Life cycle assessment (LCA) of liquefied natural gas (LNG) and its environmental impact as a low carbon energy source

[Abstract]: A life cycle assessment is an environmental management methodology documented by the International Standards Organization (ISO2006) for researching the impact a product has on the environment. Liquefied natural gas is a product contributing to the emission of greenhouse gases such as carbon dioxide, methane and nitrous oxide. These emissions can be minimized by analysis of its source and adopting appropriate process technology throughout the product lifecycle. Natural gas for many years was regarded as a volatile waste product within the oil and coal industries, and was subsequently vented into the atmosphere resulting in pollution. Natural gas is now accepted as a source of low carbon energy assisting the transition from heavy fuels to renewable energy. Liquefying the natural gas has proved to be an economic method for transporting this energy to the market place where pipeline infrastructure is unavailable. Australia has large resources of natural gas in conventional off-shore wells and underground coal-seams. Demand for energy security has positioned Australia to capitalize on its natural resources and supply low carbon energy to fuel economic growth in Asia. The production of liquefied natural gas in Australia is forecast to grow above one hundred million tons per annum within the next five years, becoming the world’s second largest supplier behind Qatar. Natural gas has a calorific value of approximately 40 MJ/m3, with greater than eighty five percent Methane content. Liquefied natural gas is produced by cooling natural gas to its boiling point of minus 161°C, becoming 1/600th its original volume. It is stored in insulated tanks at normal atmospheric pressure before being loaded on-board ships and transported to market. Ships used to transport liquefied natural gas range in size between 135,000m³ and 265,000m³. Once delivered to market, liquefied natural gas is used for cryogenic storage and re-gasified for domestic gas supply, power generation and industrial manufacturing. This study assesses the environmental impact of liquefied natural gas during liquefaction, shipping and re-gasification using a life cycle assessment approach. Greenhouse gas emissions are quantified in the form of carbon dioxide equivalent emissions and recommendations are made for process and technology improvements. Liquefaction of natural gas produces emissions during the removal of carbon dioxide from inflow gas, fuel used in gas turbines compressors and fuel used by power generation turbines. Shipping liquefied natural gas generates emissions from fuel used by the ships engines and re-gasification generates emissions from fuel used to operate pumps and power turbines. A thirty eight percent improvement in efficiency has been identified in the lifecycle of liquefied natural gas from Australia compared to global production, resulting in only six and a half grams of carbon dioxide equivalent emissions per mega Joule of energy delivered to Asian markets

Evaluation of an Open-source Chemical Process Simulator Using a Plant-wide Oil and Gas Separation Plant Flowsheet Model as Basis

In this paper, a detailed evaluation of the open source process simulator DWSIM is presented. Using a previously published simulation model of an oil and gas separation plant, the results obtained with DWSIM are compared to a commercial process simulator widely used in the industry. The modelled flow scheme comprises a vast number of unit operations including separators (flash vessels), valves, splitters, mixers, compressors, heat exchangers, pumps and recycles (tear streams). The results obtained with DWSIM both for characterization of the inlet fluid as well as for a single operating state for the entire process, compare very well with the data obtained using a commercial tool. A rigorous comparison is made and generally, compared results are within 1% in deviation with a few exceptions. Further, an elaborate comparison is made for over 90 simulations with different settings where 10 independent variables are randomly varied over a wide range. Again, good agreement is found between the two tools. The results are very encouraging and provide fidelity in the use of the investigated open source process simulation tools in a professional environment

Robust simulation and optimization methods for natural gas liquefaction processes

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 313-324).Natural gas is one of the world's leading sources of fuel in terms of both global production and consumption. The abundance of reserves that may be developed at relatively low cost, paired with escalating societal and regulatory pressures to harness low carbon fuels, situates natural gas in a position of growing importance to the global energy landscape. However, the nonuniform distribution of readily-developable natural gas sources around the world necessitates the existence of an international gas market that can serve those regions without reasonable access to reserves. International transmission of natural gas via pipeline is generally cost-prohibitive beyond around two thousand miles, and so suppliers instead turn to the production of liquefied natural gas (LNG) to yield a tradable commodity. While the production of LNG is by no means a new technology, it has not occupied a dominant role in the gas trade to date. However, significant growth in LNG exports has been observed within the last few years, and this trend is expected to continue as major new liquefaction operations have and continue to become operational worldwide. Liquefaction of natural gas is an energy-intensive process requiring specialized cryogenic equipment, and is therefore expensive both in terms of operating and capital costs. However, optimization of liquefaction processes is greatly complicated by the inherently complex thermodynamic behavior of process streams that simultaneously change phase and exchange heat at closely-matched cryogenic temperatures. The determination of optimal conditions for a given process will also generally be nontransferable information between LNG plants, as both the specifics of design (e.g. heat exchanger size and configuration) and the operation (e.g. source gas composition) may have significantly variability between sites. Rigorous evaluation of process concepts for new production facilities is also challenging to perform, as economic objectives must be optimized in the presence of constraints involving equipment size and safety precautions even in the initial design phase. The absence of reliable and versatile software to perform such tasks was the impetus for this thesis project. To address these challenging problems, the aim of this thesis was to develop new models, methods and algorithms for robust liquefaction process simulation and optimization, and to synthesize these advances into reliable and versatile software. Recent advances in the sensitivity analysis of nondifferentiable functions provided an advantageous foundation for the development of physically-informed yet compact process models that could be embedded in established simulation and optimization algorithms with strong convergence properties. Within this framework, a nonsmooth model for the core unit operation in all industrially-relevant liquefaction processes, the multi-stream heat exchanger, was first formulated. The initial multistream heat exchanger model was then augmented to detect and handle internal phase transitions, and an extension of a classic vapor-liquid equilibrium model was proposed to account for the potential existence of solutions in single-phase regimes, all through the use of additional nonsmooth equations. While these initial advances enabled the simulation of liquefaction processes under the conditions of simple, idealized thermodynamic models, it became apparent that these methods would be unable to handle calculations involving nonideal thermophysical property models reliably. To this end, robust nonsmooth extensions of the celebrated inside-out algorithms were developed. These algorithms allow for challenging phase equilibrium calculations to be performed successfully even in the absence of knowledge about the phase regime of the solution, as is the case when model parameters are chosen by a simulation or optimization algorithm. However, this still was not enough to equip realistic liquefaction process models with a completely reliable thermodynamics package, and so new nonsmooth algorithms were designed for the reasonable extrapolation of density from an equation of state under conditions where a given phase does not exist. This procedure greatly enhanced the ability of the nonsmooth inside-out algorithms to converge to physical solutions for mixtures at very high temperature and pressure. These models and submodels were then integrated into a flowsheeting framework to perform realistic simulations of natural gas liquefaction processes robustly, efficiently and with extremely high accuracy. A reliable optimization strategy using an interior-point method and the nonsmooth process models was then developed for complex problem formulations that rigorously minimize thermodynamic irreversibilities. This approach significantly outperforms other strategies proposed in the literature or implemented in commercial software in terms of the ease of initialization, convergence rate and quality of solutions found. The performance observed and results obtained suggest that modeling and optimizing such processes using nondifferentiable models and appropriate sensitivity analysis techniques is a promising new approach to these challenging problems. Indeed, while liquefaction processes motivated this thesis, the majority of the methods described herein are applicable in general to processes with complex thermodynamic or heat transfer considerations embedded. It is conceivable that these models and algorithms could therefore inform a new, robust generation of process simulation and optimization software.by Harry Alexander James Watson.Ph. D

Process Efficiency Optimisation of Cascade LNG Process

The aimed of this thesis is to optimise the Cascade LNG process efficiency of 5 MTPA production capacity. The cascade process was modelled and simulated in Aspen HYSYS version 7.2 using Peng Robinson equation of state. The optimisation of cascade process was carried out from operation and design perspectives. It focused on two main cycles which are propane and ethylene refrigeration cycles as they are the main energy consumers of this process

Efficiency Enhancement for Natural Gas Liquefaction with CO₂ Capture and Sequestration through Cycles Innovation and Process Optimization

Liquefied natural gas (LNG) plants are energy intensive. As a result, the power plants operating these LNG plants emit high amounts of CO2. To mitigate global warming that is caused by the increase in atmospheric CO2, CO2 capture and sequestration (CCS) using amine absorption is proposed. However, the major challenge of implementing this CCS system is the associated power requirement, increasing power consumption by about 15-25%. Therefore, the main scope of this work is to tackle this challenge by minimizing CCS power consumption as well as that of the entire LNG plant though system integration and rigorous optimization. The power consumption of the LNG plant was reduced through improving the process of liquefaction itself. In this work, a genetic algorithm (GA) was used to optimize a propane pre-cooled mixed-refrigerant (C3-MR) LNG plant modeled using HYSYS software. An optimization platform coupling Matlab with HYSYS was developed. New refrigerant mixtures were found, with savings in power consumption as high as 13%. LNG plants optimization with variable natural gas feed compositions was addressed and the solution was proposed through applying robust optimization techniques, resulting in a robust refrigerant which can liquefy a range of natural gas feeds. The second approach for reducing the power consumption is through process integration and waste heat utilization in the integrated CCS system. Four waste heat sources and six potential uses were uncovered and evaluated using HYSYS software. The developed models were verified against experimental data from the literature with good agreement. Net available power enhancement in one of the proposed CCS configuration is 16% more than the conventional CCS configuration. To reduce the CO2 pressurization power into a well for enhanced oil recovery (EOR) applications, five CO2 pressurization methods were explored. New CO2 liquefaction cycles were developed and modeled using HYSYS software. One of the developed liquefaction cycles using NH3 as a refrigerant resulted in 5% less power consumption than the conventional multi-stage compression cycle. Finally, a new concept of providing the CO2 regeneration heat is proposed. The proposed concept is using a heat pump to provide the regeneration heat as well as process heat and CO2 liquefaction heat. Seven configurations of heat pumps integrated with CCS were developed. One of the heat pumps consumes 24% less power than the conventional system or 59% less total equivalent power demand than the conventional system with steam extraction and CO2 compression

Study of methane fuel for subsonic transport aircraft

The cost and performance were defined for commercial transport using liquid methane including its fuel system and the ground facility complex required for the processing and storage of methane. A cost and performance comparison was made with Jet A and hydrogen powered aircraft of the same payload and range capability. Extensive design work was done on cryogenic fuel tanks, insulation systems as well as the fuel system itself. Three candidate fuel tank locations were evaluated, i.e., fuselage tanks, wing tanks or external pylon tanks

Modeling and optimization of process systems for unconventional technologies and feedstocks

In the present era, the petrochemical/chemical process industries must adapt to unconventional feedstocks and energy sources, in order to keep pace with increased competition, regulatory pressure, and changing markets. However, developing processes compatible with these changes requires deviating from traditional and accepted process design and operation paradigms. This dissertation addresses fundamental challenges related to this transition from three angles: incorporation of custom (and detailed) models into process design, integration of variable operation with process design, and optimization of transient process operations. The first part of the dissertation introduces a framework for modeling, simulation, and optimization of process flowsheets incorporating highly detailed physical models of important and complex process units, termed “multi-resolution flowsheets”. The framework relies on pseudo-transient continuation as a numerical method and allows for the robust optimization of large-scale process models. Several case studies demonstrate the method, including process flowsheets featuring both intensified (e.g., dividing-wall distillation column, multistream heat exchanger) and unconventional (e.g., quenched reactor, packed column for carbon capture) process units. Furthermore, these results reveal significant benefits of considering the added level of detail at the design stage. Finally, an avenue is presented to accelerate the convergence of the pseudo-transient method, which is especially important for the large-scale models considered. In the second part of the dissertation, the focus shifts to process design optimization for variable operation, or optimization under uncertainty. Here, I present a method for process design that considers the effect of uncertain physical parameters (assumed to follow continuous probability distributions), using a formulation that exploits the semi-infinite nature of dynamic optimization. I compare the method to traditional “scenario-based” approaches using both theoretical analyses and multiple case studies. In addition to demonstrating the effectiveness of the proposed method, these case studies also emphasize the importance of considering several practically relevant uncertainties during process design. The final part of the dissertation examines explicit consideration of process dynamics for operational optimization. First, I examine periodic (dynamically intensified) processes, which operate at a cyclic steady state. I present a pseudo-transient method for robust optimization of fully discretized dynamic process models, and I present an approach for implementing cyclic conditions based on their fundamental relation to material/energy recycle loops. Lastly, I propose a framework for optimal production scheduling in fast changing market situations. Towards this end, I show how data-driven dynamic models can represent the behavior of a set of scheduling-relevant (physical or latent) variables. A method is also given for executing scheduling calculations using these models, and the framework is demonstrated by considering the demand response operation of both simulated and real-world air separation units.Chemical Engineerin

Gas flaring reduction in nigeria in context of carbon dioxide (CO₂) reduction and utilisation requirements.

The growing demand for energy due to a rise in global population and an improved standard of living has resulted in the production, refining and consumption of hydrocarbon fuel. A consequence of this has been an increase in the global rate of natural gas flaring. While natural gas flaring is accepted as a waste of energy and natural resources, as well as a contravention of Nigeria’s current energy policy for sustainable development through natural gas conservation, natural gas flaring is still considered the most cost efficient and effective Associated Natural Gas (ANG) flaring management option in developing countries such as Nigeria. The need to further consolidate routine gas flaring reduction or management techniques has never been greater with the 2030 zero routine flaring initiative by the World Bank fast approaching. While there are several studies on natural gas utilisation techniques, they rarely consider the shortage of practical tools that integrate economic, technical, and regulatory factors into a gas flaring management framework; and also, the intricacies of the existing tools, which often comes at the expense of simplicity, to obtain real-time information output. Thus, the aim of this study was to develop a systematic framework and ANG management tool to aid the reduction of routine natural gas flaring in Nigeria. This research developed a systematic management framework (using a flowchart decision tree technique) and models to further develop a simple, relatively quick, flexible, and user-friendly ANG flaring management tool (using a MATLAB graphical user interface). This was integrated with techno-economic models for the Liquefied Natural Gas, Gas to Methanol and Gas to Wire ANG utilisation options using the ASPEN HYSYS computer software. The tool was then tested with data obtained from three fields A, B and C in the Niger Delta region of Nigeria. Field A is an offshore field in Bayelsa State in the South-West Niger Delta. Field B is an offshore field in Rivers State in the South-South Niger Delta while Field C is an onshore field in Delta State in the South-West Niger Delta. Results obtained showed the choice of Gas to Methanol option as the most optimal for Field A due to its preference for large gas volumes and cost effectiveness, Liquefied Natural Gas for Field B because of its proximity to the Liquefied Natural Gas pipeline infrastructure and Gas to Wire utilisation option for Field C due to its proximity to the electrical grid and high electricity requirements of that area when both economic and technical considerations were taken into account. The addition of further regional profiles within West Africa, as well as the consideration of more ANG utilisation options were among suggested areas for further research.Simms, Nigel J. (Associate)PhD in Energy and Powe

The Impact of Ambient Temperature on Low Carbon Energy Supply - Modelling and optimization studies on the supply of hydrogen energy from northern Norway

To avoid the worst impacts of climate change a rapid green energy transition is required where traditional fossil fuels are replaced by low-carbon alternatives. One attractive route to emissions reduction is blue hydrogen, which has lower CO2 emissions that traditional hydrogen production. For hydrocarbon exporters, increased blue hydrocarbon production can be achieved in two main ways: continued gas export with end-user-based hydrogen production or in-country hydrogen production and export. The cold climate in Norway provides a particular advantage to the performance of some industrial processes. A good example of this being the LNG plant at Melkøya, which is the most efficient of its type. Several other processes associated with blue hydrogen production could also benefit from low ambient temperature, increasing the attractiveness of in-country hydrogen production and potentially better supporting a future green hydrogen economy. The work summarised in this thesis includes a set of process optimization studies that look at the impact of ambient temperature on performance for several key links in the blue hydrogen supply chain. Along with this, a supply chain model is developed for a scenario where hydrogen is supplied from northern Norway to the UK. The focus of the work is process modelling and optimization, and several new sets of performance data are developed for important industrial processes. The main conclusion of this study is that the advantage offered by low ambient temperature in northern Norway is sufficient to make the export of blue hydrogen more efficient that a conventional LNG export based scenario over a range of realistic operating cases. The implication of this is that the basis for projects based on a conventional approach should be considered in more detail to ensure that they are based on a sound footing

Simulation of LNG rollover in storage tanks

LNG rollover is the sudden mixing of stratified LNG layers, which can generate significant amounts of boil-off gas. Such event is a severe safety concern; however, there are no reliable models at industrial scales available in the literature. In this research, we extend the definition of the hydrostatic stability ratio for binary mixtures to multi-component mixtures. Moreover, the fundamental issues associated with LNG rollover are reviewed, and a new model for simulating rollover is presented