Synthesis of work exchange networks for gas processing applications 2

2.1 LNG Refrigeration Processes Due to the energy intensive nature of cryogenic refrigeration processes used in air liquefaction plants and in the production of LNG, process optimizatio

CHAPTER 2

LITERATURE REVIEW

Two types of systems approach considering LNG is available: Synthesis and Operation This work is related the later one and thus, the available literatures on LNG processes are discussed in the following sections Besides this, due to the unavailability of academic research on work exchange networks, similar type of networks such as heat exchanger networks is highlighted to understand the complexity and challenge of this novel network

2.1 LNG Refrigeration Processes

Due to the energy intensive nature of cryogenic refrigeration processes used in air liquefaction plants and in the production of LNG, process optimization is extremely advantageous as optimal process design and operation can result in substantial capital and energy cost savings An efficient facility is also a greener facility as it reduces carbon and pollutant emissions into the environment As a consequence, there had been numerous publications by academic researchers on the optimization of cryogenic processes in the open literature

Majority of the publications centered on the optimal design of cryogenic processes There had been significant works on the synthesis of pure refrigerant cascade

refrigeration stages and their respective refrigerants to satisfy a given cooling load and corresponding temperature and pressure while minimizing capital and operational costs The work was later extended to incorporate the use of mixed refrigerant where number of

different types of mixed refrigerant cycles was calculated to minimize the total work required by the system by determining temperature, pressure, and composition of each

iterative approach by incorporating FORTRAN90 and MINOS

There had been also significant works in mixed refrigerant cryogenic processes

selection of MR compositions in addition to the selection of key process variables such as

mathematical optimization framework based on stochastic algorithms for the optimal design of mixed refrigerant cycles

operations in an LNG plant to minimize power compressor power requirements via NLP formulation The work focused on the operational optimization of existing and well

an MINLP formulation to optimize compressor load among any number of refrigeration

systems As stated by Hasan et al., the aforementioned works serve as preliminary investigations into the potential cost savings that could be derived from operational optimization of existing facilities around the world As such, operational factors such as variations in NG feed composition, flow rate, and MR compositions were not taken into consideration in their preliminary investigation and formulation Hence, this work serves

as a more extensive study before developing the model as any number of cycles so that an in-depth knowledge is gained on the behavior of the existing refrigeration system

This work focuses on the optimization of the AP-XTM system There are two ways

technology by Air-Products, the former aim is not feasible as the detailed technical configurations and setups are proprietary and not available in the public domain In addition, design optimizations are also subjected to factors including client priorities, costs, production levels and availability concerns The alternate approach would be to develop an operational optimization formulation based upon a simpler model built from

on the stream flows, temperatures, pressures, and equipment sizes are not documented, the formulated model shall be generalized to accept the widest possible range of specifications such that its applicability is not restricted to a single case or scenario This generality enables the optimization model to be applied over a range of operating conditions including process fluctuations in the NG feed flow rate, compositions and

cooling water temperature

2.2 Process Networks

The chemical industry accounts for about 20% of the total industrial energy consumption

forms of energy in chemical plants are heat and work Even though work is more expensive than heat, heat integration has been studied far more extensively than work integration This in spite the fact that many chemical plants such as gas processing and

transportation, Liquefied Natural Gas (LNG), refineries, petrochemicals, air enrichment, ammonia, fertilizer, etc use air, gases, streams, and/or refrigerants at high pressures, and compression work is a major need in these plants In such plants, some streams need work for compression, while others can produce work through expansion For instance, consider the LNG plant in Figure 2.1 Here, high-pressure natural gas (NG) is subcooled

MCHEs to cool NG It uses one compressor and two turbines to provide cooling as well

as produce work Thus, while the MCHEs address heat integration, the plant has four separate turbines and two compressors that are not systematically integrated to minimize work requirements If these turbines and compressors are integrated on one or more SSTCs, then the losses arising in separate turbines/compressors from the supply and delivery of work in disparate forms could be reduced or eliminated Furthermore, it would also be possible to integrate both heat and work simultaneously to conserve energy further in the same network In fact, the LNG industry in Qatar and other plants have already begun exploring some simple options on an ad hoc basis to save energy by using simple 2-stream SSTC units (one high-pressure and one low-pressure stream)

This idea of SSTC is a straightforward extension of a steam/gas turbine running a compressor using a common shaft The only difference is that a high-pressure stream replaces steam/gas in the turbine driver Of course, the idea can be generalized to include multiple turbines with several high-pressure streams running multiple compressors with several low-pressure streams using a single shaft Configuring a network for exchanging

work in this manner may be called “Work Exchange Network Synthesis” or WENS It is

a useful and direct extension of the well known Heat Exchange Network Synthesis

surprisingly, no work has so far developed a systematic procedure for exchanging work among multiple streams by matching high-pressure and low-pressure streams

Figure 2.1 Process Flow Diagram (PFD) of an LNG process

for optimizing boil-off gas (BOG) compressor operations to minimize the total average

optimized compressor operations for propane pre-cooled mixed refrigerant (C3MR) cycles and minimized the total power cost for the refrigerant compressors Del Nogal et

considered gas turbine, steam turbine, helper motor/generator, and electric motor as drivers to satisfy the given power demands of several compressor stages They addressed decisions to select appropriate gas/steam turbines as drivers for these stages

Pinch Analysis and Design (ExPAnD) to utilize pressure-exergy for minimizing energy requirements in sub-ambient processes such as LNG They used compressors and turbines separately to minimize the energy usage However, they did not explicitly mention the use of single-shaft turbine-compressor combinations to exchange energy Besides this, they only considered thermodynamic rather than cost aspects Since compressors and turbines are some of the most expensive equipment in a chemical plant,

a highly energy-effective process may be uneconomical Besides, a heuristics-based methodology may not offer the most economical network Therefore, there is a need for a cost-based structural optimization approach for work exchange network synthesis as presented in this paper

formulation for integrating pressure energy among multiple streams using compressors alone For this, they used a staged superstructure for each stream However, they did not consider operational constraints such as surging and choking, and did not correlate speed

to work exchange They also did not include both utility heaters and coolers in their network

2.3 Research Focus

Based on the aforementioned discussions and challenges, this research project focuses on the following aspects

1 An NLP model is developed to minimize the compressor load among different

optimal operational parameters for this process in different conditions such as weather fluctuation, feed NG composition, MR composition, etc It is worth to mention that the model is able to optimally produce realistic operational parameters that are very close to the real operations though the real design cannot be utilized due to the proprietary restriction of this system

2 As it is found that compressors are the preeminent energy consumers in the most chemical and petrochemical industries, utilization of available energy can economically save a lot of energy Therefore, an MINLP formulation is utilized to exchange both pressure and temperature energy among different streams to minimize the total cost of the network This study reveals that it is possible to save a significant amount of energy while utilizing such a network