Composition optimisation of working fluids for Organic Rankine Cycles and Kalina cycles

Composition optimisation of working fluids for Organic Rankine Cycles and Kalina cycles

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Energy xxx (2013) 1e13

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Composition optimisation of working fluids for Organic Rankine Cycles and Kalina cycles Rachel Anne Victor a, Jin-Kuk Kim b, *, Robin Smith a a b

Centre for Process Integration, School of Chemical Engineering and Analytical Science, The University of Manchester, Manchester M13 9PL, UK Department of Chemical Engineering, Hanyang University, 222 Wangsimni-ro, Haengdang-dong, Seongdong-gu, Seoul 133-791, Republic of Korea

a r t i c l e i n f o

a b s t r a c t

Article history: Received 9 January 2013 Received in revised form 15 March 2013 Accepted 26 March 2013 Available online xxx

An optimisation model for the composition of mixed working fluids for (Organic Rankine Cycles) ORCs and Kalina cycles has been developed. The temperatures investigated were 100  Ce250  C for the heat source and 30  C for the heat sink. The optimisation method of the composition was carried out with Simulated Annealing technique with the objective function of maximising the thermal efficiency of the cycle, based on 1 MW of heat source. The results show that the pure component organic fluids are more energy-efficient than mixed organic fluids. The selection of organic working fluids was studied for achieving maximum cycle efficiency at a given operating temperature. The composition of the Kalina cycle was also optimised and it was found that for a maximum temperature of 250  C, the minimum ammonia concentration in the ammoniaewater mixture was 73.8% mol fraction. A novel consideration of employing alcoholewater mixtures in the cycle was also investigated and the most efficient mixture at 250  C was methanol and water mixture when compared to the Kalina cycle and steam Rankine Cycle. The study showed overall that the optimal choice of working fluids for a particular type of cycle would depend on the operating temperature and pressure. The developed design method can be useful for engineers to evaluate the performance of the cycles considering a wide range of working fluids, and determines the optimal choice of working fluids and operating conditions of the cycle. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: Organic Rankine Cycles Kalina cycles Mixed fluids Optimisation

1. Introduction Sustainable power generation has become increasingly important due to the accelerated consumption of fuels over the recent years. The excessive use of fossil fuels not only depletes these natural resources at an exponential rate, but also contributes to serious environmental problems, such as global warming. It is necessary to identify alternative sources of energy that could be utilised for energy generation with minimal harmful effects to the environment. Current environmental concerns have led to interest in the recovery and utilisation of low-grade heat sources. Typical examples of low-grade heat sources are geothermal energy, biomass energy, solar heat and waste heat from industrial processes such as flue gas and exhaust gases. The interest in these energy sources requires special attention because the temperatures at which these sources are available are relatively low (ranging from 60  C to 200  C). This

* Corresponding author. Tel.: þ82 2 2220 2331. E-mail address: [email protected] (J.-K. Kim).

results in low efficiency for power extraction, which makes power generation from such sources uneconomic. The Rankine cycle was initially identified as having the highest efficiency system when it was compared to other dynamic energy conversion systems [1]. Steam, the working fluid for the conventional Rankine cycle, offered advantages such as low cost, nonflammability and non-toxicity [2]. In the case of low temperature heat sources, however, steam as a working fluid operates at a relatively low efficiency. Alternatives to the Rankine cycle to increase the efficiency for low temperature applications are the (Organic Rankine Cycle) ORC and the Kalina cycle. The main challenge with the ORC is the choice of appropriate working fluids. Aside from the working fluid, a significant difference between the conventional Rankine cycle and the ORC is the device employed for the expansion of the fluid to generate power. The conventional Rankine cycle could utilise a steam turbine from the expansion of the pressurised steam, but the ORC would require a specialised expander device to cater for the properties of the organic working fluid. The Kalina Cycle, introduced in the early 1980s, is a thermodynamic power cycle using a binary mixture of ammonia and water as the working fluid. The binary properties of the mixture produce a

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non-isothermal evaporation and condensation in the cycle which contributes to the higher efficiency as compared to pure working fluids [3]. However, the main drawback identified in the Kalina cycle is the increase in the number of components required for the cycle. The objective of this paper is to investigate the performance of mixed working fluids for the ORC and Kalina cycle for low temperature applications. The heat source and heat sink for this study were assumed at a constant temperature, therefore giving a flat temperature profile. For the ORC, various organic components were considered in this work. The temperature range investigated was between 100 and 250  C for both ORCs and Kalina cycles. The selection and/or composition optimisation of working fluids for both ORCs and Kalina cycles was carried out with an automated design procedure, which had been implemented on commercial software, CRYO-intÒ(version 1.4) [4]. CRYO-intÒ is a commercial simulation and optimisation software package for the design of refrigeration cycles developed by Process Integration Limited. The optimal results were then further analysed with Aspen HYSYSÒ (version 2006.5) [5] for sensitivity analysis. 2. Literature review 2.1. Organic Rankine Cycle (ORC) The use of organic fluids in a Rankine cycle system for low temperature applications, as shown in Fig. 1, has been known for a number of years. When the selection of the appropriate organic fluids in the ORC is to be made, key issues to be considered are the thermodynamic and environmental performance of the cycle, as well as health and safety criteria.

Fig. 1. A simple closed Rankine Cycle.

Badr et al. [6] surveyed 68 possible organic working fluids for the application of low-grade heat recovery for low power output applications. Three performance indicators were applied to evaluate the performance of working fluids: heat transfer coefficients of the working fluids in the evaporator and condenser, feed pump power requirement, and the overall system energy efficiency. The working fluid with the highest heat transfer coefficient was implied to be the more favourable choice, because a high heat transfer coefficient suggests a smaller heat transfer area which consequently reduces the capital cost of the heat exchangers. The feed pump power requirement for the working fluids was related to the pressure differential across the pump, and the power required for pumping was less than 10% of the expander output. It was further suggested that high molecular weight compounds have less internal leakage rate in expanders, which results in a higher expander isentropic efficiency. These results produced were then compared to available experimental data, which showed a good agreement with their hypothesis. Devotta and Holland [7] compared the cycle efficiency of 24 working fluids using four performance indicators for the selection of the appropriate working fluid for the Rankine cycle, including the temperature at the evaporator, the temperature difference between the evaporator and condenser, the pressure ratio of the evaporator and condenser, and the thermal efficiency of the cycle. Thermodynamic properties of the working fluids were obtained from published data, which were used to evaluate the cycle for the evaporator temperature of 80  C, 100  C, 120  C, 160  C and 200  C. 31 organic working fluids were investigated for the application of a maximum working temperature of 100  C [8]. Different types of ORC cycles were identified for the purpose of matching the thermodynamic properties of the working fluids to the requirements of the process. These cycles were classed based on two factors: the shape of the saturated vapour line in the temperature (T) e entropy (s) diagram and the state of the working fluid from the evaporator to the turbine outlet. The two shapes of saturated vapour line discussed were the negative- and positive-sloped curve. The identification of these shapes is important in order to choose the operating conditions for the different types of fluids. For the expansion with negative-sloped saturated vapour line, the working fluid enters the turbine inlet as a saturated vapour and leaves the turbine in the two phase region. It is important to note that for a conventional turbine expander, a certain liquid fraction tolerance can be accepted. Liquid formation in turbines can cause mechanical damage and erratic operations which are undesirable. The working fluid entering the turbine inlet as a saturated vapour for the positive-sloped case leaves the turbine as a superheated vapour. Another case is a supercritical pressure cycle where the working fluid is compressed up to supercritical condition before entering the turbine, and leaves in the two phase region. Another configuration which could be applied for the supercritical pressure cycle is where the working fluid leaves the turbine as a superheated vapour. The notation for 2a and 4a represents the points at which a recuperator is used in the cycle, shown in Fig. 1(b). Saleh et al. [8] also analysed the performance of the working fluid with respect to the heat transfer between the heat source and working fluid. It has been identified that the choice of working fluid should take into account how the heat source is utilised in the cycle. Results showed that for subcritical cycles, achieving superheated vapour at the turbine inlet always gives a higher thermal efficiency. Coupling the recuperator with the superheated cycle was demonstrated to produce a more significant increase in the thermal efficiency. Although the use of recuperators were addressed to be beneficial for Rankine Cycles in most literature, Dai et al. [9] pointed out

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that the use of the recuperator is dependent on the type of cycle considered. It may be beneficial to implement the heat exchange through the recuperator when the temperature of the working fluid leaving the expander is significantly higher than that of fluid leaving the condenser. Lai et al. [10] further investigated alkanes, aromates and linear siloxanes as working fluids for the maximum working temperatures of 250  C and 300  C, based on the same methodology by Saleh et al. [8]. Ranking points were used to analyse the performance of the working fluids based on the minimum or maximum values of the thermal efficiency, volumetric flowrate of inlet stream to the turbine, and the volumetric flowrate of the outlet stream from the turbine. The analysis of the heat transfer from the heat source, however, involved minimising the heat capacity flowrate for a given net work of 1 MW. The heat capacity flowrate was then incorporated into the ranking point equation to analyse the performance of the working fluid. Papadopoulos et al. [11] investigated the selection of optimal working fluids for ORCs using (computer aided molecular design) CAMD and process optimisation techniques. For a simple closed Rankine Cycle, 15 properties based on thermodynamic, environmental, safety and process related properties were used as performance measures in the CAMD to generate suitable components for the cycle. The components generated were then employed in the process optimisation technique in which (Simulated Annealing) SA methods were used to minimise the cost of heat exchanger area. It was suggested that it would be reasonable to avoid any components with a significantly higher maximum operating pressure and with a significantly higher mass flowrate than 10 kg/h. This assumption limits the choice of working fluids, and the method employed is only limited to pure component fluids, not for multicomponent mixture. The merits of employing mixed working fluids were highlighted by Angelino and Colonna di Paliano [12]. A simple closed Rankine Cycle was considered in this study, with a recuperator where applied. The analysis was classified based on the cycle configurations as saturated cycle, superheated cycle and supercritical cycle, and the type of molecules as simple molecules and complex molecules. Their analysis could be summarised as mixed composition fluids provide better heat profile matching with the heat and cooling source. This is due to the non-isothermal evaporation and condensation of the fluid which could reduce the mean temperature difference between the source and working fluid in heat exchangers. However, it should be kept in mind that reducing the mean temperature difference implies that a higher heat exchanger area is required for a given heat flow, suggesting a trade-off between operating and capital costs. 2.2. Kalina cycle The layout of a Kalina cycle is significantly different from a Rankine cycle, due to the complexity of the design. In general, a Kalina cycle requires additional equipment involving a separator and intermediate heat exchangers. Ibrahim and Kovach [13] investigated the ammoniaewater mixture as working fluids. The cycle configuration is similar to the Rankine cycle with the addition of a separator downstream of the turbine. This configuration allowed the manipulation of the ammoniaewater mixture, in which water is added to the ammoniarich stream before the condenser. The mixing of these streams allows a liquid mixture at the outlet of the condenser, as well as resulting in a condensing operating pressure above atmospheric pressure. An iterative energy balance procedure around the separator was used when manipulating the operating conditions (temperature, pressure and mass flowrate) of the separator. Results


from this study showed that the mass fraction of ammonia-rich stream and the operating temperature and pressure of the separator affect the thermal efficiency of the cycle, and decreasing the separator pressure for a fixed temperature and ammoniaewater composition increases the thermal efficiency of the cycle. The Kalina-type cycle studied was 10e20% more efficient than a Rankine cycle under similar conditions, but no parameters or results of the Rankine cycle were provided for the comparison between the two cycles. Consideration of the turbine inlet conditions (composition and temperature) and the separator temperature as key parameters were further emphasised through an optimisation study done by Nag and Gupta [14]. Thermodynamic analysis was used to assess the optimal design for the cycle using ammoniaewater mixtures. This study also investigated the exergy loss in the system due to thermodynamic irreversibility for each component. Gibbs free energy equations for mixtures were used to evaluate the thermodynamic properties of the working fluid. The second law cycle efficiency was then defined as the ratio of the exergy output and the exergy input, taking into account the exergy losses in the components. The results suggested that increasing the temperature of the separator while decreasing the ammonia concentration at the inlet of the separator could increase the cycle efficiency. However, variation of the cycle efficiency for a given separator temperature with increasing ammonia concentration (0.55e0.80 mass fraction) varies at a maximum of 2%. An interesting fact that was highlighted in the exergy analysis is the different effects produced by the concentration of ammonia for different components. Increasing the ammonia concentration at the turbine inlet reduces the losses in the turbine, but increases the losses in the evaporator. The authors suggested that this is because low ammonia concentrations produce a better matching for the temperature profile between the heat source and the working fluid and therefore reduces the thermodynamic irreversibility of the system. The evaporator also exhibited the greatest losses as compared to the other components (turbine, pump and absorber) by nearly 30%. Ogriseck [15] investigated five Kalina cycle cases with varying ammoniaewater compositions, cooling water temperatures and condenser pressures based on an existing (combined heat and power) CHP plant. The layout of the Kalina cycle process investigated is similar to a Rankine cycle with the addition of two recuperators and a separator located upstream of the turbine expander. It was pointed out that the mixing ratio of the ammoniaewater mixture varies during the evaporation. This is due to the fact that ammonia has a lower boiling temperature than water and therefore evaporates more than water. The separator here is placed before the turbine expander so as to separate the ammonia-rich steam from the liquid phase mixture. This paper used the net electrical efficiency as the performance measure for the case studies. One important feature that was mentioned is the significance of the condenser pressure to the efficiency of the cycle. Aside from utilising a lower temperature cooling utility, the pressure of the condenser could be reduced by decreasing the concentration of the ammonia in the mixture. 2.3. Comparison between ORC and Kalina cycle A study of the thermodynamic comparison between the Kalina and ORC cycle was carried out for the heat recovery from diesel engines [16]. The working fluid for the ORC used was (hexamethyldisiloxane) MM. The thermodynamic properties of both MM and ammoniaewater mixture were calculated using commercial software. The Kalina cycle layout evaluated in this study is similar to the layout proposed by Ibrahim and Kovach [13] in which the separator is located downstream of the turbine followed by a series

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of heat exchangers and pumps. For the sake of simplicity, Bombarda et al. [16] assumed no pressure drops within the heat exchangers. This assumption suggests that the thermal efficiency of the cycle would be overestimated. The optimisation of the ammoniaewater mixture for maximum net work output required a very high operating pressure (over 100 bar). This suggested high capital and operating cost, and would not be reasonable especially for smallscaled plants. The ORC cycle considered for comparison in this study is a simple, closed cycle with a recuperator (Fig. 1b). The same parameters applied for the evaluation of the Kalina cycle were applied in the ORC cycle so as to perform a reasonable comparison. However, the condensing pressure applied in the ORC cycle for this working fluid is 0.12 bar, below atmospheric pressure. As mentioned previously, not only is it inadvisable to operate below atmospheric pressure, but the condensing pressure also has a significant effect on the thermal efficiency. Keeping all other variables constant, lowering the condensing pressure will increase the thermal efficiency of the cycle. The condensing pressure of 0.12 bar clearly suggests that the thermal efficiency of the ORC cycle will be significantly higher than when operating at a more reasonable pressure (above atmospheric). Results from this study showed that the performance of the ORC cycle and the Kalina cycle at 100 bar to be competitive to one another. Reducing the pressure of the Kalina cycle to 50 bar showed a significant decrease in the performance of the cycle. Zamfirescu and Dincer [17] proposed the use of a (Trileteral Flash Cycle) TFC employing the ammoniaewater mixture as working fluids. The TFC, similar to the Rankine cycle, flashes the working fluid through a scroll expander into the two phase region and then fully condenses the working fluid. It should be mentioned that unlike a turbine expander, a scroll expander has the advantage of operating with wet steam [18]. The TFC ammoniaewater cycle was first analysed to maximise cycle efficiency, based on varying temperature difference at the condenser and varying turbine efficiency. Results showed that both parameters produced insignificant differences in the cycle efficiency for varying ammonia concentration. The study then proceeded to compare the ammoniaewater TFC cycle with four organic fluids for the ORC as well as a Kalinatype cycle (Rankine cycle employing ammoniaewater mixture as a working fluid). All cases applied a turbine inlet temperature of 150  C and the corresponding pressure of 6 bar. The four organic working fluids used in this study were R-141b, R-123, R-245ca and R-21. The results from this comparison showed that all the organic fluids achieved higher cycle efficiencies as compared with the ammoniaewater mixture. However, the exergy analysis suggested that the TFC cycle produced the highest exergy efficiency, more than double of the next highest exergy efficiency. This is due to the profile matching obtained by the TFC configuration as a single component cycle being less efficient, due to its inability to match the heat profile, especially at the condensing side. 2.4. Recent advances and summary Recent studies on ORCs have been extended to address complex cycle design which accommodates discontinuous waste heat recovery and considers the influence of outlet temperature of heat source on the cycle efficiency [19]. Industrial application of ORCs has been highlighted in the refining process in which different working fluids for using a process stream from 140  C to 45  C were tested and ranked in terms of maximum achievable power output, efficiency of the cycle, amount of the heat recovered, heat exchanger area, CO2 emissions and capital cost [20]. The utilisation of low grade heat in ORCs for steel industry has been investigated for improving energy efficiency through the environmental and techno-economic evaluation of a

case study using waste heat available from the stacks of a coke oven used in steel-making process [21]. Systematic investigation for using low grade heat in process industries has been made with the aid of process integration concept, which evaluates different technologies, including ORC, and identifies the most appropriate way for industrial waste heat recovery [22]. The integrated application of the Kalina cycle in the context of energy generation systems has been reported. Peng et al.’s work [23] proposed an energy conversion system which combines the Kalina cycle with the intercooled gas turbine cycle in the solar thermal power system. The application of Kalina cycle for the coal fired steam power plant has been investigated, which examines the possibility of using low-temperature heat of flue gases for generating power with the aid of process simulation and optimisation techniques [24]. A review of studies on the Kalina cycle has been documented in the recent work, which addresses exergy and energy analysis for the Kalina cycle, explains different Kalina systems and properties of working fluid. Also, engineering aspects in the design and operation of Kalina cycle has been discussed in the context of stability, environmental impacts, safety and corrosion [25]. A review of the previous work showed that the use of ORC and Kalina cycle has been proven to be beneficial, especially for low temperature applications. Optimisation studies on the cycle outlined the significant effects associated with choices of cycle parameters on the cycle efficiencies, for example, configuration of cycles, use of recuperators and operating conditions on the condensing side. Although the importance of the choice of working fluids to improve the performance of the cycle has been addressed, little work has been done to the computer-aided screening of optimal working fluids, especially for mixed-composition fluids. Also, the current paper aims to build a systematic design method which can effectively evaluate a wide range of possible working fluids in Kalina and ORC cycles, and enables choice of the most appropriate working fluids with their composition in a holistic manner. Therefore, the developed modelling and simulation framework can provide a practical and reliable decision-support tool for achieving energy-efficient ORC and Kalina cycle in practice. Another major contribution from this work includes the detailed and thorough consideration of alcoholewater mixture in the optimisation study, leading to high energy efficiency in the energy generation. 3. Base case: modelling of a Rankine Cycle Although it is evident from many publications that the conventional steam Rankine Cycle is highly inefficient for low temperature applications, this section intends to model a steam Rankine Cycle as a base case for the purpose of producing a reasonable comparison with the ORC and Kalina cycles. The cycle analysed in this study was the simple, closed Rankine cycle operating at subcritical conditions. The four main components considered in this cycle were the evaporator, turbine, condenser and pump as shown in Fig. 1. With the given parameters for this study as shown in Table 1, the objective of the case studies is to optimise the performance of the cycle for 1 MW of heat supplied at the evaporator for the temperature range from 100  C to 250  C. The temperatures of the heat source and heat sink were assumed to be constant. For the sake of simplicity, the study considered only above atmospheric pressure operations hence a minimum condensing pressure of 1 bar, which also avoids potential problems with the ingress of air into the cycle. Cost and safety concerns have been raised in previous publications regarding the maximum allowable pressure for a system. A maximum pressure of 50 bar was chosen so

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Table 1 Cycle design parameters considered. Turbine isentropic efficiency, hturb Pump isentropic efficiency, hpump Minimum condensing pressure, P3, min Maximum turbine inlet pressure, P1, max Minimum temperature difference, DTmin Cooling water outlet temperature Condenser outlet temperature, T3 Pressure drop in heat exchangers

0.80 0.65 1 bar 50 bar 10  C 20  C 30  C 1 bar

as not to significantly constrict any optimisation opportunities within the cycle. The mechanical efficiency for the pump and the generator efficiency for the turbine have been assumed to be unity, which would be a fair assumption as literature values suggested these efficiencies to be approximately 98% [15]. Thermodynamic calculations of the working fluids were performed using Aspen HYSYSÒ (version 2006.5) simulator [5]. The following equations describe the thermodynamic modelling of each component under steady-state conditions. The amount of heat supplied by the heat source to the working fluid in the evaporator, Qin, was expressed as shown in Equation (1) and the amount of heat rejection from the working fluid to the environment, Qout, was expressed as shown in Equation (2).

_ 1  h4 Þ Q in ¼ mðh


_ 2  h3 Þ Q out ¼ mðh


Expressions for Qin and Qout would be defined as shown in Equations (3) and (4) when applying a recuperator to the cycle.

_ 1  h4a Þ Q in ¼ mðh


_ 2a  h3 Þ Q out ¼ mðh


The mechanical work generated by the expander, Wturb, and the mechanical work required by the pump, Wpump, were expressed as shown in Equations (5) and (6).

_ 2  h1 Þhturb Wturb ¼ mðh Wpump ¼

_ 4  h3 Þ mðh


(5) (6)

The net work generated by the cycle, Wnet, was therefore defined as the difference between Wturb and Wturb:

Wnet ¼ Wturb  Wpump


The first and second law cycle efficiencies were applied to measure the performance of the cycle. The first law cycle efficiency was defined as the ratio of net work generated to the heat source supplied to the system (Equation (8)). However, hi alone does not measure the efficiency with regards to the true potential of the cycle [26]. The second law cycle efficiency, hii, was then applied, with relation to the Carnot cycle efficiency, hCC, which represents the maximum thermodynamic efficiency of the cycle. A better representation of the cycle efficiency could be achieved by calculating hii, which represents the effectiveness of the cycle with regards to the maximum energy that could have been extracted from the system in Equation (9).

hi ¼

Wnet Q in


hii ¼

hi hCC


Fig. 2. Simulation results: steam Rankine Cycle.

The steam Rankine Cycle shown in Fig. 1(a) was modelled in Aspen HYSYSÒ [5] employing PengeRobinson (Equation of State) EOS for the thermodynamic calculation. The conditions for a temperature of 30  C at 1 bar were specified for the outlet of the condenser. Due to the pressure drop specification of 1 bar throughout the heat exchangers, the minimum working temperature of the steam Rankine Cycle modelled was 130  C at 2.7 bar (saturated vapour condition). The results of the base case simulation are shown in Fig. 2. The results shown in Table 2 were presented for turbine inlet temperature of 150  C, 200  C and 250  C, will be used later on for comparison with the other cycles. The results showed a decrease in efficiency as the working temperature decreases. Detailed results of the simulation for this base case can be found in Appendix A. For the same turbine inlet temperature, applying superheated vapour conditions would reduce the pressure of the working fluid and hence the work extracted from the turbine. To demonstrate this, an analysis was performed for 250  C with a 10  C superheated conditions. The pressure at which steam is available for this condition was calculated to be 33 bar. Results showed that hi of the cycle decreased as compared to the saturated vapour condition of the same temperature. The hii of the cycle also decreased because the maximum available energy of the cycle remains constant. Therefore, only saturated vapour conditions at the turbine inlet were considered in the study, to maximise efficiency opportunities. It should also be noted that the base case modelled is not an optimum steam Rankine Cycle. An optimum cycle would employ the normal boiling temperature at the outlet of the condenser at which the liquid would be compressed from a higher temperature, reducing the work required by the pump. The increase in temperature at the condenser would also require a higher working fluid flowrate. 4. Selection of optimal working fluids for ORC 4.1. Performance of pure working fluids A wide range of organic compounds have been investigated. The majority are alkanes, cycloalkanes, aromates, siloxanes, alcohols, Table 2 Simulation results of a steam Rankine Cycle. Vapour condition

T1 ( C)

P1 (bar)

hi (%)

hCC (%)

hii (%)

Saturated vapour Saturated vapour Saturated vapour Superheated Vapour

150 200 250 250

4.8 15.4 39.1 33.0

4.65 10.68 15.01 14.29

87.50 90.47 92.30 92.30

5.31 11.80 16.26 15.48

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Table 3 Commercially-viable HCFCs identified by Montreal Protocol 2009.

Table 5 Additional organic compounds considered in the current study.






Chemical formula



HCFC-21 HCFC-123 HCFC-124 HCFC-141b HCFC-142b

0.040 0.020 0.022 0.110 0.065

210 120 620 700 2400

i-Pentane n-Heptane n-Octane 22-Mbutane 33-Mpentane 2-Mheptane i-Butene 1-Pentene 1-Hexene 1-Heptene 1-Octene Propadiene Cyclopropane Cyclobutane Cyclohexane Cycloheptane Cyclooctane Cyclobutene Cyclopropene Ethanol 2-Propanol 1- Butanol

C5H12 C7H16 C8H18 C6H14 C7H16 C8H18 C4H8 C5H10 C6H12 C7H14 C8H16 C3H4 C3H6 C4H8 C6H12 C7H14 C8H16 C4H6 C5H8 C2H6O C3H8O C4H10O

Alkanes Alkanes Alkanes Alkanes Alkanes Alkanes Alkenes Alkenes Alkenes Alkenes Alkenes Allenes Cycloalkanes Cycloalkanes Cycloalkanes Cycloalkanes Cycloalkanes Cycloalkenes Cycloalkenes Alcohols Alcohols Alcohols

(chlorofluorocarbons) CFCs and (hydrochlorofluorocarbons) HCFCs. A number of HCFCs which have been identified by the Montreal Protocol as the most commercially-viable substances (Table 3) were considered in this work [27]. Eliminating CFC compounds, potential organic working fluids which have been investigated from various previous studies are summarised in the list seen in Table 4. Results from these studies would not provide a reasonable comparison due to the fact that each study applied different cycle parameters. Therefore, the performance of these fluids was analysed again based on the parameters used in this study. Expanding on organic fluids studied in previous works, a further 22 organic fluids were considered in this study, listed in Table 5. Additional substances from the same group with similar chemical formula were chosen to search potential working fluids. The performances of the 40 organic working fluids listed in Tables 3e5 were evaluated as pure component working fluids in Aspen HYSYSÒ. The cycle configuration for this analysis is the steam Rankine Cycle shown in Fig. 1(a) which is based on conventional simple cycle widely used in the production of power from heat [11,28]. The same cycle parameters given in Table 1 are used. The operating conditions for the outlet of the condenser would be specified for 30  C at 1 bar. The EOS applied in the simulations for the hydrocarbons (alkanes, alkenes, allene, cycloalkanes, cycloalkenes, aromatics, HCFCs and organoflourines) was PengeRobinson, while the EOS applied for the analysis of the alcohols was NRTL model. The results shown in Figs. 3e6 are the performance of various working fluids for saturated vapour cycle configurations over the temperature range of 100  C and 250  C. The general trend observed from different chemical groups was that the higher molecular weight compounds produced a lower efficiency. However, the range at which these compounds could operate extended to the higher temperature more than that of the lower molecular weight compounds. This might be due to the higher critical temperature and higher normal boiling point. The critical pressure, however, decreased as the molecular weight increase, subsequently reducing the entropy difference between the two pressures. Therefore, the efficiency of the cycle was reduced.

The results showed that for the temperature range of 100  C and 150  C, C4 and C5 hydrocarbons produced the highest efficiencies within its group. The performance of refrigerants at this temperature was also similar to the hydrocarbons. For the temperature range of 150  Ce200  C, the fluids with high energy efficiency were the refrigerants and methanol. At 250  C, only benzene exhibited an efficiency of higher than 10%. Compared to the performance of steam at this pressure, it could be concluded that the use of pure component organic fluids was more beneficial than steam for up to the temperature of approximately 200  C. 4.2. Composition optimisation of ORC working fluids CRYO-intÒ is a commercial simulation and optimisation software package that can carry out the design and the optimisation of mixed working fluids for refrigeration cycles [4]. The refrigeration cycle is essentially the reverse process of a power cycle, in which power input for the compressors is required, instead of extracting power from the system. The software was modified to incorporate power cycle components, like the turbine and pump to accommodate for the optimisation of mixed composition for power cycle working fluids. CRYO-intÒ has two optimisation methods for both the refrigeration and power cycles: (Simulated Annealing) SA and (Non-Linear Programming) NLP [4]. To simulate a process, a flowsheet for the cycle has to be generated followed by a set of calculation sequence.

Table 4 Potential organic working fluids identified from previous work. Substance

Chemical formula


n-Butane/R600a i-Butane/R600 n-Pentane n-Hexane 22-Mpropane Cyclopentane Benzene Toluene o-Xylene p-Xylene Difluoroethane/R152a Tetrafluoroethane/R134a Methanol

C4H10 C4H11 C5H12 C6H14 C5H12 C5H10 C6H6 C7H8 C8H10 C8H10 C2H4F2 C2H2F4 CH4O

Alkanes Alkanes Alkanes Alkanes Alkanes Cycloalkanes Aromatics Aromatics Aromatics Aromatics Organoflourine Organoflourine Alcohol

Fig. 3. Performance of pure component working fluids e alkanes.

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Fig. 4. Performance of pure component working fluids e alkenes, allene and aromatics. Fig. 6. Performance of pure component working fluids e HCFCs, organoflourines and alcohols.

The default optimisation objective is to minimise shaftpower. However, for the case of a power cycle, the specified objective is to maximise efficiency, which has to be incorporated into the calculation sequence. It should be noted that the modelling and optimisation framework can readily accommodate capital cost of the cycle in the objective function for carrying out more rigorous economic trade-off between operating and capital costs. However, optimisation study carried out is to focus on maximising energy efficiency, which is a reliable and sound performance indicator for comparing the cycle in a common design basis. Inclusion of capital costing may not be able to provide realistic design guidelines, due to considerable uncertainty in the capital costing parameters. A summary of the optimisation method is shown in Fig. 7. Although built-in physical properties calculation methods in CRYO-intÒ could be used for the simulation, CRYO-intÒ allows the use of the physical property library which is available in Aspen HYSYSÒ [4]. This allowed more flexibility with the choice of physical property calculations, especially for the optimisation of mixed component fluids where binary interaction parameters were required. The Rankine cycle flowsheet generated in CRYO-intÒ is shown in Fig. 8(a) [4]. One of the limitations in the CRYO-intÒ software is the pressure drop specification within heat exchangers. Letdown valves have been incorporated into the flowsheet to accommodate for the loss of net work, due to pressure drops from the condenser and evaporator. A summary of the calculation sequence implemented for the composition optimisation of the working fluids is shown in Fig. 8(b). A difficulty identified for optimising the mixed composition was to specify a minimum condensing pressure for the working fluid at 30  C. If the desired pressure and temperature were specified at the condenser, there was the probability that the optimiser would set the working fluid to be in the vapour phase.

The calculation of the pump would therefore lead to a negative shaftwork, misleading the objective function into maximising the negative shaftwork to maximise hi. To overcome this, the objective function was expressed as Equation (10). This expression, although not the most elegant method, would not only avoid the resulting condensing pressure below atmospheric pressure, but also kept the condensing pressure to a minimum where possible.

objective function ¼ hi 

P3  1 P32


The optimisation method employed in the study was the SA (Simulated Annealing) method. This method is an effective method for obtaining the minimum of an objective function for highly nonlinear problem, although computational time, as compared to conventional deterministic NLP (nonlinear programming) methods, is much longer [29]. The optimisation was first performed to select a most energyefficient pure fluid to be used for the turbine inlet temperatures of 100  C, 150  C, 200  C and 250  C and the results obtained are shown in Table 6. Different turbine inlet temperatures were then applied for the selected compound with the Aspen HYSYSÒ simulator [5], and the sensitivity of turbine inlet temperature on the cycle efficiency was obtained, as depicted in Fig. 9. The initial assumption of the project was that a mixed composition fluid would result in a better performance than pure working fluids. However, a closer look at the interactions between the compounds proved that there is no significant benefit for using mixed components for achieving a better performance, due to insignificant interactions between the compounds, especially for hydrocarbonehydrocarbon mixtures. When two compounds with different efficiencies were mixed, the resulting fluid with mixed composition would be an average of the two. An example to illustrate this is shown with a mixture of n-Butane and n-Hexane. Two sets of mixtures for n-Butane and n-Hexane were investigated with 50e50 mol fraction and a 70e30 mol fraction for n-Butane and nHexane respectively. The cycle efficiencies of these mixtures are shown in Fig. 10. As expected, the efficiency of the resulting mixture lies between the efficiencies of the pure components. As the mol fraction of n-Butane in the mixture was increased, the trend of the efficiency of the mixture increasingly follows the trend for nButane. 5. Composition optimisation of a Kalina cycle

Fig. 5. Performance of pure component working fluids e cycloalkanes and cycloalkenes.

The configuration of a Kalina cycle could vary from the location of the separator (before or after the turbine) to the number of

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Fig. 7. Optimisation method in CRYO-int simulation software.

recuperators employed in the cycle. For the purpose of optimising the composition of the ammoniaewater mixture, the Kalina cycle in this work was scaled down to the most fundamental level, replicating the configuration of a simple closed Rankine Cycle [11,28]. A saturated vapour configuration was applied to the ammoniaewater mixture, hence eliminating the need for a separator. However, when the maximum pressure restriction of 50 bar was applied on the cycle, a two-phase mixture might form at the outlet of the evaporator, depending on the operating pressure. A separator was then placed before the turbine in this configuration (Fig. 11). The rest of the cycle remained the same (i.e. two heat exchangers, a pump and a turbine). Water is a highly polar compound due to the hydrogen bonding, causing significant interactions in the binary mixture, unlike hydrocarbonehydrocarbon mixtures which have small interactions. Built-in interaction parameters for PengeRobinson EOS for the ammoniaewater mixture are available on the simulation software Aspen HYSYSÒ [5], which was used to calculate the thermodynamic properties. The performance of ammonia as a pure fluid was first investigated and compared to the performance of steam. For a saturated vapour cycle configuration, ammonia showed a significantly high efficiency, even when comparing to the performance of organic fluids, at a low temperature (Fig. 12). This was due to the low normal boiling point of the component. As compared to the normal boiling point of water, the extent to which ammonia could be applied for low temperature applications is promising. However, due to the low critical temperature of ammonia (i.e. 134  C), the saturated vapour cycle configuration, with the cycle parameters set in this work, was only effective up to 130  C. As the concentration of the water increased in the ammoniae water mixture, the normal boiling point of the mixture increased. The computational time for the composition optimisation could be reduced by specifying the upper limit of the water composition to avoid operating below atmospheric pressure at the condenser side. The maximum water concentration for the ammoniaewater binary mixture is identified with the calculation sequence as given in Fig. 13.

Table 6 Selection of optimal pure compounds and its cycle efficiency.

Fig. 8. Simulation and optimisation framework for Rankine Cycles.

T1 ( C)





Compound selected





hi (%) hii (%)

10.71 13.09

14.25 16.29

15.15 16.74

12.83 13.9

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Fig. 9. Sensitivity of turbine inlet temperature for selected working fluids.

Fig. 11. Flowsheet of a Kalina cycle with a separator.

A temperature range from 25  C to 40  C was investigated for this analysis. Table 7 shows that as the condensing temperature increases, the maximum concentration of water in the mixture increases. This study considered a condensing temperature of 30  C, therefore the resulting maximum water mol fraction in the ammoniaewater mixture was 0.7549. A higher water fraction in the mixture would force the operation below atmospheric pressure. This value was used as the upper limit concentration for the optimisation of the ammoniaewater mixture. The Kalina cycle in CRYO-intÒ was modelled as a simple closed Rankine Cycle, similar to the ORC cases. The same cycle parameters were also applied for this case for consistency. The same calculation sequence for the ORC was used, but only with the two components: ammonia and water. The objective function for this calculation sequence was to maximise the first law cycle efficiency hi. The expression related to pressure, as shown for the optimisation of the organic fluids, was not necessary, due to the water concentration specification. The optimisation of the ammoniaewater composition was performed for turbine inlet temperatures of 100  C, 150  C, 200  C and 250  C. Table 8 shows the optimal ammoniaewater composition in mol fractions generated from optimisation. These optimal results were then used in Aspen HYSYSÒ for performing sensitivity analysis as shown in Fig. 14. The results showed that for a saturated vapour cycle, as the turbine inlet temperature increased, the efficiency of the cycle could be improved by increasing the concentration of water in the mixture. Another sensitivity analysis was performed to

investigate whether a lower ammonia concentration of the mixture would produce a higher efficiency. The different concentrations of ammonia were investigated, and the results in Fig. 15 showed that reducing the concentration of ammonia further than 73.8% would not produce a cycle with better efficiency when the upper limit for the stream temperature of turbine inlet is 250  C. Although the efficiency of the cycle with mixed composition was lower than that with optimal composition, the performances were still higher than that of using steam alone. The optimal pressures for the ammoniaewater mixture produced for the saturated vapour configuration were shown to be over the maximum pressure constraint. For that reason, another set of optimisations was performed while applying the maximum pressure constraint of 50 bar. Table 9 shows the results from the composition optimisation at 50 bar. Although steam presented a higher efficiency than an ammoniaewater mixture at 250  C, steam was a liquid (water) at 250  C at 50 bar. Allowing a reduced pressure of 39.1 bar showed that steam was a better fluid than the ammoniaewater mixture at 250  C. The results of the sensitivity analysis for these results are shown in Fig. 16. Due to the low critical temperature of ammonia, the working range of ammonia for a saturated vapour configuration is limited. However, compressing the working fluid to 50 bar increased the working temperature range to the superheated vapour region, which allowed the ammonia to be used at higher temperatures beyond 130  C. On the other hand, the ammoniaewater mixture was limited to be operated at a lower pressure. Depending on the temperature and pressure, the mixture would exist as a two-phase mixture. This would result in not only an increase in the required

Fig. 10. Cycle efficiency of mixed organic fluids.

Fig. 12. Performance of ammonia and water as pure components.

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Fig. 14. Sensitivity analysis of optimal ammoniaewater composition.

Fig. 13. Summary of maximum water concentration calculation sequence.

flowrate, but a reduced efficiency due to fractions of the mixture that would not be expanded through the turbine. 6. Investigation of novel alcoholewater mixtures The fact that the Kalina cycle could yield high efficiencies despite being a mixed composition fluid, initiated the research into organic-water mixtures. The majority of the organic fluids investigated in this study are relatively insoluble in water, especially the alkanes and cycloalkanes [30]. Among the organic compounds which were investigated in this work, the alcohol group was the most soluble group with water. The alcohol compounds considered for the optimisation of alcoholewater compositions were methanol, ethanol, 2-propanol and 1-butanol. These components and water were investigated in the optimisation framework for identifying the optimal composition at the temperature of 250  C. This temperature was chosen on the basis that the ammoniaewater mixture yielded the highest efficiency at this temperature.

Table 7 Maximum water concentration in ammoniaewater binary mixture to avoid operating below atmospheric pressure. Condensing temperature, T3 ( C) Mole fraction Ammonia Water





0.2711 0.7289

0.2451 0.7549

0.2210 0.7790

0.1984 0.8016

Table 8 Optimal ammoniaewater composition. Turbine inlet temperature, T1 ( C) Pressure (bar) Mole fraction Ammonia Water Efficiency hi (%) hii (%)

100 62.5 1 0 13.16 16.08

Fig. 15. Sensitivity analysis of ammonia concentration.

Table 10 shows the results obtained from the optimisation of the alcoholewater composition. A sensitivity analysis for this composition was made to compare between the performance of the alcohol as a pure fluid and the performance of steam. The operating pressure of the mixture, however, was above the maximum operating pressure of 50 bar for the saturated vapour cycle configuration. An analysis on the performance of the mixture with a limiting pressure of 50 bar was carried out. As seen in Fig. 17, the efficiency of the mixture was higher for the temperature range of 220  Ce 250  C, exceeding the efficiency of the steam Rankine Cycle. Even with at 50 bar, the mixture is shown to have a higher performance for the range of 230  Ce250  C. The performance of the fluid below that temperature would result in a two-phase mixture at the turbine inlet. Another sensitivity analysis was performed to consider impact of using different alcohols. The optimisation resulted in steam as the better performing working fluid. An ethanol mol fraction of

Table 9 Optimal ammoniaewater composition with the pressure constraint of 50 bar. 150



107.6 0.949 0.051 15.87 18.14

129.7 0.886 0.114 16.85 18.62

178.1 0.738 0.262 17.66 19.13

Turbine inlet temperature, T1 ( C) Pressure (bar) Mole fraction Ammonia Water Efficiency hi (%) hii (%)

100 50 1 0 10.52 12.86

150 50 0.935 0.065 11.71 13.38

200 50 1 0 12.44 13.75

250 50 1 0 13.20 14.30

250 39.1 0 1 15.01 16.26

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Fig. 18. Analysis of ethanolewater mixture. Fig. 16. Sensitivity analysis for ammoniaewater mixture with pressure constraint.

Table 10 Optimal methanolewater mixture. Composition T1 ( C) P1 (bar) Efficiency

Methanol Water

hi (%) hii (%)

0.73488 0.26512 250 77.2 16.74 18.14

250 50.0 15.97 17.3

obtained. For the 100  Ce130  C, ammonia as a pure component had the highest efficiency followed by the n-Butane for the range of 130  C and 150  C. The ammoniaewater mixtures, at the different compositions, seemed to be the best performing fluid at higher temperatures up to 250  C. However, it should be kept in mind that these performances required a high operating pressure, up to 180 bar. The performance achieved by ammonia also required an operating pressure above the maximum pressure which was set for the study. Applying the maximum pressure constraint, a different set of optimal working fluid choices was obtained as shown in Fig. 20. The

60.2% in the mixture showed a higher efficiency of 12.32%. It could be seen from the trend in Fig. 18 that the mixture can provide a better cycle performance for the range of 170  Ce230  C. Grouping the results together, a pure methanol working fluid was the best fluid up to 220  C followed by the methanolewater mixture for up to 250  C. 7. Overall comparison The analysis of steam, organic working fluids, ammoniaewater mixture and alcoholewater mixture presented different optimum working fluids and compositions at different temperature intervals. These results were combined together in this section to investigate the optimum choice of working fluid as a whole. The working fluids which appeared to be the most appropriate choice for each of the cases are first presented in Fig. 19 without any operating pressure constraints. The results showed that the optimal components were very competitive to one another, with a difference of thermal efficiencies as close as 1%. Also Fig. 19 clearly demonstrates that inappropriate choice of working fluids and associated operating conditions results in a considerable reduction in energy efficiency about 5e12%, compared to the best efficiencies

Fig. 17. Sensitivity analysis of methanolewater mixture.

Fig. 19. Overall comparison for optimal working fluids without pressure constraint.

Fig. 20. Overall comparison for optimal working fluids with maximum pressure constraint.

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hydrocarbons and the refrigerant presented as the more efficient working fluids for the ranges of 100  Ce200  C, because of the characteristics of the components to produce high efficiency at lower operating pressures. Between 200  C and 230  C, methanol showed the highest efficiency among the working fluids followed by a methanolewater mixture to up to 250  C. The results of the methanolewater mixture were shown to perform better than the Kalina cycle and steam-based cycle even with limiting the operating pressure.

8. Conclusions and future work This research showed that mixed-composition fluids might only be beneficial if there are strong interactions between the components, like the ammoniaewater mixture and the alcoholewater mixture. Due to weak interactions between the organic hydrocarbons, the pure component fluids have been shown to produce higher efficiencies in a cycle. The composition of ammonia and water mixture should be optimised to achieve the optimal performance. Different compositions were obtained at different temperatures and pressures. The alcoholewater mixtures have showed potential in increasing the efficiency of a cycle, especially at temperatures of 220  Ce250  C. The optimisation framework developed in this study has been proven to produce reliable results for the optimisation of pure components and multi-component fluids. Without the aid of the automated design procedure and optimisation solver, manually investigating different compositions for an optimum performance would have been too lengthy. The developed design framework allows users to evaluate impacts of using different working fluid in the cycle in confidence, and to fully appreciate the benefit gained from simultaneous decision on the choice of working fluid and optimal operating conditions. From Figs. 19 and 20, it was clearly illustrated that considerable loss in energy efficiency around 5e12%, can be avoided with the careful consideration in the choice of working fluid and operating conditions. The results presented in this paper, however, were limited to a single cycle configuration, namely, the saturated vapour cycle. Alternative cycle configurations to increase the efficiency of the cycle could include the use of superheated vapour at the turbine inlet, supercritical pressure cycles and implementing the use of a recuperator or even multiple recuperators in the cycle. The results presented in this paper were also limited to a constant temperature profile for the heat source and heat sink. For a sloping temperature profile, the organic mixture may be more beneficial than the pure components for the exploitation of the temperature profile. The difference between the sloping temperature profile and the constant temperature profile would suggest that the optimisation of the mixtures (organic, ammoniaewater or alcoholewater) would have been different. The results presented for novel alcoholewater mixtures showed considerable potential in increasing the efficiency of a power cycle.

Acknowledgement Financial support from European Union’s FP7 Programme EFENIS project (No. 296003) is gratefully acknowledged. This research was supported by the International Research & Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (No. 20110031290).

Appendix A. Rankine Cycle results Table A1 Details of Rankine Cycle Simulation Results. Mass Wnet T1 P1 T3 P3 Molar flow (kW) ( C) (bar) ( C) (bar) flow (kmole/s) (kg/s)





Condensing duty (kW)

130 140 150 160 170 180 190 200 210 220 230 240 250

1.63 3.19 4.65 6.02 7.30 8.50 9.62 10.68 11.66 12.59 13.45 14.26 15.01

1.90 3.68 5.32 6.82 8.21 9.50 10.69 11.80 12.83 13.79 14.68 15.50 16.26

984 968 953 940 927 915 904 893 883 874 865 857 850

2.7 3.6 4.8 6.2 7.9 10.0 12.5 15.4 18.9 23.0 27.6 33.0 39.1

30 30 30 30 30 30 30 30 30 30 30 30 30

1 1 1 1 1 1 1 1 1 1 1 1 1

0.0211 0.0210 0.0208 0.0207 0.0206 0.0205 0.0204 0.0203 0.0203 0.0202 0.0201 0.0201 0.0201

0.38 0.38 0.38 0.37 0.37 0.37 0.37 0.37 0.37 0.36 0.36 0.36 0.36

16.30 31.92 46.52 60.20 73.00 85.00 96.24 106.78 116.64 125.88 134.52 142.59 150.11

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Nomenclature _ heat capacity flowrate [kW/ C] C: h: enthalpy [kJ/kg]


_ mass flowrate [kg/s] m: P: pressure [bar] Q_ : heat flow [kW] s: entropy [kJ/K] T: temperature [ C] _ volumetric flowrate [m3/s] V: W: work [kW] Greek symbols h: efficiency [e] Abbreviations CAMD: computer-aided molecular design CFC: chlorofluorocarbon CHP: combined heat and power EOS: equation of state GWP: global warming potential HCFC: hydrochlorofluorocarbon MM: hexamethyldisiloxane NLP: non-linear programming ODP: ozone depleting potential ORC: Organic Rankine Cycle SA: simulated annealing TFC: trilateral flash cycle

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