Volume 08: Proceedings of Applied Energy Symposium: MIT A+B, United States, 2020

Optimization of Gas Loss and CO2 Emission During Disruption on a Natural Gas Network Scholastica N. Emenike, Duabari S. Aziaka


It was predicted in 2012 that the global demand for energy over a period of 28years (2012-2040) will increase by 48%. This will raise the total global energy consumption from 549 quadrillion British thermal units (Btu) in 2012 to 815 quadrillion Btu by 2040. As a strategic player in the energy mix, a reduction in the emission of CO2 to the environment from the natural gas network will result in environmental and cost savings. Although several researchers have alluded various opportunities associated with renewable energy feedstocks and have examined various strategies for optimized energy supply, the possible structural adjustments to gas infrastructure to align with future policies on climate will bring about a sustainable strategy for future economic growth. The motive of work is to investigate the problem associated with exogenous interruptions to a gas network resulting in loss of gas to the environment. The research also proposed a mitigation strategy for gas loss and emission reduction. To achieve this, a mixed integer linear programming (MILP) optimization model is developed that establishes a strategy for loss reduction in gas supply chain. Data from real case study have been accessed which enhances the applicability of the proposed model which was run on the GAMS 26.14 software using the CPLEX solver 12 in an intel ® core ™ i7 and a zero-optimality gap within reasonable solution time. The result obtained revealed a reduction from 555.1million kg of CO2 to 8.06 million kg of CO2 after optimization while still delivering on projected throughput. The proposed methodology can help natural gas operators to optimize performance considering disruption time estimation.

Keywords Natural gas supply chain, Emission, Mitigation, Relief pipeline, Optimization, Mixed integer linear programming, Loss reduction

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