours) degree in Mechanical Engineering from the University of Lagos (UNILAG), Nigeria. He returned to UNILAG for his Master of Science degree in Mechanical Engineering with a specialization in thermo-fluid option. Oluwatayo lectures at UNILAG before moving to Cranfield University, United Kingdom to pursue his PhD in Mechanical Engineering focusing on gas turbine application in pipelines. He recently completed his PhD program and is currently performing research as the outcome of his doctorate studies.

Authors:

Oluwatayo Babatope Ojo Cranfield University
Uyioghosa Igie Cranfield University
Pericles Pilidis Cranfield University