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Energy 172 (2019) 435e442

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Energy

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Sensitivity analysis of operation parameters on the systemperformance of organic rankine cycle system using orthogonalexperiment

Huan Xi a, Honghu Zhang a, Ya-Ling He a, *, Zuohua Huang b

a Key Laboratory of Thermo-Fluid Science and Engineering of Ministry of Education, School of Energy and Power Engineering, Xi'an Jiaotong University,Xi'an, 710049, Chinab State Key Laboratory of Multiphase Flow in Power Engineering, Xi'an Jiaotong University, Xi'an, 710049, China

a r t i c l e i n f o

Article history:Received 23 October 2018Received in revised form23 December 2018Accepted 14 January 2019Available online 18 January 2019

Keywords:Waste heat recovery(WHR)Organic rankine cycle(ORC)Sensitivity analysisOrthogonal experiment

* Corresponding author.E-mail address: yalinghe@mail.xjtu.edu.cn (Y.-L. H

https://doi.org/10.1016/j.energy.2019.01.0720360-5442/© 2019 Elsevier Ltd. All rights reserved.

a b s t r a c t

In the present study, a 1 kW-scale experimental system which can be switched between BORC (basicorganic Rankine cycle) and RORC (organic Rankine cycle with a regenerator) is employed. In order toanalyze the influence of working parameters on the system performance quantitatively, the rangeanalysis based on orthogonal design is adopted. The selected three system parameters are: the tem-perature at the inlet of the expander, temperature at the outlet of the condenser and the plunger travel ofworking fluid pump. For the system performance, six indices are selected, including the thermal effi-ciency, the back-work ratio, output power of the expander, pump work consumption, network and themass flow of the working fluid. The optimal and worst level constitutions of factors for the six indices areconcluded, the orders of the three factors' sensitivity to the six indices are also obtained. The resultsshow that the temperature at the inlet of the expander is the dominant factor of the thermal efficiency,the back-work ratio, output power of the expander, and network. While the plunger travel of the workingfluid pump is the dominant factor of pump work consumption and the mass flow of the working fluid.

© 2019 Elsevier Ltd. All rights reserved.

1. Introduction

In the past decade, organic Rankine cycle (ORC) has attracted alarge amount of attention. It has proved to be a very promisingtechnology for the efficient conversion of low-grade heat intoelectricity. The cycle configuration of ORC is similar to that of aconventional steam Rankine, involves four processes includingevaporation, expansion, condensation and compression. The onlydistinction is the working fluid: ORC using organic substancesinstead of using water. Many previous studies are available on ORC,the research so far mainly focused on optimization [1e4] andworking fluids selection [5e7] based on numerical calculation.However, as the ORC technology has been gradually getting ripe,the experimental studies of different ORC systems are increasinglyinvestigated.

Currently, regarding the experimental researches of ORC, manystudies have focused on the aspects of working fluids selection and

e).

comparison. Abadi GB et al. [8] evaluated the performance of asmall-scale ORC experimentally. Theworking fluid the adoptedwasa new zeotropic mixture of R245fa/R134a (0.6/0.4) (molar con-centration). The power output and thermal efficiency of the ORCsystem with this mixture were analyzed. The results showed thatthe proposed zeotropic mixture increases the power outputcompared to an identical ORC with pure R245fa. Shu G et al. [9]presented a series of experiments to compare the performance ofR123 and R245fa. The result showed that for heavy duty, R123 isbetter, while for light-and-medium duty, R245fa is more suitable.Performance test of R123 for waste heat recovery showed that themaximum fuel consumption should be improved as much as 2.8%.Dickes R et al. [10] built an experimental system to validated andcompared different modelling methods for the off-design simula-tion of ORC. Benefits and limitations of the methods were bothdiscussed. The results showed that semi-empirical models are themost reliable for simulating the off-design working conditions ofORC systems. Desideri A et al. [11] experimentally compared theperformance of an ORC system with two different working fluids,SES36 and R245fa. The results showed that themaximum expanderisentropic efficiencies obtained were about 60% and 52% when

H. Xi et al. / Energy 172 (2019) 435e442436

using SES36 and R245fa as the working fluids respectively. Eyerer Set al. [12] introduced a low-GWPworking fluid R1233zd-E, which isalso a promising alternative to R245fa. The cycle efficiency andpower output of two working fluids were compared. The resultsshowed that for the identical system, the use of R1233zd-ER1233zd-E performs 6.92% better than R245fa. However, for thepower output, R245fa performed 12.17% better than R1233zd-E.Navarro-Esbrí J and Mol�es F et al. [13,14] compared HFO-1336mzz-Z and R245fa experimentally under different heat andcold sink conditions. When using HFO-1336mzz-Z as the workingfluid, the maximum power generated was 1.1 kW, while the ther-mal efficiency ranged from 5.5% to 8.3%. The results showed thatthe thermal efficiency, isentropic efficiency of the expander ob-tained with HFO-1336mzz-Z in this work were higher than thoseobtained with R245fa in their previous work.

Many researchers also have carried out experimental researchesabout system performances under different working conditions. InRefs. [13,14], the authors changed the heat source temperaturesbetween 140 �C and 160 �C and heat sink temperatures between25 �C and 40 �C to measure the system performances underdifferent working conditions. Galloni E et al. [15] built a simple ORCsystem. The system performances were experimental tested byusing R245fa as theworking fluid. The heat source temperaturewasvaried in the range 75e95 �C and the cold sink temperature rangedbetween 20 �C and 33 �C. The electric power was about 1.2 kW.Shao L et al. [16] evaluated the performance of a 1 kW-scale ORCsystem. By using a self-designed radial inflow turbine and R123 asthe working fluid, system performance was tested under differentcooling conditions. The influence of cooling condition on systemand turbine performances were concluded. The obtainedmaximum thermal efficiency and net power were 5.30% and1.2 kW, respectively. In our previous work, related researches werealso carried out. A 1 kW ORC experimental system has been builtusing a scroll expander and a diaphragm pump. System perfor-mance under different condensing temperatures was experimen-tally tested [17]. By changing the key working parameters, thetransient responses of the two systems (i.e. basic ORC and ORC witha regenerator) under the controlled critical conditions were testedand compared, some physical explanations were provided [18].

A review of the previous literature reveals that for the experi-mental researches of ORC, large information can be found onexperimental research of working fluids selection. Experimentalresearches about system performances under different workingconditions have also been carried out in many studies. Whenstudying the system performance, the different working conditionswere usually creative by changing the key parameters, such as heat/cold source temperatures. However, few works try to reveal thequantitative rules about how the working parameters influence thesystem performances. Given this, the objective of this study is toanalyze the sensitivity of system parameters to the performance ofthe ORC systems quantitatively. The system parameters, such as thetemperature at the inlet of the expander (Tin_exp), the temperatureat the outlet of the condenser (Tout_con) and the plunger travel ofworking fluid pump (PTpump), are selected as three factors fororthogonal design. It should be mentioned that in some simulationworks, the orthogonal design was ever adopted to analyze thesystem performances [19,20], however, to the author's knowledge,few works adopted it in the experimental study of ORC system. Inthis work, the order of factors sensitivity on performance indices ofthe thermal efficiency, the back-work ratio, output power of theexpander, pump work consumption, network and the mass flow ofthe working fluid are determined by the range obtained from theorthogonal design. The order and contribution rate of three factorson the performance indices are determined and analyzedrespectively.

2. Apparatus

A 1 kW-scale experimental system mentioned in our previouswork is employed in this study [17,18]. The system consists of threeloops i.e. heat source loop, ORC loop and cooling water loop, andcan be switched between BORC and RORC by control valves 3 and 4,as can be seen in Fig. 1. The temperature at the outlet of thecondenser could be adjusted by control the cooling source tem-perature (the temperature of water in the cooling water tank). Thecooling water at the inlet of the contender is bypassed by valve 8 tocontrol the flow rate, while valve 6 is used to bypass part of waterleaving the condenser (with a relatively higher temperature) backto the cooling water tank, thus adjusting the water temperature inthe cooling water tank.

An electrical oil heated boiler is employed to present the low-temperature heat source. The expander adopted in this study is ascroll-type expander, which is converted from an air-conditionercompressor with a displacement of 86 ml/r (Nanjing Aotecar NewEnergy Technology Co., Ltd, models is WHX-086). The pumpadopted is a mechanical diaphragm pump. It should be pointed outthat for the diaphragm pump, the volume flow rate of the workingfluid is controlled by adjusting the plunger travel of the workingfluid pump. However, as one of the key parameters that can directlyinfluence the system performance, the mass flow rate of theworking fluid still cannot be exactly adjusted by just controlling theplunger travel of theworking fluid pump. It is also influenced by thepressure and temperature at the inlet and outlet of the pump.Therefore, the plunger travel of the working fluid pump is selectedas one of three key factors in this system, the mass flow rate of theworking fluids is selected as one of the six indices for the systemperformance.

3. Experiment plan

3.1. The orthogonal design

The orthogonal design is a method for the multi-factor experi-ment. By utilizing an orthogonal array, the number of experimentswill be reduced without developing the objective function [21]. Forexample, for a 3-factors 3-level design, the number of experimentsis reduced effectively from 27 to 9, as can be seen in Fig. 2. Ac-cording to the results of orthogonal design, the order of systemparameters' sensitivity to the performance index should beconcluded, the optimal level constitution of system parameters canalso be obtained by range analysis.

The temperature at the inlet of the expander (Tin_exp), thetemperature at the outlet of the condenser (Tout_con) and theplunger travel of the working fluid pump (PTpump), are selected asthree factors for orthogonal design. Six performance indices of theORC system are adopted as the estimating target of the orthogonaldesign, including: (1) I1: the thermal efficiency (ƞth), (2) I2: the backwork ratio (BWR), (3) I3: the output power of the expander(Wexp_shaft), (4) I4: the pump work consumption (Wpump_ele), (5) I5:the network (Wnet) and (6) I6: the mass flow of the working fluid(qm).

The factors and their levels are listed in Table 1. The three factorsare labelled as A ~ C. The four levels are represented by digits 1e4.Based on the numbers of factors and levels, the orthogonal array L16(43) is adopted. The layout of the experiment is listed in Table 2.

During the experiment, the factor C (PTpump) is easy to controland adjust. For the factor A (Tin_exp), it can be controlled byadjusting the power of the heat source. Factor B (Tout_con) is rela-tively difficult to adjust to set values, for it is controlled by adjustingthe valves 5 and 6. Therefore, for each system configurations, theexperiments in Table 2 are carried out as the following sequence:

Fig. 1. Schematic of the ORC apparatus.

Fig. 2. The sketches for uniform and orthogonal experiential designs.

Table 1The factors and levels based on orthogonal design.

Factors LevelsParameters 1 2 3 4A Tin_exp/oC 95 100 105 110B Tout_con/oC 24 26 28 30C PTpump/% 30 50 70 90

H. Xi et al. / Energy 172 (2019) 435e442 437

(1) 1-5-9-13 (begin from Tout_con¼ 24 �C, Tin_exp is increasedfrom 95 to 110 �C with the step of 5 �C, PTpump is increasedfrom 30% to 90% with the step of 20%).

(2) 14-10-6-2 (begin from Tout_con¼ 26 �C, Tin_exp is decreasedfrom 110 to 95 �C with the step of 5 �C, PTpump is changed inthe order of 70%e90%-30%e50%).

(3) 3-7-11-15 (begin from Tout_con¼ 28 �C, Tin_exp is increasedfrom 95 to 110 �C with the step of 5 �C, PTpump is changed inthe order of 70%e90%-30%e50%).

(4) 16-12-8-4 (begin from Tout_con¼ 30 �C, Tin_exp is decreasedfrom 110 to 95 �C with the step of 5 �C, PTpump is increasedfrom 30% to 90% with the step of 20%).

3.2. The indices of orthogonal design

For the network (Wnet) of the system, thermal efficiency (ƞth) of

the system and the can be obtained according to the experimentaland calculating results using Eqs. (1) and (3):

Wnet ¼ Wexp_shaft �Wpump_ele (1)

hth ¼ ðWexp_shaft �Wpump_eleÞ.Qeva ¼ Wnet=Qeva (2)

BWR ¼ Wpump_ele

.Wexp_shaft (3)

The pumpwork consumption can be calculated as the measuredline current (I) and line voltage (U) of the three-phase pump:

Wpump ele ¼ffiffiffi3

p,U,I,cos 4 (4)

where 4 is the phase angle.

Table 2The layout of the experiment.

No. Factors

A (Tin_exp/oC) B (Tout_con/oC) C (PTpump)

1 95 24 30%2 95 26 50%3 95 28 70%4 95 30 90%5 100 24 50%6 100 26 30%7 100 28 90%8 100 30 70%9 105 24 70%10 105 26 90%11 105 28 30%12 105 30 50%13 110 24 90%14 110 26 70%15 110 28 50%16 110 30 30%

H. Xi et al. / Energy 172 (2019) 435e442438

3.3. The range analysis

The range analysis is introduced to measure the sensitivity ofthe factors to the performance indices in the orthogonal design.Range value(R) is introduced to reflect the extent of the variable(factor) influencing the indices, which can be calculated as:

Ri ¼ maxIi;j �minIi;j (5)

where i presents the factor A-C in Table 1 j stands for the level of thefactors, from 1 to 4. Ri is the range value of factor i. Ii,j presents themean value of the index of factor i at level j. According to Eq. (5), thegreater the value of R is, the more sensitive the factor will be.

Ii,j in Eq. (4) can be calculated as:

Ii;j ¼1j

Xj

n¼1

Kj;n (6)

where j means the number of levels, equals 4 in this study. Kj,n

presents the experimental value of factor i at level j. For example,for BORC and index I1, it can be seen from Table 3 that Kj,1 of factor Ais equal to 1.2, Kj,2 is 1.28, Kj,3 is 1.21 and Kj,4 is 0.93. According to Eq.(6), I1,1 is equal to 1.155. By analogy, I1,2, I1,3 and I1,4 are equal to1.4375, 1.7125 and 1.9675, respectively. RA for index I1 (the ranger

Table 3Experiment results of BORC.

No. Factors Indices

A B C I1 I2 I3 I4 I5 I6

1 95 24 30 1.20 0.60 420.70 254.17 166.53 0.04412 95 26 50 1.28 0.57 419.47 239.83 179.64 0.04253 95 28 70 1.21 0.60 429.82 257.23 172.59 0.04664 95 30 90 0.93 0.67 412.46 275.76 136.70 0.05105 100 24 50 1.46 0.55 474.58 259.21 215.37 0.04886 100 26 30 1.51 0.53 450.53 239.12 211.41 0.04537 100 28 90 1.39 0.57 481.54 272.49 209.05 0.05348 100 30 70 1.39 0.57 471.43 267.20 204.23 0.05389 105 24 70 1.66 0.52 524.19 274.86 249.33 0.050210 105 26 90 1.72 0.50 545.48 272.79 272.69 0.056911 105 28 30 1.71 0.51 499.34 253.91 245.43 0.048612 105 30 50 1.76 0.49 536.36 262.80 273.56 0.056913 110 24 90 1.96 0.47 584.57 273.68 310.89 0.057114 110 26 70 2.00 0.46 573.80 263.16 310.64 0.048515 110 28 50 1.97 0.45 574.26 259.98 314.28 0.051316 110 30 30 1.94 0.47 546.67 259.52 287.15 0.0491

value of factor A) can be calculated using max IA,j-min IA,j accordingto Eq. (5), the value is 0.8215.

4. Results and discussion

The experiment results of BORC and RORC are listed in Tables 3and 4. The mean values of six indices of three factors at four levelscan be seen in Figs. 3e8. For the index I1 (ƞth), it can be seen fromFig. 3 that for BORC system, the maximum value for factor A isobtained at level 4, while for factor B and C, the maximum valuesare both obtained at level 2. For RORC, the maximumvalue of factorA is also obtained at level 4. However, for factor B and C, themaximum values are both obtained at level 1. Given the above, itcan be concluded that for BORC and RORC, the constitutions of A4-B2-C2 and A4-B1-C1 correspondwith the optimal (highest) thermalefficiency, respectively. For both systems, the constitution of A1-B4-C4 corresponds with the worst (lowest) thermal efficiency. Ac-cording to the method, based on the experimental results shown inFigs. 3e8, the optimal and worst level constitutions of factors forthe six indices are concluded in Table 5.

From Table 5, Figs. 3 and 4, it can be seen that for the factor A,when the level changes from 1 to 4, the value of index I1 (ƞth) in-creases linearly. However, for factor B and C, when the level changesfrom 1 to 4, the value of index I1 (ƞth) first increases then decreases,shows a different trend. It can be explained as follows: the value ofI1 (ƞth) is determined by I6 (Wnet) and Qeva, while Qeva is propor-tional to I7 (qm). Based on Eq. (1), I6 (Wnet) is determined by I4(Wexp_shaft) and I5 (Wpump_ele). It can be seen from Figs. 5e7 thatwhen the level changes from 1 to 4, I4 (Wexp_shaft), I5 (Wpump_ele), I6(Wnet) are both showing nonlinear behaviour, which is the cause ofthe non-monotone variation of I1 (ƞth) for factor B and C.

Also, from Fig. 4 it can be seen that for the factor A, when thelevel changes from 1 to 4, the value of I3(BWR) decreases linearly.Although the value of I5(Wpump_ele) shows a nonlinear behaviourwith the change of the level, however, the dominant factor,I4(Wexp_shaft), shows a strong linear behaviour (see Fig. 5), which isthe main parameter to influence the behaviour of I3(BWR). Simi-larly, I6 (Wnet) increases rapidly with the increase of levels of factorA, which is also caused by the change of I4(Wexp_shaft) as the keyparameter. From Figs. 6e8, it can be found that for factor B and C,when the level increases, I4 (Wexp_shaft) and I6 (Wnet) show mod-erate trends. It indicates that the effects of factor A on I4 (Wexp_shaft)and I6 (Wnet) is great than the factor B and C.

Fig. 9 shows the range analysis of the three factors

Table 4Experiment results of BORC.

No. Factors Indices

A B C I1 I2 I3 I4 I5 I6

1 95 24 30 0.95 0.68 381.86 259.41 122.45 0.04902 95 26 50 0.99 0.66 379.20 251.20 128.00 0.05513 95 28 70 0.67 0.75 355.32 265.45 89.87 0.06054 95 30 90 0.29 0.88 323.81 285.17 38.64 0.06375 100 24 50 1.38 0.57 452.30 259.79 192.51 0.06206 100 26 30 1.39 0.59 437.59 257.67 179.92 0.05567 100 28 90 0.65 0.76 399.71 304.21 95.50 0.08228 100 30 70 1.02 0.66 421.90 278.56 143.34 0.06219 105 24 70 1.74 0.53 508.13 268.25 239.88 0.062210 105 26 90 1.50 0.57 499.54 283.58 215.96 0.069911 105 28 30 1.76 0.53 488.80 258.98 229.82 0.056512 105 30 50 1.62 0.54 490.29 265.25 225.04 0.063613 110 24 90 1.83 0.52 579.15 303.46 275.69 0.078814 110 26 70 1.95 0.49 571.44 281.54 289.9 0.073815 110 28 50 1.92 0.50 565.62 285.09 280.53 0.071816 110 30 30 1.92 0.51 513.32 261.45 251.87 0.0573

Fig. 3. The mean value of index I1 of three factors at four levels.

Fig. 4. The mean value of index I2 of three factors at four levels.

Fig. 5. The mean value of index I3 of three factors at four levels.

H. Xi et al. / Energy 172 (2019) 435e442 439

corresponding to the six indices. From Fig. 9(a)-(b) it can be seenthat the for I1 (ƞth) and I2(BWR), the ranger values of factor A arelarger than that of other factors for both systems. For BORC, therange values of factor B and C are nearly the same. In the same way,

for I3(Wexp_shaft), I4(Wpump_ele), I5(Wnet) and I6 (qm), the dominantfactors are factor A, C, A, C, respectively. For the three factors weconsidered in the work, factor A is the dominant factor of I1 (ƞth), I2(BWR), I3 (Wexp_shaft) and I5 (Wnet), while factor C is the dominant

Fig. 6. The mean value of index I4 of three factors at four levels.

Fig. 7. The mean value of index I5 of three factors at four levels.

Fig. 8. The mean value of index I6 of three factors at four levels.

H. Xi et al. / Energy 172 (2019) 435e442440

factor of I4 (Wpump_ele) and I6 (qm). It should be noticed that for thetwo systems, the orders of the factors' sensitivity are not alwaysconsistent. For example, for I3(Wexp_shaft) in Fig. 9(c), the order of

the factors' sensitivity for BORC is A＞C＞B, however, for RORC, theorder is A＞B＞C. The order of the three factors' sensitivity to the sixindices are summarized in Table 6.

Table 5The optimal and worst level constitution of factors.

Indices BORC RORC

Maximum Minimum Maximum Minimum

A B C A B C A B C A B C

I1 4 2 2 1 4 4 4 1 1 1 4 4I2 1 4 4 4 2 2 1 4 4 4 1 2I3 4 1 4 1 4 1 4 1 2 1 4 4I4 3 4 4 1 2 1 4 3 4 1 2 1I5 4 2 2 1 4 4 4 1 2 1 4 4I6 3 4 4 1 2 1 4 3 4 1 4 4

Fig. 9. Range analysis of the three facto

H. Xi et al. / Energy 172 (2019) 435e442 441

5. Conclusions

Many previous experimental studies are available for ORC sys-tem under different working conditions. However, fewworks try toreveal the rules about how the working parameters influence thesystem performances, especially in a quantitative way. In the pre-sent study, aimed to analyze the sensitivity of system parameters tothe performance of the ORC systems quantitatively, the orthogonaldesign method is adopted, the sensitivity of three system param-eters to the six indices of BORC and RORC systems are evaluated.The optimal and worst level constitution of factors for the sixindices are concluded in Table 5. The orders of the three factors'

rs corresponding to the six indices.

Table 6The order of the three factors' sensitivity to the six indices.

Indices BORC RORC

I1 A> Cz B A> C > BI2 A> Cz B A> C > BI3 A> C> B A> B > CI4 C> B> A C> A> BI5 A> Cz B A> C > BI6 C> A> B C> A> B

H. Xi et al. / Energy 172 (2019) 435e442442

sensitivity to the six indices are listed in Table 6. For the threefactors we considered in thework, factor A is the dominant factor ofI1 (ƞth), I2 (BWR), I3 (Wexp_shaft) and I5 (Wnet), while factor C is thedominant factor of I4 (Wpump_ele) and I6 (qm). Comprehensively,factor A is the most significant factors for the system performances,followed by factor C. Factor B have a minimal impact on the systemperformances, relatively.

6. Outlook

ORC is an effective way to recover low-grade heat from differentindustrial processes or renewable energy resources. The heatsources for the ORC systems, in most cases, is unstable. In mostcases, the systemworks in variable-operating condition. Therefore,how the operation parameters influence the system performances,to summarize the law in a qualitative way is significant meaningful,especially for system design and development of control strategies.Adopting the orthogonal design method is an attempt to get thequalitative law, but it is not the unique way, other options includethe response surface method may also be applicable in the futurework. On the other hand, as can be seen, the system efficiency isquite low in this study. The pump was working with very low ef-ficiency and high BWR value, which is the main reason for the lowefficiency of the whole system. A 10 kW ORC system is being builtwith the pump redesigned. More factors will be take into consid-eration in the following experimental work with the new-builtsystem.

Acknowledgements

This work was supported by the National Key R&D Program ofChina (No. 2016YFB0601204), the National Natural Science Foun-dation of China (No. 51706176) and the the Qinghai ProvincialNatural Science Foundation of China (No. 2018-ZJ-927Q).

Nomenclature

I the mean value of the index of factorK experimental index valuePT plunger travel of working fluid pumpq mass flow rate (kg/s)R ranger valueT temperature (oC)Q heat transfer flow rate (kW)W power (kW)

Greek symbolst torque (N,m)ƞ efficiency

Subscriptscon condenser

eva evaporatorele electricityexp expanderi j level of the factors factorin inletj level of the factorsout outletpump pumpshaft shaft power outputcw cooling water

References

[1] Yang F, Zhang H, Yu Z, Wang E, Meng F, Liu H, Wang J. Parametric optimizationand heat transfer analysis of a dual loop ORC (organic Rankine cycle) systemfor CNG engine waste heat recovery. Energy 2017;118:753e75.

[2] Xi H, Li MJ, Xu C, He YL. Parametric optimization of regenerative organicRankine cycle (ORC) for low grade waste heat recovery using genetic algo-rithm. Energy 2013;58:473e82.

[3] Song J, Li XS, Ren XD, Gu CW. Performance analysis and parametric optimi-zation of supercritical carbon dioxide (S-CO2) cycle with bottoming OrganicRankine Cycle (ORC). Energy 2018;143:406e16.

[4] Behzadi A, Gholamian E, Houshfar E, Habibollahzade A. Multi-objective opti-mization and exergoeconomic analysis of waste heat recovery from Tehran'swaste-to-energy plant integrated with an ORC unit. Energy 2018;160:1055e68.

[5] Xi H, Li MJ, He YL, Tao WQ. A graphical criterion for working fluid selectionand thermodynamic system comparison in waste heat recovery. Appl ThermEng 2015;89:772e82.

[6] Xi H, Li MJ, He YL, Zhang YW. Economical evaluation and optimization oforganic Rankine cycle with mixture working fluids using R245fa as flameretardant. Appl Therm Eng 2017;113:1056e70.

[7] Lee U, Mitsos A. Optimal multicomponent working fluid of organic Rankinecycle for exergy transfer from liquefied natural gas regasification. Energy2017;127:489e501.

[8] Abadi GB, Yun E, Kim KC. Experimental study of a 1 kw organic Rankine cyclewith a zeotropic mixture of R245fa/R134a. Energy 2015;93:2363e73.

[9] Shu G, Zhao M, Tian H, Huo Y, Zhu W. Experimental comparison of R123 andR245fa as working fluids for waste heat recovery from heavy-duty dieselengine. Energy 2016;115:756e69.

[10] Dickes R, Dumont O, Daccord R, Quoilin S, Lemort V. Modelling of organicRankine cycle power systems in off-design conditions: an experimentally-validated comparative study. Energy 2017;123:710e27.

[11] Desideri A, Gusev S, Van den Broek M, Lemort V, Quoilin S. Experimentalcomparison of organic fluids for low temperature ORC (organic Rankine cycle)systems for waste heat recovery applications. Energy 2016l;97:460e9.

[12] Eyerer S, Wieland C, Vandersickel A, Spliethoff H. Experimental study of anORC (Organic Rankine Cycle) and analysis of R1233zd-E as a drop-inreplacement for R245fa for low temperature heat utilization. Energy2016;103:660e71.

[13] Navarro-Esbrí J, Mol�es F, Peris B, Mota-Babiloni A, Kontomaris K. Experimentalstudy of an Organic Rankine Cycle with HFO-1336mzz-Z as a low globalwarming potential working fluid for micro-scale low temperature applica-tions. Energy 2017;133:79e89.

[14] Mol�es F, Navarro-Esbri J, Peris B, Mota-Babiloni A. Experimental evaluation ofHCFO-1233zd-E as HFC-245fa replacement in an Organic Rankine Cycle sys-tem for low temperature heat sources. Appl Therm Eng 2016;98:954e61.

[15] Galloni E, Fontana G, Staccone S. Design and experimental analysis of a miniORC (organic Rankine cycle) power plant based on R245fa working fluid.Energy 2015;90:768e75.

[16] Shao L, Ma X, Wei X, Hou Z, Meng X. Design and experimental study of asmall-sized organic Rankine cycle system under various cooling conditions.Energy 2017;130:236e45.

[17] Xi H, Zhang HH, He YL. Experimental study of organic Rankine cycle systemusing scroll expander and diaphragm pump under different condensingtemperatures. Heat Tran Res 2018;49:899e914.

[18] Xi H, He YL, Wang J, Huang Z. Transient response of waste heat recoverysystem for hydrogen production and other renewable energy utilization. Int JHydrogen Energy 2018. https://doi.org/10.1016/j.ijhydene.2018.08.062.

[19] Wang X, Liu X, Zhang C. Parametric optimization and range analysis ofOrganic Rankine Cycle for binary-cycle geothermal plant. Energy ConversManag 2014;80:256e65.

[20] Liu X, Wang X, Zhang C. Sensitivity analysis of system parameters on theperformance of the Organic Rankine Cycle system for binary-cycle geothermalpower plants. Appl Therm Eng 2014;71:175e83.

[21] Ren LQ. Optimum design and analysis of experiments. Beijing: Higher Edu-cation Press; 2003.