Thermodynamic design of a cascade refrigeration system of liquefied natural gas by applying mixed integer non-linear programming

Kamalinejad, Meysam; Amidpour, Majid; Naeynian, S.M. Mousavi

doi:10.1016/j.cjche.2014.05.023

Cited by 18 publications

(6 citation statements)

References 9 publications

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“…Preliminary versions of this heat pump superstructure (HPS) [32,33] were generalized and extended to incorporate fluid selection, HEN [34] 2016 AHP MINLP -contin. 1 TAC G Oluleye et al [35] 2016 HP/AHP/HE/AHT TP HYSYS 10 K 2 Fuel S TP Oluleye et al [36] 2016 HP/AHP/HE/AHT MILP HYSYS 10 K 2 TAC S Binary Dinh et al [37] 2015 HP MILP PR fixed 3 Power S ( ) Flowrates Kamalinejad et al [29] 2015 HP MINLP RP contin. 3 TAC S ( ) Flowrates Liu et al [38] 2014 HP TP -fixed 3 Power S TP Khan and Lee [39] 2013 HP NLP PR contin.…”

Section: Discussion and Goalmentioning

confidence: 99%

“…Fluid selection Fluid selection has not been considered extensively in heat pumping literature. Some authors have compared different working fluids based on thermodynamic principles, such as Oluleye et al [28], while others mainly derive the optimal mass flow rates or composition from preselected fluids, including Kamalinejad et al [29]. Few researchers have integrated fluid selection into the optimization in the form of integer, binary, or continuous variables such as Becker [27], Vaidyaraman and Maranas [30], or Colmenares and Seider [31].…”

Section: Mathematical Methodsmentioning

confidence: 99%

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Optimal heat pump integration in industrial processes

et al. 2018

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Among the options for industrial waste heat recovery and reuse which are currently discussed, heat pumping receives far less attention than other technologies (e.g. organic rankine cycles). This, in particular, can be linked to a lack of comprehensive methods for optimal design of industrial heat pump and refrigeration systems, which must take into account technical insights, mathematical principles and state-of-the-art features. Such methods could serve in a twofold manner: (1) in providing a foundation for analysis of heat pump economic and energetic saving potentials in different industries, and further (2) in giving directions for experimentalists and equipment manufacturers to adapt and develop heat pump equipment to better fit the process needs. This work presents a novel heat pump synthesis method embedded in a computational framework to provide a basis for such analysis. The superstructure-based approach is solved in a decomposition solution strategy based on mathematical programming. Heat pump features are incorporated in a comprehensive way while considering technical limitations and providing a set of solutions to allow expert-based decision making at the final stage. Benchmarking is completed by applying the method on a set of literature cases which yields improved-cost solutions between 5 and 30% compared to those reported previously. An extended version of one case is presented considering fluid selection, heat exchanger network (HEN) cost estimations, and technical constraints. The extended case highlights a trade-off between energy efficiency and system complexity expressed in number of compression stages, gas-and sub-cooling. This is especially evident when comparing the solutions with 3 and 5 compression stages causing an increase of the coefficient of performance (COP) from 2.9 to 3.1 at 3% increase in total annualized costs (TAC).

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Section: Discussion and Goalmentioning

confidence: 99%

Section: Mathematical Methodsmentioning

confidence: 99%

Optimal heat pump integration in industrial processes

et al. 2018

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“…Detailed design: Various detailed design studies are present in academic literature and typically focused on few technologies and processes. Studies by Kamalinejad et al (2015), Yang et al (2017), and Becker (2012) presented optimal integration approaches of heat pumps in different industrial processes relying on mathematical programming and superstructure-based design. Most recently presented a comprehensive heat pump integration method based on mathematical programming and expert insight.…”

Section: General Potential Estimationmentioning

confidence: 99%

Bottom-up method for potential estimation of energy saving measures

Wallerand

Kantor

Maréchal

2019

Computer Aided Chemical Engineering

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Technology and energy saving potentials in the industrial sector are key data that policy makers rely on to drive decision making. A literature review reveals a distinct discrepancy between general potential estimation and detailed design studies. The former relies principally on top-down conceptual approaches based on temperature levels of the processes' thermal requirements, while the latter aims at mathematically optimized solutions for specific technologies in specific processes under specific economic conditions. This work attempts to close this gap by proposing a bottom-up method for potential estimation of energy saving measures. To this end, a generalized optimization framework was developed which aims at generating a database of optimal solutions which are independent from most economic and environmental input data. By fixing these data, the optimal solution for the same process type in different countries and under various criteria can be identified in the database. The method also increases accessibility of optimization techniques by providing the solution database which then requires limited input parameters and background knowledge to provide expert guidance toward optimal utility integration. The method was applied to the dairy industry, highlighting that energy saving potentials can be achieved through heat recovery and integration of heat pumps, mechanical vapor re-compression, and co-generation units economically favourable especially in Japan and Switzerland.

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“…Other authors based their formulation in the linear domain [11][12][13][14]. While more recent work dealt with exergy analysis of heat pumps and Mixed Integer Nonlinear Programming (MINLP) [15,16]. None of these works have dealt with solar utility integration.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of solar-assisted industrial processes considering heat pumping: Case study of a dairy

et al. 2018

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Pinch analysis and Mixed Integer Linear Programming (MILP) have been extensively studied for optimization of industrial processes addressing heat recovery, utility selection and sizing. Analysis of renewable utility integration, such as solar thermal or photovoltaics, introduces several obstacles for established methods: the time-dependency of resources, storage inertia and losses, and intrinsic non-linearities of the system performance are difficult to represent by linearized, time-invariant MILP equations. Moreover, waste heat recovery options such as heat pumping cannot be neglected as a potential competitor to solar heat. This work presents a set of multi-period MILP equations for solar technologies as well as a superstructure for optimization of heat pump cycles. Additionally, a methodology is proposed and applied to simultaneously optimize the process' refrigeration and renewable utility system using ε-constrained parametric optimization. The proposed methodology is illustrated on the basis of a dairy plant for which the different utility technologies are compared and evaluated based on economic and environmental criteria. It is illustrated that integration of solar energy can contribute to strongly reduce the environmental impact of the process (65-75% reduction in CO 2 equivalent emissions), but only in combination with heat recovery (27%) and an improved heat pump system (33%). Heat recovery and heat pump placement for industrial processes are hereby shown to reduce exergy destruction and total costs and increase energy efficiency in the system by means of thermo-economic optimization. The solutions show that investment in solar energy can be economically and environmentally attractive for industrial processes by considering the whole system and ensuring that solar energy is optimally integrated and utilized.

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Thermodynamic design of a cascade refrigeration system of liquefied natural gas by applying mixed integer non-linear programming

Cited by 18 publications

References 9 publications

Optimal heat pump integration in industrial processes

Optimal heat pump integration in industrial processes

Bottom-up method for potential estimation of energy saving measures

Optimal design of solar-assisted industrial processes considering heat pumping: Case study of a dairy

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