Edited by: Vincent Lemort, University of Liège, Belgium
Reviewed by: Xiaofeng Guo, ESIEE Paris, France; Santanu Bandyopadhyay, Indian Institute of Technology Bombay, India
This article was submitted to Process and Energy Systems Engineering, a section of the journal Frontiers in Energy Research
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This paper presents the optimization of organic Rankine cycles (ORCs) for recovering waste heat from a hypothetical aluminum production plant to be installed in Norway. The case study is particularly interesting because it features two hot streams at different temperatures (the pot exhaust gases and the cell wall cooling air), which make available about 16 MWth below 250°C. First, a recently proposed cycle optimization approach is adopted to identify the most promising working fluid and optimize the cycle variables (pressures, temperatures, mass flow rates) for the maximum energy performance. The analysis includes both pure fluids, including recently synthesized refrigerants, and binary zeotropic mixtures assessing in total 102 working fluids. The best pure fluid in terms of exergy efficiency turns out to be HFE-347mcc (which can achieve a target exergy efficiency of 85.28%), followed by neopentane, butane, and R114. HFO-1336mzz appears to be one of the most promising non-flammable alternatives with low Global Warming Potential (GWP). The mixture leading to the highest exergy efficiency is isobutane–isopentane, which can increase the net electrical power output by up to 3.3% compared to pure fluids. The systematic techno-economic optimization, repeated for two different electricity prices, shows that RE347mcc is the best option in both low and high electricity prices. The cost of the cycle using HFO-1336mzz is penalized by the larger evaporation heat (negatively influencing the heat integration) and the smaller regenerator.
With the current aim of energy saving in order to reduce emission and effort to diminish environmental impact of process and manufacturing plant, energy recovery from industrial processes is becoming a major topic. For instance, it was estimated that the “energy wasted by all U.S. industrial facilities could produce power equivalent to 20% of U.S. electricity generation capacity, without burning any fossil fuel, and could help many industries to meet recent global warming regulation” (Sami,
Given the heat source temperatures and relatively small size of the heat recovery Rankine cycle, organic fluids are expected to outperform steam as working fluid (Cavallini,
In this work, a future aluminum plant case study, based on Norwegian conditions, is selected to evaluate the benefits of heat recovery. The plant features two hot streams at different temperatures: one stream from the cooling medium of the pot cell walls (cathode) and one from the pot flue gases. The objective of the work is to identify the optimal ORC design [working fluid, pressures, temperatures, mass flow rates, layout, and heat exchanger network (HEN)] as well as the energy and economic performance with state-of-the-art computer-aided tools. The main peculiarity of the plant is the availability of two hot streams with different temperatures, which calls for the use of heat integration methodologies. For this reason, working fluid and cycle pressure and temperatures are optimized with the systematic optimization approaches recently proposed by Scaccabarozzi et al. (
The case study is a future aluminum production plant based on Norwegian conditions. The plant is based on several electrolytic reduction cells (also called “smelters”), which operate at high temperature (about 940–980°C) absorbing about 10 kWh/kgAl. It is assumed that in novel aluminum production processes, about 35% of the electricity is converted into heat and released with the stream of flue gases leaving the pot at about 180°C and the pot shell cooling air at approximately 250°C.
General scheme of the case study
Since performing a detailed techno-economic optimization of the ORC for each possible working fluid is clearly not practicable because of the required computational time, three classes of computationally efficient approaches have been proposed:
- Screening approaches: numerical methods are employed to select the cycle configuration and operating parameters for a set of candidate fluids, which is identified based on engineering criteria [see, e.g., (Wang et al.,
- Computer-aided molecular design methods [see, e.g., (Papadopoulos et al.,
- Molecular targeting methods [see, e.g., (Lampe et al.,
For a thorough review of computer-aided fluid selection and ORC design optimization methods, the reader is referred to Linke et al. (
In this work, the screening approach proposed by Scaccabarozzi et al. (
The complete list of pure fluids and mixtures considered in this work is listed in
List of the pure fluids and mixtures considered in this study.
Alkanes | Propane, Propyne, Propylene, Butane, Cisbutane, 1-Butene |
Perfluorocarbon (PFC) | R218, C4F10, C5F12, RC318 |
Hydrofluoroolefin (HFO) | R1234yf, R1234ze, R1233zde, R1336mzz, R1216 |
Hydrofluoroether (HFE) | RE134a, RE245cb2, RE245fa2, RE347mcc |
Hydrofluorocarbon (HFC) | R161, R227ea, R236ea, R236fa, R245fa, R345ca, R365mfc |
Chlorofluorocarbon (CFC) | R11, R12, R113, R114, R115 |
Hydrochlorofluorocarbons (HCFC) | R21, R22, R123, R124, R141b, R142b |
Siloxanes | MM, MDM, MD2M, MD3M, MD4M, D4, D5, D6 |
Fluorinated Ketone | Novec649 |
R1233zde/R134a (Scaccabarozzi et al., |
Given the set of available hot and cold streams of the plant, for each candidate working fluid (pure fluids and/or mixtures), the algorithm of Scaccabarozzi et al. (
Where
Since the denominator of Equation (1) and (2) are problem data, maximizing
The methodology (Scaccabarozzi et al.,
Block-flow diagram of the algorithm.
The evolutionary algorithm PGS-COM optimizes the independent cycle variables, namely, the evaporating and condensing pressure, the turbine inlet temperature, and the mixture composition. Each combination of independent cycle variables sampled by PGS-COM is given as input to the black-box, which solves the cycle model to calculate the dependent variables (e.g., streams temperature profiles, mass flow rates, etc.) and the objective function (second law efficiency).
In the black-box, the ORC model is implemented in Matlab® R2015 (The MathWorks Inc,
Vapor fraction of the flow evolving in the expander greater or equal to 0.88;
Temperature difference in the heat exchangers ≥ 5°C;
Condensation pressure ≥ 0.03 bar.
These constraints are handled within PGS-COM with the extreme barrier approach (see Astolfi et al.,
Once all the cycle-specific and intensive properties are determined, only the mass flow rates of the ORC and cooling water are missing. The heat integration between ORC streams and heat sources/heat sinks is optimized with the methodology proposed by Kalitventzeff and Maréchal (
where
For each fluid, the average total computational time to reach convergence of the PGS-COM algorithm is approximately 30 min, corresponding to about 2,000 function evaluations.
List of the 10 best performing pure fluids.
1 | RE347mcc | 164.55 | 24.76 | 160.71 | 22.63 | 77.25 | 0.70 | 78.76 | 3530.63 | 22.68 | 85.28 | 0 | 530 | No |
2 | Neopentane | 160.59 | 31.96 | 159.52 | 29.51 | 70.05 | 1.67 | 35.52 | 3502.03 | 22.50 | 84.59 | 0 | 0 | Yes |
3 | Butane | 151.98 | 37.96 | 164.20 | 39.05 | 56.23 | 2.38 | 30.44 | 3472.07 | 22.31 | 83.86 | 0 | 4 | Yes |
4 | R114 | 145.68 | 32.57 | 163.92 | 33.99 | 68.59 | 2.10 | 85.58 | 3471.72 | 22.31 | 83.85 | 1 | 10040 | No |
5 | R115 | 79.95 | 31.29 | 192.16 | 41.23 | 139.96 | 8.88 | 115.73 | 3457.61 | 22.22 | 83.51 | 1 | 7370 | No |
6 | Isobutene | 144.94 | 40.09 | 165.27 | 42.04 | 55.66 | 2.99 | 30.76 | 3448.18 | 22.15 | 83.28 | 0 | 0 | Yes |
7 | R143a | 72.71 | 37.61 | 199.52 | 51.28 | 135.11 | 12.40 | 67.93 | 3447.73 | 22.15 | 83.27 | 0 | 4470 | Yes |
8 | 1-Butene | 146.14 | 40.05 | 165.34 | 41.86 | 50.96 | 2.92 | 30.85 | 3438.87 | 22.09 | 83.06 | 0 | 0 | Yes |
9 | Propylene | 91.06 | 45.55 | 205.94 | 54.43 | 125.28 | 11.17 | 30.42 | 3437.25 | 22.08 | 83.02 | 0 | 1.8 | Yes |
10 | R245fa | 154.01 | 36.51 | 160.30 | 33.34 | 57.13 | 1.45 | 58.55 | 3434.26 | 22.07 | 82.95 | 0 | 812 | No |
List of the 10 best performing mixtures.
1 | Isobutane/Isopentane |
153.82 | 37.53 | 166.52 | 38.50 | 60.86 | 2.06 | 32.06 | 3648.35 | 23.44 | 88.12 | Yes |
2 | Novec649/1-Butene |
154.52 | 33.66 | 165.26 | 34.50 | 67.71 | 1.62 | 46.98 | 3642.70 | 23.40 | 87.98 | No |
3 | Isobutane/Pentane |
152.57 | 37.99 | 166.85 | 39.19 | 61.03 | 2.17 | 31.78 | 3626.91 | 23.30 | 87.60 | Yes |
4 | R1336mzz/1-Butene |
153.09 | 36.25 | 166.05 | 37.34 | 50.45 | 1.78 | 42.87 | 3618.59 | 23.25 | 87.40 | No |
5 | Novec649/Isobutane |
148.83 | 35.87 | 165.74 | 37.24 | 62.59 | 2.06 | 44.37 | 3611.39 | 23.20 | 87.23 | No |
6 | Butane/Pentane |
167.43 | 37.85 | 158.51 | 31.42 | 48.56 | 1.45 | 30.28 | 3602.86 | 23.15 | 87.02 | Yes |
7 | Isopentane/R245fa |
175.44 | 40.52 | 167.04 | 33.71 | 55.51 | 1.23 | 42.56 | 3601.18 | 23.14 | 86.98 | No |
8 | Novec649/Transbutene |
147.41 | 36.16 | 164.94 | 37.42 | 64.02 | 2.15 | 42.56 | 3601.08 | 23.14 | 86.98 | No |
9 | R1234ze/Cisbutene |
140.27 | 43.85 | 172.77 | 47.24 | 58.94 | 3.03 | 43.01 | 3595.16 | 23.10 | 86.83 | No |
10 | R1336mzz/Isobutane |
142.94 | 34.19 | 163.07 | 35.70 | 66.77 | 2.21 | 42.48 | 3594.28 | 23.09 | 86.81 | No |
Similar to what was done by Scaccabarozzi et al. (
Exergy efficiency of the considered pure fluids
Temperature–entropy (T–s) diagram and composite curves (T–Q diagrams) of the optimized organic Rankine cycle (ORC) employing RE347mcc
As far as mixtures are concerned, the best zeotropic mixture (in terms of energy efficiency) is isobutane (66% mass basis)–isopentane (34%), leading to an exergy efficiency gain of about 2.8 percentage points with respect to the best pure fluid. The corresponding increase in net power output of the ORC is 3.3%. The optimal cycle is supercritical for the first 10 mixtures, except for the sixth and seventh (butane/pentane, isopentane/R245fa). Unfortunately, all the mixtures in the first positions contain a high concentration of hydrocarbons, which may lead to safety issues related to fluid flammability.
Given the results of the thermodynamic optimization, the safety issues of flammable fluids and the current limitations on the ODP, HFE-RE347mcc, and HFO-R1336mzz are selected for the technoeconomic optimization. Despite its flammability, the mixture isobutene/isopentane is also considered in the technoeconomic optimization with the goal of assessing the potential economic advantage of using zeotropic mixtures compared to pure fluids.
The pure fluids and the mixture selected in Fluid Ranking and Selection are compared from a technoeconomic point of view, keeping the cycle parameters (i.e., cycle pressures and temperatures) fixed at the optimal values found in thermodynamic optimization. The goal of the technoeconomic optimization is to determine the best trade-off between energy efficiency and capital costs of the ORC and the heat exchanger network (HEN). To the best of the authors' knowledge, the problem of the technoeconomic optimization of the design of the integrated HEN and ORC has been addressed only by few works in literature. Desai and Bandyopadhyay (
Martelli et al. (
The method proposed by Martelli et al. (
Scheme of the combined HEN + ORC superstructure for techno-economic optimization. Hot and cold streams are represented with arrows pointing respectively to the right and to the left. In temperature stage
The mathematical model is characterized by the following variables, constraints, and objective function.
Heat exchanged between each hot stream and each cold stream (process, ORC, and cooling water streams) in each temperature stage of the HEN (positive continuous variables),
Temperature of each hot and cold non-isothermal stream at hot end of each stage (continuous variables),
Temperature difference for each heat exchanger between each hot and cold stream at hot end of each stage (positive continuous variables),
Activation of the heat exchanger between each hot stream and each cold stream in each stage (binary selection variables),
Area of the heat exchanger between each hot stream and each cold stream in each stage (positive continuous variables),
Activation of each ORC stream (binary selection variables),
Mass flow rate of each ORC stream (positive continuous variables).
Overall energy balances for all hot and cold streams in the HEN,
Stage energy balances for all hot and cold streams in the HEN,
Monotonicity of temperature profiles of streams along the stages,
Logical constraints relating the heat exchanger load and area with the corresponding binary variables for the selection of the heat exchangers, for all possible matches between hot and cold streams,
Logical constraints relating the continuous variables representing the mass flow rate for all streams of the ORC and the corresponding binary variables for the selection of the streams,
Additional logical constraints relating the existence of ORC streams with the existence of all possible heat exchangers involving them,
Mass and energy balances at each header of the
Constraints to calculate the temperature differences for the selected heat exchangers,
Relation between heat exchanger areas, mean logarithmic temperature differences, global heat transfer coefficient, and heat duty of the heat exchanger.
The non-linear objective function to be minimized is the total annual cost (TAC) of the overall HEN and ORC, which includes the sum of the investment costs for the HEN, for the ORC, the operational costs due to cooling water pumping and auxiliaries' consumption, and the avoided costs for buying the produced electricity from the grid at the wholesale price:
The variables that appear in the formula above are as follows: ṁ
As shown in Martelli et al. (
The main assumptions used for the technoeconomic optimization are reported in
Data for the techno-economic optimization.
Isentropic efficiency of turbine (Martelli et al., |
0.8 |
Hydraulic efficiency of pump | 0.8 |
Mechanical/electrical efficiency of turbine, η |
0.9 |
Mechanical/electrical efficiency of pump, η |
0.9 |
Convective heat transfer coefficient of air (process streams), W/m2K | 70 |
Convective heat transfer coefficient of cooling water, W/m2K | 1,500 |
Convective heat transfer coefficient of liquid and boiling pure fluids (organics with liquid dynamic viscosity <0.5 10−3 Pa s) (Cavallini, |
1,500 |
Convective heat transfer coefficient of liquid organic mixture (organics with liquid dynamic viscosity <0.5 10−3 Pa s) (Cavallini, |
1,500 |
Convective heat transfer coefficient of boiling organic mixture (organics with liquid dynamic viscosity <0.5 10−3 Pa s) (Azzolin et al., |
750 |
Convective heat transfer coefficient of superheated fluid (organics with liquid dynamic viscosity <0.5 10−3 Pa s) (Cavallini, |
1,000 |
Convective heat transfer coefficient of condensing pure fluid (organics with liquid dynamic viscosity <0.5 10−3 Pa s) (Cavallini, |
3,000 |
Convective heat transfer coefficient of condensing mixtures (organics with liquid dynamic viscosity <0.5 10−3 Pa s) (Azzolin et al., |
2,400 |
Specific investment cost for turbine at the reference size |
430 |
Scale factor for turbine cost, α | 0.67 |
Specific cost for heat exchangers at the reference size |
400 |
Scale factor for heat exchanger cost, β | 0.6 |
Annualization factor, |
0.2 |
Equivalent operating hours, |
7,008 |
Multiplication factor for costs due to engineering, procurement and construction, |
1.5 |
Cooling water pumping and auxiliaries' cost, |
3 |
Two scenarios for the technoeconomic optimization study are considered:
Low electricity price,
High electricity price,
Due to large power consumption of the aluminum production process, the electricity generated by the ORC is not sold to the electric grid but self-consumed by the plant, leading to savings in the electricity bill (i.e., it represents an avoided cost). For this reason, the economic value of electricity is representative of the average electricity purchase price of the plant (not the electricity selling price). The low electricity price of 70 $/MWh in this work is meant to represent a realistic price within the next 10 years in Norway. The average electricity spot price of the Nordpool (Nordpool,
Due to the lack of reliable literature data, the extra equipment costs required to prevent fluid leakages and to perform fluid makeup are not considered. These additional costs are expected to be higher for the zeotropic mixture as better sealing systems are required. Indeed, as reported in Kruse and Rinne (
As far as the HEN superstructure is concerned, five temperature stages have been considered for all working fluids, yielding MINLP problems with 592 single equations, 332 continuous variables, and 73 binary variables. The computational time on a single-core computer for convergence of the bilevel decomposition algorithm (Elsido et al.,
The optimization results for the low and high electricity price case are presented, respectively, in
Results of the techno-economic optimization for the low electricity price scenario (70 $/MWh).
Mass flow rate ORC working fluid, kg/s | 69.32 | 45.84 | 24.42 |
Regenerator (Yes/No) | Yes | Yes | Yes |
Net electric power, kW | 2316.2 | 1857.4 | 2045.5 |
Net electric efficiency η |
14.85 % | 11.91 % | 13.11 % |
Exergy efficiency η |
51.11 % | 40.99 % | 45.14 % |
Number of heat exchangers | 6 | 5 | 5 |
Total heat transfer area, m2 | 8,977 | 6,398 | 7,201 |
Cost of heat exchangers, k$ | 2007.4 | 1475.6 | 1686.2 |
Cost of machinery, k$ | 1215.2 | 1042.9 | 1143.3 |
TAC (ORC and HEN), k$/year | −272.5 | −236.7 | −246.6 |
Results of the techno-economic optimization for the high electricity price scenario (140 $/MWh).
Mass flow rate ORC working fluid, kg/s | 77.77 | 63.37 | 31.65 |
Regenerator (Yes/No) | Yes | Yes | Yes |
Net electric power, kW | 2598.4 | 2567.8 | 2653.0 |
Net electric efficiency η |
16.66 % | 16.46 % | 17.01 % |
Exergy efficiency η |
57.34 % | 56.66 % | 58.54 % |
Number of heat exchangers | 7 | 7 | 6 |
Total heat transfer area, m2 | 13,195 | 14,202 | 13,127 |
Cost of heat exchangers, k$ | 2646.6 | 2841.0 | 2730.6 |
Cost of machinery, k$ | 1312.6 | 1295.6 | 1361.1 |
TAC (ORC and HEN), k$/year | −1639.2 | −1552.1 | −1658.2 |
Optimized schemes of the optimal solutions found with fluid RE347mcc
Optimized schemes of the optimal solutions found with fluid RE347mcc
For all working fluids and in both price scenarios, the optimal solution found by the algorithm is a single pressure level ORC cycle with regenerator and the TAC is negative (meaning that there is an economic advantage in installing the ORC). The regenerator is used in all cases because organic vapors (on the hot side of the regenerator) feature a heat transfer coefficient higher than streams H1 and H2 (air): to preheat the liquid, from an economic point of view, it is more advantageous to use the regenerator instead of the economizers. In the low electricity price case, the cycle using RE347mcc achieves the best efficiency and economic performance, with net electric power output equal to 2316.2 kW (−34% compared to the ideal target) and TAC equal to −272.5 k$/year (being negative, it is a revenue). The difference in electric power output between the economic optimization solution and the thermodynamic target is due to 1) the expansion losses in the real cycle turbine featuring an isentropic efficiency equal to 80% and 2) the decrease of heat recovered from the heat sources. Concerning the last point, the economically optimal solution has −13.5% working fluid mass flow rate compared to the target found with the thermodynamic optimization owing to the need of containing the investment cost of the heat exchangers. Compared to RE347mcc, the economic profit of the solutions obtained using R1366mzz and the isobutane/isopentane mixture is −15.1 and −9.5%, respectively. The main reason appears to be the lower working fluid mass flow rate (25–28% lower than the target), which limits the net electric power output (−24.7 and −11.7%, respectively, compared to RE347mcc). Interestingly, the reduction of mass flow rate compared to the thermodynamic target is about double of that found for RE347mcc (−13.5%). This is due to (1) pinch point at the evaporator, which limits the working fluid mass flow rate, and (2) costly recovery of low-temperature heat from heat source H2. Concerning the evaporator, in the low electricity price scenario, there is no evaporator coupled with heat source H1 (or the high-temperature heat exchanger in the case of the mixture) in any of the three fluids, because it would be highly expensive due to the low heat transfer coefficient of the hot stream and the small temperature difference (stream H1 has an inlet temperature quite close to the evaporation temperatures). Therefore, the mass flow rate of fluid that can be evaporated is limited by the heat of H2 available from 250°C to the pinch point with the evaporation temperature (or critical temperature in case of supercritical fluid). RE347mcc has a smaller enthalpy of evaporation (equal to 36.95 kJ/kg) compared to R1336mzz (63.65 kJ/kg), and this allows the generation of a larger mass flow rate of vapor using only the heat available for the evaporator in H2. For R1336mzz, the mass flow rate of generated vapor is limited by the heat available in H2 for evaporation, and this causes a considerable reduction of heat recovery compared to the thermodynamic optimization. The ORC using the mixture shares the same issue as R1336mzz because of the large heat capacity of the supercritical fluid around the critical temperature (between 150 and 165°C), equal to 143 kJ/kg. For R1336mzz and the mixture given the limited mass flow rate of working fluid raised by the evaporator (for the mixture, the high-temperature heat exchanger HX3), it is sufficient to use the regenerator and the economizer in H1 for liquid preheating. For RE347mcc, given the larger mass flow rate of fluid, another economizer is necessary to preheat the liquid recovering heat from H2 leading to a higher heat recovery rate compared to the other two fluids (this is evident looking at the outlet temperatures of stream H2 reported in
For the scenario with high electricity prices (e.g., the plant benefits from incentives), the amount of recovered heat and the mass flow rate of working fluids are very close to the thermodynamic target. As already pointed out by Elsido et al. (
For both pure fluids and mixtures, there is clear relation between the maximum achievable exergy efficiency and the critical temperature. The fluids achieving the highest efficiency feature a critical temperature in the range 80–84% of the maximum heat source temperature. The maximum efficiency cycle turns out to have a turbine inlet pressure close to the critical one. As an exception, R115, R143a, and propylene achieve close to maximum efficiency employing a highly supercritical turbine inlet pressure (their critical temperature is only 66–69% of the maximum heat source temperature).
The first ranked pure fluid is RE347mcc, which can achieve an exergy efficiency of 85.28% (corresponding to an ORC net power target of 3.53 MW) with a subcritical regenerated ORC. It appears to be a promising candidate since it is non-flammable, its ODP is zero, and the GWP is not excessive (530). If flammable fluids are discarded because of safety issues, the most promising alternatives seem to be R1336mzz (GWP = 2) and R1233zde (GWP = 1). In all solutions, the regenerator of the ORC is used to compensate for the relative scarcity of available heat below 80°C.
The use of binary zeotropic mixtures with optimized composition leads to a gain in exergy efficiency of 2.8 percentage points (+3.3% of ORC net power target). The most efficient solution employs a mixture of isobutane/isopentane (0.66/0.34) with a supercritical regenerated ORC. The efficiency gain compared to the pure fluids is mainly due to the temperature glide occurring in condensation.
The technoeconomic optimization, performed for RE347mcc, R1336mzz, and the mixture of isobutane/isopentane, shows that RE347mcc is the best option for low electricity prices (in absence of incentives). Its optimized ORC maintains good efficiency (generating 88% of the target mass flow rate of ORC vapor) as the electricity revenues more than compensate for the equipment costs. As a comparison, the optimized cycle using R1336mzz has an appreciable reduction of ORC mass flow rate compared to the target value (it generates only 72% of the target mass flow rate). The main reason appears to be the pinch point at the evaporator (due to larger enthalpy of evaporation of R1336mzz compared to RE347mcc) that limits the mass flow rate. Another important result is the economic advantage of using the regenerator to preheat the liquid in place of the economizers (which would recover heat from H1 and H2). This is due to the higher heat transfer coefficient of organic fluids compared to stream H1 and H2 (air). For high electricity prices, the economic optimum becomes close to the thermodynamic optimum in terms of energy performance and working fluid mass flow rates. Differences between economic performance of the different fluids are mainly due to the cost of the heat exchangers, favoring the fluid (RE347mcc) with larger regenerator.
The mixture results showed to be economically advantageous only for high electricity prices, although the relative difference compared to RE347mcc is small. The gain can likely not compensate for the extra equipment costs related to fluid flammability (i.e., need of a thermal oil loop) and to prevent fluid leakages (important issue for zeotropic mixtures), not considered in this work.
As far as fluid selection criteria are concerned, this work has shown that the thermodynamic performance of ORCs mainly depend on the critical temperature of the fluids while the economic performance is influenced also by other parameters, such as the de-superheating heat (available for the regenerator) and the evaporation enthalpy (influencing the heat integration with the available hot streams and the raised mass flow rate of working fluid).
All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Thermodynamic optimization results of all pure fluids ranked according to the exergy efficiency. Thermodynamic optimization results of all mixtures ranked according to the exergy efficiency.
1
RE347mcc
164.55
24.76
160.71
22.63
77.25
0.70
78.76
3530.63
22.68
85.28
0
530
2
Neopentane
160.59
31.96
159.52
29.51
70.05
1.67
35.52
3502.03
22.50
84.59
0
0
3
Butane
151.98
37.96
164.20
39.05
56.23
2.38
30.44
3472.07
22.31
83.86
0
4
4
R114
145.68
32.57
163.92
33.99
68.59
2.10
85.58
3471.72
22.31
83.85
1.00
10,040
5
R115
79.95
31.29
192.16
41.23
139.96
8.88
115.73
3457.61
22.22
83.51
1.00
7,370
6
Isobutene
144.94
40.10
165.27
42.04
55.66
2.99
30.76
3448.18
22.15
83.28
0
0
7
R143a
72.71
37.61
199.52
51.28
135.11
12.40
67.93
3447.73
22.15
83.27
0
4,470
8
1-Butene
146.14
40.05
165.34
41.86
50.96
2.92
30.85
3438.87
22.09
83.06
0
0
9
Propylene
91.06
45.55
205.94
54.43
125.28
11.17
30.42
3437.25
22.08
83.02
0
1.8
10
R245fa
154.01
36.51
160.30
33.34
57.13
1.45
58.55
3434.26
22.07
82.95
0
693
11
Transbutane
155.46
40.27
165.42
41.21
38.84
2.31
29.69
3425.99
22.01
82.75
0
0
12
R142b
137.11
40.55
168.55
43.66
54.16
3.32
55.11
3422.91
21.99
82.67
0.065
2,310
13
R22
96.15
49.90
212.67
65.63
95.38
10.01
54.53
3416.85
21.95
82.53
0.055
1,810
14
Isobutane
134.66
36.29
161.45
38.64
71.61
3.43
33.10
3411.95
21.92
82.41
0
0
15
RE245fa2
171.73
34.33
156.57
26.05
58.32
0.83
58.61
3408.83
21.90
82.33
0
812
16
R1336mzz
171.27
29.01
158.74
23.14
58.72
0.71
63.75
3407.64
21.89
82.31
0
2
17
R152a
113.26
45.17
179.18
52.87
66.68
5.85
39.64
3395.36
21.82
82.01
0
124
18
Cyclo-propane
125.15
55.80
170.07
62.09
50.75
7.12
27.60
3390.63
21.78
81.89
0
0
19
Propyne
129.23
56.26
172.33
62.29
37.48
5.74
24.27
3388.41
21.77
81.84
0
0
20
RE245cb2
133.66
28.86
157.80
30.58
78.91
2.02
73.17
3384.73
21.75
81.75
0
654
21
R12
111.97
41.36
177.00
48.34
72.96
6.38
79.18
3382.61
21.73
81.70
1
10,890
22
Propane
96.74
42.51
204.67
50.65
129.11
9.08
28.55
3373.41
21.67
81.48
0
3.3
23
R1233zde
165.60
35.73
157.15
29.77
37.63
1.28
59.86
3366.35
21.63
81.31
0
1
24
R124
122.28
36.24
164.68
40.12
75.46
3.75
75.77
3366.15
21.63
81.30
0.022
609
25
Cisbutane
162.60
42.26
157.51
37.00
26.78
2.12
29.81
3346.55
21.50
80.83
0
0
26
R227ea
101.75
29.25
198.86
33.91
143.74
4.31
86.42
3332.30
21.41
80.49
0
3,220
27
R161
102.10
50.10
176.85
59.17
73.03
9.09
32.90
3312.03
21.28
80.00
0
12
28
R125
66.02
36.18
194.67
49.89
144.69
13.53
99.24
3284.55
21.10
79.33
0
3,500
29
Novec649
168.66
18.69
163.69
17.02
98.98
0.37
97.25
3261.23
20.95
78.77
0
1
30
R345ca
174.42
39.41
139.46
21.12
50.66
0.98
55.47
3260.50
20.95
78.75
0
1,030
31
R134a
101.06
40.59
169.47
48.01
85.32
6.50
62.05
3221.80
20.70
77.82
0
1,430
32
R365mfc
186.85
32.66
129.37
11.28
61.10
0.55
56.86
3162.90
20.32
76.39
0
794
33
Isopentane
187.20
33.78
130.59
13.26
59.15
0.89
31.60
3155.30
20.27
76.21
0
0
34
RC318
115.23
27.78
200.85
29.85
146.65
2.86
82.62
3141.71
20.19
75.88
0
10,030
35
C4F10
113.18
23.23
195.58
25.46
150.77
2.46
99.00
3135.86
20.15
75.74
0
8,860
36
R236ea
139.29
34.20
138.85
26.46
63.03
2.02
73.79
3117.19
20.03
75.29
0
1,370
37
Pentane
196.55
33.70
126.98
10.41
56.47
0.66
29.65
3072.86
19.74
74.22
0
0
38
R123
183.68
36.62
129.29
14.37
39.14
0.89
66.07
3064.61
19.69
74.02
0.02
77
39
R218
71.87
26.40
166.85
33.67
131.41
8.51
145.98
3046.90
19.58
73.59
0
8,830
40
R1234ze
109.36
36.35
146.85
38.11
68.96
4.91
69.37
3039.16
19.53
73.41
0
6
41
RE134a
104.77
36.35
146.85
40.34
65.39
5.65
64.65
3000.75
19.28
72.48
0
5,560
42
Isohexane
224.55
30.40
121.97
5.13
62.80
0.27
30.73
2990.85
19.22
72.24
0
0
43
R113
214.06
33.92
122.05
7.10
50.63
0.43
71.75
2956.81
19.00
71.42
0.8
6,130
44
Hexane
234.67
30.34
120.35
4.03
59.65
0.19
29.17
2947.31
18.94
71.19
0
0
45
Heptane
266.98
27.36
119.31
1.80
62.20
0.06
28.57
2899.86
18.63
70.04
0
0
46
R141b
204.35
42.12
121.40
10.62
30.01
0.76
49.38
2889.18
18.56
69.78
0.11
725
47
C5F12
147.41
20.45
196.79
7.34
165.36
0.78
103.28
2881.32
18.51
69.59
0
9,160
48
R21
178.33
51.81
124.14
21.24
24.01
1.76
52.56
2878.49
18.49
69.52
0.04
151
49
R11
197.96
44.08
122.28
12.91
23.96
1.02
62.15
2862.24
18.39
69.13
1
4,750
50
R236fa
124.92
32.00
126.85
26.11
55.65
2.68
81.33
2851.31
18.32
68.87
0
9,810
51
R1234yf
94.70
33.82
136.84
37.61
71.90
6.72
80.17
2839.22
18.24
68.58
0
4
52
Methyl-cyclohexane
299.05
34.70
117.51
1.58
55.16
0.06
28.61
2829.06
18.18
68.33
0
0
53
Cyclopentane
238.57
45.71
119.59
6.45
31.98
0.40
26.19
2816.07
18.09
68.02
0
0
54
R32
78.11
57.82
161.85
71.59
52.72
16.60
42.82
2796.95
17.97
67.56
0
675
55
MM
245.55
19.39
201.60
1.05
162.76
0.05
38.05
2723.96
17.50
65.79
N.A.
N.A.
56
Toluene
318.60
41.26
116.09
1.18
29.60
0.03
25.11
2714.51
17.44
65.56
0
0
57
Benzene
288.87
49.07
115.42
2.68
23.38
0.12
24.68
2703.43
17.37
65.30
0
0
58
Cyclo-hexane
280.45
40.81
200.39
1.77
139.15
0.11
22.51
2671.46
17.16
64.52
0
0
59
R1216
85.75
31.50
126.84
35.10
75.12
7.26
107.21
2627.61
16.88
63.47
0
1
60
Octane
296.17
24.97
118.23
0.82
71.16
0.03
28.40
2469.54
15.87
59.65
0
0
61
MDM
290.94
14.15
129.44
0.53
104.65
0.03
45.94
1777.12
11.42
42.92
N.A.
N.A.
62
NONANE
321.40
22.81
127.40
0.52
91.12
0.03
25.37
1769.62
11.37
42.74
0
0
63
N-Propyl-cyclohexane
357.65
28.60
218.39
0.34
184.69
0.03
21.86
1657.53
10.65
40.03
0
0
64
Decane
344.55
21.03
229.31
0.28
203.22
0.03
19.72
1246.89
8.01
30.12
0
0
65
D4
313.34
13.32
223.91
0.26
205.10
0.03
39.82
1177.19
7.56
28.43
N.A.
N.A.
66
MD2M
326.25
12.27
228.18
0.20
213.99
0.03
35.43
885.34
5.69
21.38
N.A.
N.A.
67
Undecane
365.65
19.90
237.22
0.20
216.98
0.03
17.74
885.33
5.69
21.38
0
0
68
D5
346.08
11.61
233.22
0.16
221.55
0.03
35.40
661.65
4.25
15.98
N.A.
N.A.
69
Dodecane
384.95
18.17
242.03
0.15
226.40
0.03
15.38
598.78
3.85
14.46
0
0
70
MD3M
355.21
9.45
237.40
0.12
229.05
0.03
28.21
434.86
2.79
10.50
N.A.
N.A.
71
D6
372.63
9.61
240.12
0.10
233.59
0.03
27.45
310.76
2.00
7.51
N.A.
N.A.
72
MD4M
380.05
8.77
245.00
0.16
236.05
0.03
12.87
197.98
1.27
4.78
N.A.
N.A.
1
Isobutane
Isopentane
0.66
0.34
153.82
37.53
166.52
38.50
60.86
2.06
32.06
3648.35
23.44
88.12
Yes
2
Novec649
1-butene
0.50
0.50
154.52
33.66
165.26
34.50
67.71
1.62
46.98
3642.70
23.40
87.98
No
3
Isobutane
Pentane
0.73
0.27
152.57
37.99
166.85
39.19
61.03
2.17
31.78
3626.91
23.30
87.60
Yes
4
R1336mzz
1-butene
0.53
0.47
153.09
36.25
166.05
37.34
50.45
1.78
42.87
3618.59
23.25
87.40
No
5
Novec649
Isobutane
0.43
0.57
148.83
35.87
165.74
37.24
62.59
2.06
44.37
3611.39
23.20
87.23
No
6
Butane
Pentane
0.67
0.33
167.43
37.85
158.51
31.42
48.56
1.45
30.28
3602.86
23.15
87.02
Yes
7
Isopentane
R245fa
0.50
0.50
175.44
40.52
167.04
33.71
55.51
1.23
42.56
3601.18
23.14
86.98
No
8
Novec649
Transbutene
0.40
0.60
147.41
36.16
164.94
37.42
64.02
2.15
42.56
3601.08
23.14
86.98
No
9
R1234ze
Cis-butene
0.59
0.41
140.27
43.85
172.77
47.24
58.94
3.03
43.01
3595.16
23.10
86.83
No
10
R1336mzz
Isobutane
0.45
0.55
142.94
34.19
163.07
35.70
66.77
2.21
42.48
3594.28
23.09
86.81
No
11
Novec649
Propyne
0.56
0.44
142.05
43.93
172.22
46.79
56.79
2.94
41.84
3591.71
23.08
86.75
No
12
Novec649
Isobutene
0.59
0.41
163.82
34.70
157.43
28.50
58.42
1.29
50.45
3587.71
23.05
86.66
No
13
R1336mzz
Butane
0.86
0.14
165.18
31.39
157.32
25.98
55.94
0.96
56.94
3585.71
23.04
86.61
No
14
R245fa
R152a
0.49
0.51
126.51
42.87
174.44
47.86
61.83
3.44
46.89
3581.43
23.01
86.50
No
15
R1233zde
Cyclopropane
0.42
0.58
132.82
52.99
172.45
57.71
48.65
4.98
35.81
3575.38
22.97
86.36
No
16
Novec649
Cyclopropane
0.70
0.30
126.52
40.33
170.06
44.71
71.89
3.72
49.22
3573.14
22.96
86.30
No
17
R1234yf
Cis-butene
0.73
0.27
124.23
40.01
169.65
44.57
73.53
3.83
50.78
3572.59
22.95
86.29
No
18
R1336mzz
Cyclopropane
0.35
0.65
130.65
51.87
171.08
57.07
52.41
5.18
34.74
3556.58
22.85
85.90
No
19
R1233zde
R134a
0.35
0.65
120.28
41.97
174.22
47.69
73.33
3.97
60.90
3555.04
22.84
85.87
No
20
Butane
Cyclopentane
0.83
0.17
164.89
39.66
156.63
32.79
44.06
1.68
30.17
3552.44
22.82
85.80
No
21
R1233zde
Propyne
0.46
0.54
136.81
50.73
170.80
54.94
34.07
3.76
33.34
3551.77
22.82
85.79
No
22
R1336mzz
Propyne
0.37
0.63
134.44
51.13
171.28
55.06
40.52
4.05
31.48
3540.91
22.75
85.52
No
23
Butane
Hexane
0.92
0.08
159.52
38.85
156.32
31.94
54.61
1.88
30.34
3530.06
22.68
85.26
Yes
24
R1336mzz
Isobutene
0.50
0.50
151.74
36.61
155.90
30.23
57.82
1.86
42.24
3523.79
22.64
85.11
No
25
Novec649
Butane
0.34
0.66
131.64
50.86
171.18
53.88
49.97
4.36
32.45
3523.19
22.64
85.10
No
26
Novec649
Cisbutane
0.17
0.83
126.30
53.00
170.22
58.83
53.42
6.02
31.30
3512.02
22.56
84.83
No
27
Butane
Propane
0.31
0.69
114.93
43.94
168.68
50.03
76.13
5.93
31.01
3509.80
22.55
84.77
Yes
28
R1336mzz
R134a
0.23
0.77
111.97
39.73
168.90
45.60
78.19
4.47
63.88
3467.80
22.28
83.76
No
29
MM
MDM
0.88
0.12
249.45
18.75
122.22
1.52
79.00
0.04
46.89
3076.67
19.77
74.31
No
30
Toluene
Cyclohexane
0.28
0.72
279.61
36.96
118.84
2.08
37.59
0.07
26.23
2946.75
18.93
71.17
Yes