Thermodynamic Optimization of a Double-pressure Organic Rankine Cycle Driven by Geothermal Heat Source

Thermodynamic Optimization of a Double-pressure Organic Rankine Cycle Driven by Geothermal Heat Source

Available Available online online at at www.sciencedirect.com www.sciencedirect.com ScienceDirect Availableonline onlineatatwww.sciencedirect.com ww...

591KB Sizes 13 Downloads 144 Views

Available Available online online at at www.sciencedirect.com www.sciencedirect.com

ScienceDirect

Availableonline onlineatatwww.sciencedirect.com www.sciencedirect.com Available Energy Energy Procedia Procedia 00 00 (2017) (2017) 000–000 000–000

ScienceDirect ScienceDirect

www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia

Energy (2017) 000–000 591–598 EnergyProcedia Procedia129 00 (2017) www.elsevier.com/locate/procedia

IV International Seminar on ORC Power Systems, ORC2017 13-15 September 2017, Milano, Italy The 15th International Symposium Heating and Cooling Thermodynamic Optimization ofona District Double-pressure Organic Rankinethe Cycle Drivenofbyusing Geothermal Source Assessing feasibility the heatHeat demand-outdoor

** Qingxuan Sun, Yaxiong Wang,for Ziyang Cheng, Jiangfeng Wangheat , Pan Zhao and Yiping Dai temperature function a long-term district demand forecast Institute of School Institute of of Turbomachinery, Turbomachinery, State Key Key Laboratory Laboratory of Multiphase Multiphase Flow in in Power Power Engineering, Engineering, School of of Energy Energy and Power Power Engineering, Engineering, a,b,c State a a Flow b c and c Xi’an Jiaotong Jiaotong University, University, Xi’an Xi’an 710049, 710049, People’s People’s Republic Republic of of China China Xi’an

I. Andrić

*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Corre

a

IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Abstract Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract

Geothermal Geothermal energy, energy, as as aa typical typical low-temperature low-temperature heat heat source, source, has has been been exploited exploited for for decades decades to to generate generate electricity. electricity. Organic Organic Rankine Rankine cycle cycle (ORC) (ORC) system system has has aa high high energy energy conversion conversion efficiency efficiency due due to to the the good good performance performance of of organic organic fluids fluids under under the the Abstract water geothermal geothermal water temperature. temperature. In In this this study, study, aa double-pressure double-pressure organic organic Rankine Rankine cycle cycle system system driven driven by by geothermal geothermal heat heat source source is is used used to to generate generate electricity. electricity. The The double-pressure double-pressure ORC ORC system system achieves achieves the the cascaded cascaded utilization utilization of of energy, energy, which which can can improve improve the the District heating networks are commonly addressed literature based as one on of thermodynamic the most effective solutions decreasing the efficiency of conversion. Mathematical model established laws, and system efficiency of energy energy conversion. Mathematical modelinis isthe established based on thermodynamic laws, and the theforoverall overall system greenhousehas gasbeen emissions fromA buildinganalysis sector. These systemsto investments which are returned through the heat performance evaluated. parametric is examine the of key parameters, performance has been evaluated. Athe parametric analysis is conducted conducted torequire examinehigh the effects effects of some some key thermodynamic thermodynamic parameters, sales. turbine Due to high-level the changed climate conditions building heat demand the future on could namely inlet pressure, turbine low-level inlet pressure, policies, turbine high-level high-level inlet intemperature, temperature, on the decrease, system namely turbine high-level inlet pressure, turbine and low-level inletrenovation pressure, turbine inlet the system prolonging the investment return period. performance. Parametric optimization is conducted by means of genetic algorithm (GA) to find the maximum system performance. performance. Parametric optimization is conducted by means of genetic algorithm (GA) to find the maximum system performance. thisperformances paper is to assess the feasibility of usingfluids the heat – outdoor function forhas heataa demand At the same time, the performances of three three organic working working fluids aredemand examined. Resultstemperature indicate that that R245fa has better AtThe themain samescope time,ofthe of organic are examined. Results indicate R245fa better forecast. The district Alvalade, in Lisbon used as a case study.5.8% The district is supply consisted of of 665 performance among the of three organiclocated fluids. The The exergy(Portugal), efficiency was of overall overall system exceeds under water performance among the three organic fluids. exergy efficiency of system exceeds 5.8% under the the supply water of buildings vary in boththan construction period and Three water weather scenarios (low, medium, high) 120℃, and it itthat produce more than 800kW electricity electricity withtypology. the geothermal geothermal water at the the mass flow flow rate of 250t/h. 250t/h. It is isand alsothree founddistrict that 120℃, and produce more 800kW with the at mass rate of It also found that renovation scenarioshas were developed (shallow, intermediate, To estimate the error, obtained heat demand values were the exergy efficiency efficiency has peak value under under the effect effect of turbine turbine deep). high-level inlet pressure pressure and turbine low-level inlet pressure. In the exergy peak value the of high-level inlet and turbine low-level inlet pressure. In compared with results from a dynamic heat demand model, and validated by the authors. addition, increasing turbine high-level inlet temperature bringspreviously positive developed effect to to the the system performance. Exergy analysis analysis is is also also addition, increasing turbine high-level inlet temperature brings aa positive effect system performance. Exergy The results thatshows whenthat onlythe weather changeloss is considered, the margin ofevaporator. error couldBy acceptable for somethe applications conducted andshowed the result result shows that the main exergy exergy loss occurs in in high-pressure high-pressure evaporator. Bybesystem system optimization, the doubleconducted and the main occurs optimization, double(the error in annual demand 20% for all weather geothermal scenarios considered). after introducing renovation pressure organic Rankine cycle has better performance in energy single-pressure system. pressure organic Rankine cyclewas has aalower betterthan performance in utilizing utilizing geothermal energy than than However, single-pressure system. error Published value increased up to Ltd. 59.5% (depending on the weather and renovation scenarios combination considered). © 2017 Authors. by ©scenarios, 2017 The The the Authors. Published by Elsevier Elsevier Ltd. ©The 2017 The under Authors. Published Elsevier Ltd.average value of slope coefficientby increased on within theIV range of 3.8% Seminar up to 8% decade, corresponds to the Peer-review responsibility of the scientific committee of the International onper ORC Power Systems. Peer-review under responsibility of the scientific committee of IV International Seminar ORC Powerthat Systems. Peer-review under responsibility of the scientific committee of the the International Seminar on on on ORC Systems. decrease in the number of heating hours of 22-139h during the IV heating season (depending thePower combination of weather and renovation scenariosOrganic considered). theDouble-pressure; other hand, function intercept increased for 7.8-12.7% per decade (depending on the Keywords: Geothermal; Organic RankineOn cycle; Double-pressure; Keywords: Geothermal; Rankine cycle; coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding +86 029-82668704. 029-82668704. *Cooling. Corresponding author. author. Tel.: Tel.: +86 +86 029-82668704; 029-82668704; fax: fax: +86 E-mail E-mail address: address: [email protected] [email protected]

Keywords: Heat demand; Forecast; Climate change 1876-6102 © 1876-6102 © 2017 2017 The The Authors. Authors. Published Published by by Elsevier Elsevier Ltd. Ltd. Peer-review Peer-review under under responsibility responsibility of of the the scientific scientific committee committee of of the the IV IV International International Seminar Seminar on on ORC ORC Power Power Systems. Systems.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of the IV International Seminar on ORC Power Systems. 10.1016/j.egypro.2017.09.214

Qingxuan Sun et al. / Energy Procedia 129 (2017) 591–598 Qingxuan Sun/ Energy Procedia 00 (2017) 000–000

592 2

Nomenclature E h I

m

Q s T W

exergy, kW enthalpy, kJ/kg exergy loss rate, kW mass flow rate, kg/s heat load, kW entropy, kJ/kg•K temperature, K power, kW

Subscripts a evap exg hp lp pump sys tur

ambient evaporator exergy high pressure low pressure pump system turbine

Greek letters



efficiency

1. Introduction In recent years, accelerated consumption of fossil fuels has caused a series of environment problems and remind human to use clean energy. Furthermore, along with the fast development of industry, energy shortage has influenced human’s normal life. So, renewable energy due to its widely distribution and sustainability such as geothermal heat source has attract more and more attentions [1]. Geothermal heat source varies in temperature from 50 to 350℃. It is abundant all over the world and has the property of steady temperature. Therefore, it has been widely used to generate power. Generally, the high temperature geothermal water (>220℃) are most suitable for generating electricity. The low and medium temperature geothermal water (<220℃) are more available [2] and can be taken more advantages. Organic Rankine cycle is employed as an efficient technology for using this low and medium temperature heat to generate electricity. There are several advantages in using ORC with geothermal heat source, including high efficiency than steam cycle, smaller systems and low investment [3]. Much research has been conducted on geothermal power generation based on organic Rankine cycle. Astolfi et al. [4,5] conducted the thermodynamic and techno-economic analysis of medium-low temperature geothermal sources organic Rankine cycle power plants. Zhai et al. [6] studied the influence of working fluid properties on system performance. Rodríguez et al. [7] compared the exergetic and economic performance between ORC and Kalina cycle for low temperature geothermal system. Zhang et al. [8] made the performance comparison between subcritical organic Rankine cycle and transcritical organic Rankine cycle for low-temperature geothermal system. Wang et al. [9] proposed a transcritical CO2 geothermal power generation system based on the cold energy utilization of liquid nature gas (LNG) and conducted the thermodynamic analysis. And many other research had been conducted in geothermal utilization field recently [10-15]. As mentioned above, the work basically focused on the single-pressure organic Rankine cycle, double-pressure organic Rankine cycle has not been discussed. The double-pressure organic Rankine cycle system can utilize energy more efficiently due to the principle of energy cascade utilization, so more research should be done in the field of double-pressure ORC system. In this paper, a double-pressure organic Rankine cycle driven by geothermal heat source is developed. Thermodynamic simulation and parametric analysis of the system are achieved based on a mathematical model, and a system performance optimization with exergy efficiency as the objective function is also conducted to obtain the best performance. The result shows that the double-pressure ORC system has a better performance than single-pressure system. R245fa has a better performance among several working fluids. 2. System description and mathematical model Based on the single-pressure ORC system shown in Fig.1 (a), a double-pressure organic Rankine cycle driven by geothermal heat source is developed as shown in Fig.1 (b). The double-pressure ORC system contains six components:



Qingxuan Sun et al. / Energy Procedia 129 (2017) 591–598 Qingxuan Sun/ Energy Procedia 00 (2017) 000–000

593 3

double-pressure turbine, high pressure evaporator, low pressure evaporator, recuperator, condenser and generator. Geothermal water is pumped from geothermal well and then sent to evaporators to heat organic fluid. The heated organic fluid vapor from high pressure evaporator and low pressure evaporator with different temperatures and pressure are sent to turbine to produce mechanical work. The turbine exhaust is delivered to recuperator to utilize the remaining heat energy for a better system performance and then sent to condenser to be condensed to liquid by cooling water. The condensed organic fluid is pumped and divided into two parts: one is sent to low pressure evaporator and the other is pumped to a higher pressure and then sent to high pressure evaporator. The analyses of double-pressure organic Rankine cycle driven by geothermal heat source are required to be conducted from exergy viewpoints. To simplify the theoretical model, some assumptions are made as follows:    

The system reaches a steady state. The pressure drops in vapor generators, recuperator, condenser and the connection tubes are neglected. The turbine and pumps respectively have a given isentropic efficiency. The stream at the condenser outlet is saturated liquid. Double-pressure Turbine

Turbine

G

G Low pressure evaporator

High pressure evaporator

Evaporator

Recuperator Pump 2

Condenser

Condenser

Geothermal well

Pump

Pump 1

(a) Single-pressure ORC system

(b) Double-pressure ORC system

Fig.1 Schematic diagrams of the single–pressure and double-pressure ORC system

In the double-pressure organic Rankine cycle system, working fluid absorbs heat from geothermal water in evaporators and is condensed by cold water in condenser. The T-s diagram of double-pressure organic Rankine cycle is shown in Fig.2. T

1h 7h

6h 6l

5

1l

7l

2 3

4 s Fig.2 T-s diagram of double-pressure ORC system

Qingxuan Sun et al. / Energy Procedia 129 (2017) 591–598 Qingxuan Sun/ Energy Procedia 00 (2017) 000–000

594 4

The energy absorbed by working fluid from geothermal water in evaporators is

Q  mhp (h1h  h6h ) hp-evap

(1)

Q mlp (h1l  h6l ) lp-evap

(2)

where subscript hp means high pressure, lp means low pressure. The power of ORC turbine is

Wtur  mhp (h1h  h2 )+mhp (h1l  h2 )

(3)

The works input by the pumps is

W  mORC (h4  h5 ) lp-pump

(4)

W mhp (h6h  h6l ) hp-pump

(5)

The net mechanical power of ORC subsystem is

Wnet  Wtur  Whp-pump  Wlp-pump

(6)

Exergy is the maximum theoretical work obtainable from an overall system consisting of the system and the environment as the system comes into equilibrium with the environment [16]. Exergy analysis is usually conducted to analyze the system losses and evaluate the system performance. In the present study, the exergy analysis only considers the physical exergy ignoring the other forms of exergy such as chemical exergy. The physical exergy at a state point i can be defined as

Ei mi  hi  ha   Ta ( si  sa ) 

(7)

The exergy balance of a component can be expressed as:

E

input

 Eoutput  I

(8)

The total exergy loss of an overall system is

I sys   I

(9)

The exergy efficiency, also called second-law efficiency, is an important indicator for system performance evaluation, which can be expressed as

exg 

Wnet  Einput

(10)

3. Result and discussion The simulation of the system was carried out using a simulation program written by authors with Matlab. Thermodynamic properties of the working fluid were calculated by REFPROP 9.0 [17]. 3.1. Parameters sensitivity analysis A constant temperature of 293 K with the atmospheric pressure of 0.1MPa is set as the reference state for energy and exergy calculation. The temperature of geothermal water is 393K and the mass flow rater of geothermal water is 250t/h. The main parameters of the simulation are listed in Table.1.



Qingxuan Sun et al. / Energy Procedia 129 (2017) 591–598 Qingxuan Sun/ Energy Procedia 00 (2017) 000–000

595 5

Table 1 Conditions of the simulation. Term

Value

Ambient temperature, K

293

Ambient pressure, kPa

101

Geothermal water temperature, K

393

Condense water temperature, K

298

Pinch point temperature difference, K

5

Condenser terminal temperature difference, K

7

Turbine isentropic efficiency, %

75

Pump isentropic efficiency, %

65

Mass flow rate of geothermal water, t/h

250

Turbine high-level inlet pressure, kPa

1800

Turbine low-level inlet pressure, kPa

900

Turbine inlet temperature, K

380

6

7

5

6 Exergy efficiency(%)

Exergy Efficiency(%)

Based on these conditions above, the system is modelled and several key parameters, namely, turbine high-level inlet pressure, turbine low-level inlet pressure and turbine high-level inlet temperature, are examined to evaluate their effects on the system performance from the perspectives of thermodynamics. One of the parameters is varied while the other two parameters keep constant and the value of each parameters is based on Table 1. At the same time, the performances of several organic working fluids have been evaluated. Considering the fluids thermodynamic properties and environment-friendly properties, the choices of fluids are R21, R114 and R245fa.

4

3 R21 R114 R245fa

2

1

5

4 R21 R114 R245fa

3

2

1000 1200 1400 1600 1800 2000 2200 2400 2600

700

800

Turbine high-level inlet pressure(kPa)

900

(a) Turbine high-level inlet pressure

5.0 Exergy Efficiency(%)

1100

1200

1300

(b) Turbine low-level inlet pressure

5.5

4.5

4.0

3.5 378

1000

Turbine low-level inlet pressure (kPa)

R21 R114 R245fa

380

382

384

386

388

390

Turbine high-level inlet temperature (K)

(c) Turbine high-level inlet temperature Fig.3 Effects of each parameter on system performance

1400

Qingxuan Sun et al. / Energy Procedia 129 (2017) 591–598 Qingxuan Sun/ Energy Procedia 00 (2017) 000–000

596 6

The influence of turbine high-level inlet pressure on system performance is shown in Fig.3 (a). It can be seen that the exergy efficiency increases at first and then declines with the increasing turbine high-level inlet pressure. An increase in turbine high-level inlet pressure leads to an increase in enthalpy difference across turbine, which causes an increase in turbine power and exergy efficiency. But when turbine high-level inlet pressure rise, the enthalpy difference decreases due to the working fluids properties. When the turbine inlet pressure is too high, the decreased enthalpy difference across turbine brings a negative effect to system performance. It can be found in Fig.3 (a) that the efficiency reaches the peak when turbine high-level inlet pressure reaches approximately 1800kPa. In a word, there exists an optimal turbine high-level inlet pressure to achieve the best performance. Fig.3 (b) illustrates the effect of turbine low-level inlet pressure on system performance. The change of turbine lowlevel inlet pressure has a significant effect on system performance. Exergy efficiency increases because of the decrease of heat transfer loss of the system with the increase of turbine low-level inlet pressure. However, when the turbine low-level inlet pressure is too high, the increase of turbine low-level inlet pressure brings a negative effect on system performance, because higher turbine low-level inlet pressure leads to lower mass flow rates of working fluid. Besides, if the turbine low-level inlet pressure is too high, the heat transfer loss increases due to a higher temperature. Therefore, the exergy efficiency decreases with the increase of turbine low-level inlet pressure. In conclusion, turbine low-level inlet pressure has a peak for system performance, for R245fa in this case it is approximate 900kPa. The effect of turbine high-level inlet temperature is shown in Fig.3 (c). It is evident that the increase of turbine high-level inlet temperature brings a positive effect on system performance. The increase of turbine inlet temperature leads to the increase of energy gained from evaporators, so the system exergy efficiency increase. 3.2. Optimization result based on thermodynamics According to previous analysis of the effects of these key parameters on the performance of the system, it can be found that the key parameters have different effects on the system under different conditions. Since the performance of the double-pressure ORC system is not governed by one parameter but the combination of the several key parameters, it is essential to find the optimized group of parameters to achieve the best performance of the system. The parameter optimization of the double-pressure ORC system is conducted with the genetic algorithm (GA) [18] method to obtain the optimum combination of the key parameters. GA is an evolutionary algorithm inspired by evolutionary biology that uses some techniques such as selection, crossover and mutation to search for the best solution. GA, as a powerful and broadly applicable stochastic search and optimization technique, is perhaps the most widely known types of evolutionary computation method today [19]. The control parameters of GA are listed in Table 2. The conditions of the parameter optimization are listed in Table 3. Exergy efficiency is chosen as the objective function to conduct the system performance optimization. The optimization results are shown in Table 4. And as a comparison, the optimization results of single-pressure system are also listed in Table 4. Table 2 Control parameters of GA Control parameters

Value

Population size

90

Maximum generations

200

Crossover probability

0.8

Mutation probability

0.05

Selection process

Tournament

Table 3 Condition of the parameter optimization of the double-pressure ORC system. Term

Lower limit

Upper limit

Turbine high-level inlet pressure, kPa

1300

2500

Turbine low-level inlet pressure, kPa

500

1200

Turbine inlet temperature, K

375

388



Qingxuan Sun et al. / Energy Procedia 129 (2017) 591–598 Qingxuan Sun/ Energy Procedia 00 (2017) 000–000

597 7

The optimization results show that, the exergy efficiencies of double-pressure ORC system are higher than the exergy efficiencies of single-pressure system, the turbine power outputs of double-pressure ORC system are also higher than the outputs of single-pressure system. It is obviously that the double-pressure ORC system has a better performance than single-pressure system based on the three working fluids. When using R245fa as working fluid, the system can have a highest performance with exergy efficiency of 5.85% and turbine power output of 818.6kW. In addition, the single-pressure system has similar parameters but with a less exergy efficiency of 5.28%. Based on the results above, exergy analysis could be conducted to obtain the exergy losses in each component. Due to the best performance among the three fluids, the exergy analysis is conducted based on the working fluid of R245fa. The main exergy losses distribution is shown in Fig.4. Table 4 Optimization results of the double-pressure system. R21

Term

R114

R245fa

D-P

S-P

D-P

S-P

D-P

S-P

Turbine power output, kW

685.3

634.5

749.4

692.18

818.6

735.1

Exergy efficiency,%

4.96

4.62

5.37

4.98

5.85

5.28

Turbine high-level inlet pressure, kPa

1785.7

/

1813.1

/

1841.7

/

Turbine low-level inlet pressure, kPa

1012.4

/

1086.9

/

908.5

/

Turbine high-level inlet temperature, K

386.8

/

387.1

/

386.6

/

Turbine inlet pressure, kPa

/

1774.2

/

1821.6

/

1862.4

Turbine inlet temperature, K

/

387.1

/

386.8

/

387.0

* The “D-P” means double-pressure system optimization results and “S-P” means single-pressure system optimization results.

As illustrated in Fig.4, due to the high temperature difference between geothermal water and working fluid, the high pressure evaporator contributes to the largest part of exergy loss. The second largest exergy loss occurred among equipment is in turbine, and the exergy loss in condenser is also significant. It can be indicated that the major exergy loss in ORC generally occurs in the heat exchangers, which may be caused by the temperature difference during the heat exchange process. The exergy losses of heat exchangers are determined by the heat transfer temperature difference. The exergy losses of turbine and pump are relevant to the isentropic efficiencies. So, some measures could be taken on the heat exchangers reduce the exergy losses, such as employing the optimization design method.

Low pressure pump Exhausted water High pressure pump Recuperator Low pressure evaporator Condenser Turbine High pressure evaporator

0

10

20

30 Percentage(%)

Fig.4 Exergy loss distribution in system

40

50

598 8

Qingxuan Sun et al. / Energy Procedia 129 (2017) 591–598 Qingxuan Sun/ Energy Procedia 00 (2017) 000–000

4. Conclusion A double-pressure organic Rankine cycle system driven by geothermal heat source is investigated based on the thermodynamic analysis in this work. The influences of some key parameters on the system performance are examined, the optimal values of these parameters are obtained via GA optimization, and the exergy analysis is conducted. The main conclusions drawn from the study are listed as follows: In the double-pressure ORC system, the turbine high-level and low-level inlet pressure have optimal values to reach the best system performance. The increase of turbine high-level inlet temperature brings a positive influence on the system performance. Through parametric optimization, the system can reach the exergy efficiency of 5.85% under the given conditions. The double-pressure ORC system has a better performance than single-pressure ORC system. The exergy analysis based on the optimal parameters shows that the main exergy loss of overall system mainly exists in evaporator, following with the turbine and condenser. Thermodynamic analysis and optimization of ORC provides theoretical foundation and feasibility for system construction. In the coming research, off-design performance evaluation and dynamic response of ORC system will be discussed under the condition of variable capacity of geothermal water. Acknowledgements The authors gratefully acknowledge the financial support by the Youth Star of Science and Technology of Shaanxi (Grant No. 2015KJXX-03) and K. C. Wong Education Foundation. References [1] Barbier E. Nature and technology of geothermal energy: a review. Renewable Sustainable Energy Rev 1997;1(1–2):1–69. [2] Hettiarachchi HDM, Golubovic M, Worek WM, et al. Optimum design criteria for an Organic Rankine Cycle using low- and mediumtemperature geothermal heat sources. Energy 2007; 32:1698–706. [3] Tamamoto T, Furuhata T, Arai N, Mori K. Design and testing of the organic Rankine cycle. Energy 2001; 26:239–51. [4] Astolfi M, Romano MC, Bombarda P, et al. Binary ORC (organic Rankine cycles) power plants for the exploitation of medium–low temperature geothermal sources–Part A: Thermodynamic optimization. Energy 2014; 66: 423-434. [5] Astolfi M, Romano MC, Bombarda P, et al. Binary ORC (Organic Rankine Cycles) power plants for the exploitation of medium–low temperature geothermal sources–Part B: Techno-economic optimization. Energy 2014; 66: 435-446. [6] Zhai H, Shi L, An Q. Influence of working fluid properties on system performance and screen evaluation indicators for geothermal ORC (organic Rankine cycle) system. Energy 2014; 74: 2-11. [7] Rodríguez CEC, Palacio JCE, Venturini OJ, et al. Exergetic and economic comparison of ORC and Kalina cycle for low temperature enhanced geothermal system in Brazil. Applied Thermal Engineering 2013; 52(1): 109-119. [8] Shengjun Z, Huaixin W, Tao G. Performance comparison and parametric optimization of subcritical Organic Rankine Cycle (ORC) and transcritical power cycle system for low-temperature geothermal power generation. Applied energy 2011; 88(8): 2740-2754. [9] Wang J, Wang J, Dai Y, et al. Thermodynamic analysis and optimization of a transcritical CO 2 geothermal power generation system based on the cold energy utilization of LNG. Applied Thermal Engineering 2014; 70(1): 531-540. [10] Anifantis A S, Colantoni A, Pascuzzi S. Thermal energy assessment of a small scale photovoltaic, hydrogen and geothermal stand-alone system for greenhouse heating. Renewable Energy 2017; 103: 115-127. [11] Arabkoohsar A, Farzaneh-Gord M, Ghezelbash R, et al. Energy consumption pattern modification in greenhouses by a hybrid solar–geothermal heating system. Journal of the Brazilian Society of Mechanical Sciences and Engineering 2017; 39(2): 631-643. [12] Pellizzone A, Allansdottir A, De Franco R, et al. Geothermal energy and the public: A case study on deliberative citizens’ engagement in central Italy. Energy Policy 2017; 101: 561-570. [13] Kong Y, Pang Z, Shao H, et al. Optimization of well-doublet placement in geothermal reservoirs using numerical simulation and economic analysis. Environmental Earth Sciences 2017; 76(3): 118. [14] Budisulistyo D, Wong C S, Krumdieck S. Lifetime design strategy for binary geothermal plants considering degradation of geothermal resource productivity. Energy Conversion and Management 2017; 132: 1-13. [15] Vasterling M, Wegler U, Becker J, et al. Real-time envelope cross-correlation detector: application to induced seismicity in the Insheim and Landau deep geothermal reservoirs. Journal of Seismology 2016; 1-16. [16] Incropera FP, De Witt DP. Fundamentals of heat and mass transfer. 1985. [17] NIST Standard Reference Database 23, NIST thermodynamic and transport properties of refrigerants and refrigerant mixtures REFPROP, Version 9.1, 2013. [18] Holland JH. Adaptation in nature and artificial systems. 1992. [19] Gen M, Cheng R. Genetic algorithms and engineering optimization. John Wiley & Sons; 2000.