Optimization of compressor stations

Kurz, Rainer

doi:10.33737/jgpps/112399

Cited by 4 publications

References 4 publications

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A model for booster station matching of gas turbine and gas compressor power under different ambient conditions

Tukur

Osigwe

2021

Heliyon

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Transporting natural gas across different locations require compressor stations to provide the pressure needed to keep the gas moving. This paper presents a model for matching the gas turbine and gas compressor power required under different environmental conditions to support the continuous gas transmission across other locations. The trans-Saharan gas pipeline (TSGP) project proposed to transport gas from Nigeria to Algeria has been used as a case study in this paper. The TSGP project is a Nigerian Government initiative to rejig its gas development and transportation infrastructure to meet its internal and external market demand. The numerical method used in this paper integrates the effect of the ambient temperature in the power matching of the gas turbine and gas compressors. There are 18 compressor stations across the TSGP network, and compressor station 2 is used as the reference point. The daily temperature fluctuation is segmented into hours of the day, emphasising considerable ambient temperature variation at 3:00 h, 9:00 h, 15:00 h. One benefit of the model against others in the open literature is accounting for changes in the ambient temperature along the pipeline network and gas compression stations. Accounting for changes in ambient temperature provides accuracy to near real-life operational experience for gas distribution via pipelines. The model also accounts for variations in turbine entry temperature (TET) to compensate for changes in the ambient conditions to meet the power requirements of the gas turbine and the gas compressor. The results show that for every 1% increase in ambient temperature, a 3.5% increase in power is required to drive the gas compressor and a 1% decrease in gas turbine output power. The effect of the 1% increase in ambient would require a 3.5% increase in TET to meet both the gas turbine and gas compressor requirement.

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A model for booster station matching of gas turbine and gas compressor power under different ambient conditions

Tukur

Osigwe

2021

Heliyon

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Gas Turbine Compressor Configuration Analysis for Production and Efficiency Optimization at PT Saka Indonesia Pangkah Ltd.

Afandy

Ramadhani²,

Biyanto

2021

IOP Conf. Ser.: Earth Environ. Sci.

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Gas Turbine Compressors are used by Saka Indonesia Pangkah Ltd. in upstream oil and gas facilities either to boost hydrocarbon products to downstream facilities or to lift liquid hydrocarbon as a common artificial method. As production rate declining leads to gas supply deficiency to the compressors, the operating point move to surge line away from the best efficiency point. Gas feed shortage affecting the compressor’s performance which contributed to head and flow capacity. This condition is then calculated and simulated using UNISIM Design Simulator to get optimum configuration results. The simulation was performed at the same gas turbine shaft power output of each compressor. Two cases of centrifugal compressors configuration with different functions and performance are studied. Due to process dynamic conditions, constraint parameter is considered as per desired operating point. This paper also analyses techno-economic aspects between individual and serial pipelines arrangement of the two compressors by evaluating operational data and design calculation. Subsequently, this study produces assessment observations associated with the compressor performance both in individual and serial configuration and eventually analyses the rate of fuel consumption in the gas turbines as the main driver. The case study shows serial arrangement between MPC-1 and GLC with same gas turbine shaft power as individual configuration can reduce fuel consumption up to 47 kg/hr. It saves as much as USD 7,569.96 per day at low demand and USD 7,569.96 at high-demand cases.

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Modeling Power Constraints Using Maps and Field Data in Optimization Problems for Gas Transportation Systems

Allen¹

2022

Journal of Engineering for Gas Turbines and Power

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Gas transmission networks have been and continue to be the most efficient method for transporting natural gas. As Hydrogen begins to emerge as one possible solution of renewable energy and starts mixing into gas networks, now more than ever, efficient operation is paramount. Part of the efficient pipeline operation puzzle is knowing how much power is available at a given compressor station, which constrains the head and flow that can be produced. This paper derives and implements driver constraints relating to gas pipeline optimization problems such as throughput maximization and compressor station power minimization at the pipeline level. In the literature the driver is often neglected in implementations of pipeline optimization problems. Often, only the compressor map is considered during the optimization procedure. In this work we develop the necessary physical relations and constraints between the gas compressor and driver. The addition of these constraints ensures that solutions are not only bounded by surge and stonewall curves as well as compressor speed, but also by available power from the driver given current ambient conditions. We also derive a method to fit constraints to observed data. The modified optimization problem results in more accurate solutions of pipeline optimization problems, giving operators more accurate data with which to make business decisions and operate pipelines.

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Optimization of compressor stations

Cited by 4 publications

References 4 publications

A model for booster station matching of gas turbine and gas compressor power under different ambient conditions

A model for booster station matching of gas turbine and gas compressor power under different ambient conditions

Gas Turbine Compressor Configuration Analysis for Production and Efficiency Optimization at PT Saka Indonesia Pangkah Ltd.

Modeling Power Constraints Using Maps and Field Data in Optimization Problems for Gas Transportation Systems

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