(398a) Full-Scale Simulation, Energy and Environmental Analysis of an Actual LNG Chain

Authors: 
Katebah, M., Qatar University
Hussein, M., Qatar University
Shazed, A. R., Qatar University
Bouabidi, Z., Qatar University
Al-Hajri, A., Qatargas
Al-Musleh, E., Qatar University
Full-scale Simulation, Energy and Environmental Analysis of an Actual LNG Chain

Mary A. Katebah1, Mohamad M. Hussein1, Abdur Rahman Shazed1, Zineb Bouabidi1, Abdulla Al-Hajri2, and Easa I. Al-musleh1*

1Chemical Engineering Department, Qatar University

2Qatargas Operating Company

*Corresponding author. Tel. +974 44034148. E-mail address: e.almusleh@qu.edu.qa (E. Al-musleh)

Natural gas (NG) is predominating the energy market as the main energy source worldwide, where it supplies over 20% of the total global energy demand.1 The U.S. Energy Information Administration predicts that NG production will continue to grow from 83 to 93 billion cubic feet per day between 2018-2020.2 This is credited to its lower carbon intensity and costs, compared to alternative fossil fuels. NG can be supplied to consumers by either pipeline transmission or as liquefied natural gas (LNG). While the former might be attractive over short distances, it offers limited capacity and flexibility compared to LNG.3 Liquefaction allows for the storage and transportation of terawatt-hour amounts of NG at low pressures, making it the most cost-effective method of supplying NG to end-users over long distances. However, pre-treating and liquefying the NG involves complex energy-intensive steps that produce significant amounts of CO2 and other harmful emissions (e.g. SOx, NOx, etc.). Additionally, LNG processes are associated with large quantities of water and waste discharges. Enhancing the efficiencies of the various units within the LNG chain is paramount in solving today’s global dual challenge: “more energy with less carbon”.4 Furthermore, it results in substantial benefits including more LNG production, lower environmental impact, and higher profit. Process modeling and simulation is one of the quickest, predictive and cost-efficient tools to optimize a process. To date, no rigorous, comprehensive and validated process simulation model in the public literature exists for an entire actual LNG supply chain.

Japan is the world’s largest importer, followed by China and South Korea.5 In this work, we have used ProMax® and Aspen Plus® software to develop a rigorous base-case simulation model for an entire existing Qatar-Japan LNG supply chain. This included the upstream processing, liquefaction, utilities, transportation and regasification units. Two modes of operation were considered: without and with LNG carrier/receiving terminal loadings, referred to as holding and loading modes, respectively. A detailed methodology for simulating all the units within the LNG chain was developed while respecting process constraints, fuel balance and all product specifications. This approach can be extended towards simulating similar technologies within the process systems engineering field, generally, and the LNG value chain, specifically. The model was based on an actual process in Qatar, and its predictions match actual published data with less than 2% discrepancy. Simulation results were used to quantify the total plant fuel consumption and generation during the holding and loading modes. This was conducted by taking into account every single equipment within the LNG chain, including pumps, compressors, turbines, and steam generators, to name a few.

The model was also used to analyze the chain’s performance through the first law of thermodynamics by calculating the energy efficiency of each unit, and their contribution to the chain’s overall efficiency. The study also included a thorough environmental analysis to quantify CO2, SOx, NOx emissions, in addition to process water and solid-waste discharge. Unlike the literature methodologies which utilize emission factors to quantify carbon dioxide emissions, rigorous simulation was used to obtain representative emission values. The study was concluded by assessing the relationship between the efficiency and environmental impact to highlight the areas that require further improvements. The model deemed to be a valuable tool that can serve as a basis for a plethora of reliable analyses and potential optimization studies.

References:

(1) Natural Gas. https://www.iea.org/topics/naturalgas/ (accessed Apr 1, 2019).

(2) Short-term Energy Outlook 2019. https://www.eia.gov/outlooks/steo/marketreview/natgas.php (accessed Apr 10, 2019).

(3) Patel, H.; Caswell, C.; Durr, C. North American LNG terminals: Options? Hydrocarb. Process. 2005, No. July, 45–49.

(4) BP Energy Outlook 2019 edition. https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdf... (accessed Apr 1, 2019).

(5) Shell LNG Outlook 2019. https://www.shell.com/promos/download-the-full-lng-2019/_jcr_content.str... (accessed Apr 1, 2019).

(6) EIA: U.S. LNG export capacity to more than double by the end of 2019. https://www.worldoil.com/news/2019/1/1/eia-us-lng-export-capacity-to-mor... (accessed Apr 1, 2019).