Reducing energy consumption for electrical gas preheating processes

Jedlikowski, Andrzej; Englart, Sebastian; Cepiński, Wojciech; Badura, Marek; Sayegh, Marderos Ara

doi:10.1016/j.tsep.2020.100600

Cited by 9 publications

(4 citation statements)

References 30 publications

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“…Apie DSS slėgio mažinimo proceso metu galimybę atgauti energiją, naudojant turboekspanderius (TE), atlikta gana daug tyrimų (Jedlikowski et al, 2020;Khanmohammadi & Saadat-Targhi, 2019). Taip pat šie prietaisai yra naudojami ir analizuojami kitų šalių DSS, tiriami jų ir izoentalpiškai veikiančių slėgio reguliatorių skirtumai.…”

Section: įVadasunclassified

Research of Methods for Improving Energy Efficiency and Emissions Reduction in Distribution Station of Natural Gas Transmission Network

Tučkus,

Rogoža

2023

Science - Future of Lithuania

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The global energy crisis, rising energy demand and climate warming make it imperative to find ways to recover energy that is not being put to beneficial use, to reduce primary and final energy consumption, and to reduce emissions. An important part of Lithuania’s energy sector is the natural gas sector and its transmission network, including the gas distribution stations (GDS). It is the GDS that has an unexploited potential for energy recovery, as the gas pressure is reduced through the use of gas pressure regulators, where the potential energy in the highpressure gas is not utilized in a useful way, and the necessary heating of natural gas is carried out through the use of natural gas boilers, with additional environmental pollution. The aim of the study is to analyse the gas distribution station, to find the areas of the station where potential energy is not being used and the environment is being polluted, and to propose reasonable solutions. Following a literature review, alternative technical solutions are selected: turbine-expander, conversion of the gas preheating system from gas boilers to a geothermal heat pump, use of solar collectors, photovoltaic solar cells. In order to assess the potential of technological solutions to improve the efficiency of the DSS and reduce emissions, a multi-criteria analysis of the proposed solutions is carried out, where the measures under evaluation are analysed in energy, economic and environmental terms. The energy assessment analyses the energy consumption, the economic assessment calculates the net present value (NPV) of the investment for each solution and the environmental assessment examines the environmental impact of the proposed measures over their life cycle. Based on the results of the multicriteria analysis, the systems best suited to the object of study (GDS) are recommended.

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Section: įVadasunclassified

Research of Methods for Improving Energy Efficiency and Emissions Reduction in Distribution Station of Natural Gas Transmission Network

Tučkus,

Rogoža

2023

Science - Future of Lithuania

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“…• Spearman's rank correlation coefficient is a measure of rank correlation, that is the statistical dependence between the rankings of two variables and is given by the Pearson correlation coefficient of the two ranks (2). It assesses how well the relationship between two variables can be described using a monotonic function (whether linear or not) and it's also less sensitive to strong outliers than the Pearson correlation [14].…”

Section: Correlation Coefficientsmentioning

confidence: 99%

“…CGSs perform many tasks within this infrastructure: fiscal measurement, pressure reduction and control, odorant injection and gas preheating to avoid dangerous undercooling downstream of the valve throttling step. This process is essential to avoid the gas reaching low temperatures that could compromise the operation of the CGS throttling valves, or that could lead to hydrate formation in the distribution network pipes [2]. The thermal energy consumption of a CGS to maintain the gas temperature above zero degrees plus a safety factor is a significant part of the energy balance of these plants and very often it means the use of part of the NG flow itself by gas boiler systems .…”

Section: Introductionmentioning

confidence: 99%

“…The results indicate that the developed machine learning methods exhibit high accuracy in calculations over a wide range of gas mixtures and input properties. [6] Englart et al [7], [8] propose an auxiliary system based on renewable energy and heat pumps to support or completely replace traditional gas boilers. Results show that it is possible to reduce consumption by up to about one third, for the applications considered in the case study.…”

Section: Introductionmentioning

confidence: 99%

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Data-driven modelling for gas consumption prediction at City Gate Stations

Cheli

Meazzini²,

Busi³

et al. 2022

J. Phys.: Conf. Ser.

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City Gate Stations (CGS) are critical elements of Natural Gas (NG) distribution systems, as they connect national high-pressure transmission networks with local low-pressure networks. One of their main tasks is to pre-heat the gas to avoid dangerous sub-cooling due to the Joule-Thompson effect after the pressure reduction stage. For this process, significant amounts of thermal energy are required, usually obtained by burning part of the gas flow rate. This work aims to develop a data-driven model that will serve as a tool to predict and monitor the thermal consumption of the CGS. The plant chosen as a case study for this activity is in a region of central Italy. A Multiple Linear Regression (MLR) model is developed and trained, and its predictive performance is evaluated. The model results achieved an accuracy of over 95% for the coefficient of determination. The method makes it possible to create a baseline consumption model and evaluate the performance of the CGS over time using the CUSUM technique to find variations between actual and modelled gas consumption, being an essential tool for monitoring the effectiveness of the NG preheating system.

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