Optimal Operation of a Multi Source Multi Delivery Natural Gas Transmission Pipeline Network

2018 ◽  
Vol 13 (3) ◽  
Author(s):  
Dr. Adarsh Kumar Arya ◽  
Dr. Shrihari Honwad

Abstract Transportation of natural gas from gathering station to consumption centers is done through complex gas pipeline network system. The huge cost involved in transporting natural gas has made pipeline optimization of increased interest in natural gas pipeline industries. In the present work a lesser known application of Ant Colony in pipeline optimization, has been implemented in a real gas pipeline network. The objective chosen is to minimize the fuel consumption in a gas pipeline network consisting of seven compressors. Pressures at forty-five nodes are chosen as the decision variables. Results of Ant Colony Optimization (ACO) have been compared with those of GAMS that utilizes ‘Generalized gradient principles’ for optimization. Our results utilizing ACO show significant improvement in fuel consumption reductions. Similar procedures can be adopted by researchers and pipeline managers to help pipeline operators in fixing up the pressures at different nodes so as the fuel consumption in compressors gets minimized.

Author(s):  
Jill Gilmour

A software package which optimizes natural gas pipeline operation for minimum fuel consumption is in use on a commercial transmission pipeline. This Optimization Program has resulted in pipeline fuel savings in daily pipeline operation. In addition, the effect of a new compressor/turbine unit on the pipeline system as a whole can be accurately and easily quantified through use of the Optimization Program before the unit is even installed. The results from one turbine replacement study showed the total system fuel consumption and operating hours predicted for each unit were not directly related to a high turbine efficiency. This paper describes the simulation techniques used for the gas turbine and compressor modeling. The methodology behind the system-wide optimization is also provided, along with a detailed discussion of the program application to gas turbine and compressor replacement studies.


CivilEng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 87-119
Author(s):  
Sk Kafi Ahmed ◽  
Dr. Golam Kabir

The main aim of this study is to identify the most important natural gas pipeline failure causes and interrelation analysis. In this research, the rough analytic hierarchy process (Rough-AHP) is used to identify the natural gas pipeline failure causes rank order. Then a combination of rough decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) method is applied to generate the level of importance. The comparison of traditional DEMATEL and Rough-DEMATEL are also performed to establish the cause-effect interrelation diagram. Finally, the Bayesian Belief Network (BBN) is combined with Rough DEMATEL and ISM to identify the interrelation analysis among the most crucial failure causes. As a result, the energy supply company and government policymaker can take necessary safety plan and improve the operation. The main outcome of this study is to improve the security management and reduce the potential failure risks.


2011 ◽  
Vol 361-363 ◽  
pp. 966-973
Author(s):  
Debebe Woldeyohannes Abraham ◽  
Mohd Amin bin Abd Majid

The increase in demand for natural gas in different sectors attracted different scholars in optimizing the operation and configurations of natural gas pipeline network (NGPN) systems. Even though there have been reports regarding the attempts of solutions for optimizing NGPN problems, the issues of NGPN regarding energy minimizations are not fully address yet. This paper proposed robust solution for NGPN system energy consumption minimization at compressor stations based on analogical approach. The analogies between NGPN system and inventory model were observed and applied in the analysis of steady state NGPN system. The proposed technique is based on the inventory model to find optimal operations for natural gas pipeline network system. The method for the determination of the optimal pressures was efficient and handled the non-linearity that occurs on both objective and the constraint equations. Results on a gunbarrel NGPN showed the proposed method assisted in determining the discharge and suction pressures to minimized energy consumption at compressor stations.


Author(s):  
Adarsh Kumar Arya

AbstractThe enormous cost of transporting oil and gas through pipelines and the operational benefits that the industry receives through optimization has incited analysts for decades to find optimization strategies that help pipeline managers operate pipeline grids with the least expense. The paper aims to minimize the pipeline grids' operating costs using an ant colony optimization strategy. The article constructs a multi-objective modeling framework for a natural gas pipeline grid based on data from the French gas pipeline network corporation 'Gaz De France,' using pipeline and compressor hydraulics. The gas pipeline grid comprises seven gas supply nodes and nineteen gas distribution centers. Seven compressor stations provided at various locations on the pipeline route raise the gas pressure. Two competing objectives of reducing fuel usage in compressors and increasing throughput at distribution centers are acknowledged to reduce the pipeline's operating cost. The 'multi-objective ant colony optimization (MOACO)' approach is implemented to the pipeline transportation model to reduce the natural gas pipeline grid's operating cost. The process variables include the amount of gas flowing through the pipe and the pressure at pipe nodes. This method provides the optimum solution for each fuel consumption level on each compressor, and it does so by producing a Pareto front for each of the nineteen gas distribution points. The blueprints of the methodology used and the findings collected intend to guide pipeline managers and select the best of the most preferred solutions.


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