Optimization of concentrating solar thermal power plant based on parabolic trough collector

Accepted Manuscript Optimization of concentrating solar thermal power plant based on parabolic trough collector Nishith B. Desai, Santanu Bandyopadhyay PII:

S0959-6526(14)01170-6

DOI:

10.1016/j.jclepro.2014.10.097

Reference:

JCLP 4887

To appear in:

Journal of Cleaner Production

Received Date: 21 May 2014 Revised Date:

31 October 2014

Accepted Date: 31 October 2014

Please cite this article as: Desai NB, Bandyopadhyay S, Optimization of concentrating solar thermal power plant based on parabolic trough collector, Journal of Cleaner Production (2014), doi: 10.1016/ j.jclepro.2014.10.097. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Total word count: 7118

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Nishith B. Desai

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Optimization of concentrating solar thermal power plant based on parabolic trough collector

and

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Santanu Bandyopadhyay*

Department of Energy Science and Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India

_________________________________________________________ * Corresponding author. Tel.: +91 22 25767894; Fax: +91 22 25726875. E-mail address: [email protected] (S. Bandyopadhyay).

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Abstract

Concentrating solar power (CSP) plant with parabolic trough collector (PTC) using synthetic or organic oil based heat transfer fluid is the most established and commercially attractive

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technology. In this paper, extensive energy and economic analysis of PTC based CSP plants, without storage, are reported. Effects of turbine inlet pressure, turbine inlet temperature, design radiation, plant size, and various modifications of Rankine cycle on overall efficiency as well as levelized cost of energy are studied. Furthermore, the variation in optimal turbine inlet pressure

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with turbine inlet temperature, design radiation, plant size, and various modifications of Rankine cycle are also analyzed. Energy and cost optimal turbine inlet pressures for 1 MWe plant (with

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basic Rankine cycle) are about 4.5-7.5 MPa and 3.5-7.5 MPa, respectively. The optimum pressure is observed to be a weak function of design solar radiation. The overall efficiency increases and levelized cost of energy decreases with increase in turbine inlet temperature, plant size and various modifications of the Rankine cycle.

Keywords: Concentrating solar power; Parabolic trough collector; Optimization; Cost of Energy;

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turbine inlet pressure; Efficiency.

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Nomenclature aperture area of the collector (m2)

C

Cost ($)

d

discount rate

E

annual electricity generation (kWh/y)

h

specific enthalpy (J/kg)

I

aperture effective direct normal irradiance (W/m2)

m

mass flow rate (kg/s)

n

life time (y)

P

power (W)

Pr

pressure (MPa)

Q

heat flowrate (W)

T

temperature (°C)

Ul

heat loss coefficient based on aperture area (W/(m2·K))

x

dryness fraction

difference

η

efficiency

θ

incidence angle (°)

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∆

Abbreviations

CSP

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Greek symbols

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Ap

concentrating solar power

DNI

direct normal irradiance

DSG

direct steam generation

HTF

heat transfer fluid

LCOE levelized cost of energy 3

LFR

linear Fresnel reflector

LPT

low pressure turbine

PTC

parabolic trough collector

SPT

solar power tower

TAC

total annualized cost

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AR

annual replacement

CL

collector

D

design

HTF

heat transfer fluid

hx

heat exchanger

in

inlet

is

isentropic

m

mean

max

maximum

min

minimum

o

optical

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ambient

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a

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Subscripts

optimum

out

outlet

th u

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opt

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O&M operation and maintenance

thermodynamic useful

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1. Introduction Concentrating solar power (CSP) is one of the viable options among renewable energy technologies (Krishna Priya and Bandyopadhyay, 2013). There are mainly four commercially

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available CSP technologies: parabolic trough collector (PTC), linear Fresnel reflector (LFR), solar power tower (SPT) and paraboloid dish. Among these technologies, PTC with synthetic or organic oil based heat transfer fluid (HTF), is the most established and commercially attractive technology (Purohit et al., 2013). In such a plant, the temperature limit is about 400°C with a

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resulting steam temperature, at turbine inlet, of about 370°C (Al-Soud and Hrayshat, 2009). However, if molten salt is used as a working fluid then the steam temperature up to 540°C is achievable, which may lead to higher steam turbine efficiency (Zaversky et al., 2013). Direct

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steam generation (DSG) in the PTC field is also an economically viable option (Zarza et al., 2002).

The second most installed CSP technology after PTC is SPT (Zhang et al., 2013). SPT plant uses DSG (Müller-Steinhagen and Trieb, 2004) or molten salt as HTF (Cáceres et al., 2013). Franchini et al. (2013) have presented the comparative analysis of CSP plants with PTC and SPT

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technologies. A detailed review on heliostat layout design (Collado and Guallar, 2013), central receiver design (Behar et al., 2013), and SPT technology based CSP plants (Ho and Iverson, 2014) have been reported in literature. LFR field with DSG has been proposed as a cheaper alternative because of flat mirrors and structural advantages (Nixon et al., 2013). However, it has

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a lower optical efficiency compared to PTC field (Zhu et al., 2013). Giostri et al. (2012a) and Morin et al. (2012) have presented the comparative analysis of CSP plants with PTC and LFR technologies. A paraboloid dish system is the least applied CSP technology for power generation

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(Sharma, 2011).

Heat storage is an important option to improve the stability and reliability for a CSP plant. Analysis of CSP plant using molten salt (Manenti and Ravaghi-Ardebili, 2013), molten salt and quartzite rock (Flueckiger et al., 2014), and phase change materials (Roget et al., 2013) based storage have been reported in literature. A detailed review on thermal energy storage technologies for CSP plants have been presented by Kuravi et al. (2013) as well as Tian and Zhao (2013). Dynamic simulation model with thermal energy storage has also been developed by Llorente García et al. (2011).

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Selection of type and size of solar field, power cycle parameters, and sizing of power block are the most important aspects in designing a CSP plant. Several studies on optimization of different parameters for PTC based CSP plant are reported. Economic optimization of design radiation, the direct normal irradiance (DNI) at which plant produces the rated power output, has

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been presented by Montes et al. (2009). Effects of design radiation on capacity factor and dumped energy, for a PTC based CSP plant without hybridization and thermal storage, have been demonstrated by Sundaray and Kandpal (2013). Recently, Desai et al. (2014) reported a methodology to determine the optimum design radiation for CSP plant without hybridization and

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thermal storage.

García-Barberena et al. (2012) have evaluated different operational strategies using

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SimulCET computer program. Reddy and Kumar (2012) have presented modeling of PTC field as well as feasibility study of stand-alone PTC based CSP plant with HTF and DSG for various places in India. Kumar and Reddy (2012) have carried out energy, exergy, environmental, and economic analyses of stand-alone DSG based CSP plant of different sizes. Giostri et al. (2012b) have compared the PTC based CSP plants using conventional HTF, molten salt, DSG, DSGHTF, and DSG-molten salt as working fluid and reported annual overall efficiency of 15.3%,

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16.2%, 17.9%, 16%, and 17.8%, respectively. Probabilistic modelling of PTC based CSP plant has also been reported by Zaversky et al. (2012). Conventional steam Rankine cycle is the most widely used power generating cycle in CSP plants. Many researcher have evaluated the performance of steam Rankine cycle in PTC based

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CSP plants (e.g., Manzolini et al., 2011; Desai et al., 2013). Fernández-García et al. (2010) have presented a survey of CSP plants with steam Rankine cycle for power generation. Kibaara et al.

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(2012) have analyzed the dry and wet cooled steam Rankine cycle based CSP plants and concluded that in case of a dry cooled plant, compared to a wet cooled plant, the capital cost and the levelized cost of energy (LCOE) are increased by 5% and 15%, respectively. Reddy et al. (2012) have reported increase in energetic and exergetic efficiencies by 1.49% and 1.51% with increase in turbine inlet pressure from 90 bar to 105 bar, respectively. It may be noted that, the dryness fraction of steam at the outlet of low pressure turbine (LPT) decreases with increase in turbine inlet pressure. Subsequently, the isentropic efficiency of the LPT also decreases. However, the isentropic efficiency of turbine has been kept constant during the analysis (Reddy et al., 2012). Al-Sulaiman (2013) has presented energy analysis of a typical 50 MWe PTC based 6

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CSP plant using a steam Rankine cycle as well as with steam Rankine cycle as a topping cycle and an organic Rankine cycle as a bottoming cycle. The effects of different design parameters on the size of solar field have been studied. In this paper, extensive energy and economic analysis of a PTC based CSP plant, without

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storage, is carried out. Effects of turbine inlet pressure, turbine inlet temperature, design radiation, plant size, and various modifications of Rankine cycle on overall efficiency as well as LCOE are studied. Variations in turbine isentropic efficiency with turbine inlet pressure, temperature and mass flow rate as well as dryness fraction at the outlet of turbine are modelled

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appropriately in this paper. There is no such analysis reported in the literature. The analysis is

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useful for sizing of solar field, sizing of power block and deciding power cycle parameters.

2. Effect of turbine inlet pressure on overall efficiency and levelized cost of energy

Simplified schematic of a PTC based CSP plant is shown in Fig. 1. PTC field heats HTF to a high temperature using concentrated solar radiation (from state 1 to state 2) and then high

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temperature HTF is fed into a heat exchanger to produce steam (from state 4 to state 5). The cold HTF coming out of heat exchanger (state 3) is re-circulated back into the PTC field using HTF pump. The high temperature and high pressure steam is used to generate power through a conventional steam turbine (from state 5 to state 6). Finally, steam from the turbine exhaust is

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condensed in a condenser (from state 6 to state 7). The collector field useful heat gain (Qu) and collector efficiency (ηCL) are given by, Qu = m HTF ⋅ ( h2 − h1 ) = η CL ⋅ I ⋅ A p

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(1)

 Tm − Ta    I 

ηCL = ηo − U l ⋅ 

(2)

where ηo is optical efficiency of collector field, Ul is heat loss co-efficient based on aperture area of collector field (W/(m2·K)), Tm is mean temperature of collector field (°C), Ta is ambient temperature (°C), I is the DNI corrected by cosine of incidence angle (i.e., DNI · cos θ) which is also known as aperture effective DNI (Feldhoff et al., 2012), mHTF is mass flow rate of HTF (kg/s), Ap is aperture area of collector field (m2), hi and Ti are specific enthalpy and temperature at i-th state point. 7

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Denoting the difference between Tm and Ta as ∆T,

 ∆T   ∆T  η η U = − ⋅ and   CL , D o l   I   ID 

ηCL = ηo − Ul ⋅ 

(3)

Neglecting heat losses through pipes and power input to pumps,

Qu = m HTF ⋅ ( h2 − h1 ) = m ⋅ ( h5 − h7 )

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where ηCL,D and ID are collector efficiency and aperture effective DNI at design condition.

(4)

where m is mass flow rate of steam (kg/s). From equation (1) and equation (4),

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m ⋅ ( h5 − h7 ) = η CL ⋅ I ⋅ A p

(5)

U ⋅ ∆T  m ⋅ ∆h =  η o − l I 

  ⋅ I ⋅ Ap 

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Substituting the collector efficiency from equation (3) in equation (5),

(ηo ⋅ I D − U l ⋅ ∆T ) m (ηo ⋅ I − U l ⋅ ∆T ) m = and D = Ap Ap ∆h ∆h

(6)

(7)

where mD is steam mass flow rate at design condition, ∆h is the difference between h5 and h7 (see

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Fig. 1).

The aperture specific design power output can be calculated from the relation given below,

PD mD = ⋅ ∆his ⋅ηis , D Ap Ap

(8)

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where ∆his is the isentropic enthalpy change in the turbine and ηis,D is the isentropic efficiency of the turbine at design condition. From equation (7) and equation (8),

PD (ηo ⋅ I D − U l ⋅ ∆T ) ⋅ ∆his ⋅ηis , D = Ap ∆h

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(9)

and the aperture specific power output at any aperture effective DNI (I) can be given as,

P (η o ⋅ I − U l ⋅ ∆T ) ⋅ ∆his ⋅ηis = ∆h Ap

(10)

The turbine isentropic efficiency can be calculated using following correlation (Mavromatis and Kokossis, 1998),

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A   mD   6    ⋅ 1 −  ⋅ 1 −   5 ⋅ B   ∆his ⋅ mD   6 ⋅ m 

ηis = 

(11)

At design condition (m = mD), the turbine isentropic efficiency is given as follows: 1 



A

η is , D =   ⋅  1 −  ∆ his ⋅ m D  B 

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(12)

where A and B are the isentropic efficiency parameters, depend on turbine inlet pressure and turbine size.

A = a1 + a2 ⋅ Tsat ,in

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(13)

B = b1 + b2 ⋅ Tsat ,in

(14)

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where a1, a2, b1, b2 are turbine regression coefficients, and Tsat,in is turbine inlet saturation pressure. Values of these coefficients are reported by Mavromatis and Kokossis (1998) for back pressure turbines and by Shang (2000) for condensing turbines.

The net power output is calculated by subtracting power input to pumps from turbine output. Therefore, the aperture specific net power output at design condition can be calculated as,

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Pnet , D PD − PHTF − PFeedWater = Ap Ap

(15)

The overall efficiency (solar to electric energy efficiency) at design condition is given as follows:

Pnet , D I D ⋅ Ap

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ηoverall , D =

(16)

The annualized cost (CAnnual) and levelized cost of energy (LCOE) can be calculated as,

d ⋅ (1 + d )n (1+ d )n −1

(

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CAnnual ($/y) = CCapital ⋅

LCOE ($/kWh) =

(∑ C

Annual

) +C

)

O&M

(17)

+ C AR

(18)

E Annual

where d is discount rate, n is lifetime (y), CO&M is annual operation and maintenance cost ($/y), CAR is annual component replacement cost ($/y), and EAnnual is annual electricity generation (kWh/y).

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From equation (9) it may be noted that, the aperture specific design power output is directly proportional to the product of enthalpy difference ratio and isentropic efficiency of the turbine at design condition (i.e., (∆his/∆h)·ηis,D). Typical T-h diagrams for a PTC based CSP plant for two different turbine inlet pressures are shown in Fig. 2. It should be noted that the enthalpy

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difference ratio (i.e., ∆his/∆h) increases with increase in turbine inlet pressure. On the other hand, the dryness fraction at outlet of the turbine decreases with increase in turbine inlet pressure (see Fig. 2), resulting in lower turbine isentropic efficiency. Typical variation in the product of enthalpy difference ratio and isentropic efficiency of the turbine at design condition, as a

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function of turbine inlet pressure, is shown in Fig. 3. It may also be noted that, the power input to HTF pump and feed water pump increases with increase in turbine inlet pressure. Moreover, the

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heat exchanger outlet temperature increases with increase in turbine inlet pressure (see Fig. 2) and the collector outlet temperature is typically kept constant. This leads to increase in the mean collector temperature difference (∆T) and subsequently the collector field efficiency decreases. This justifies the existence of a thermodynamically optimal turbine inlet pressure, for which the net design power output is the maximum. Consequently, at that pressure the overall efficiency at design condition is also the maximum (equation16).

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For demonstration the simulations are carried out using Engineering Equation Solver (Klein, 2004). The data given in Table 1 are used for simulations and the results are shown in Fig. 4. It may be observed that the optimal turbine inlet pressure is about 7.5 MPa. It may also be noted from Fig. 4 that the nature of the net design power output curve is not very sharp near the

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maximum. The power output remains within 1% of the maximum, for the turbine inlet pressure range 4.5-11 MPa. The total annualized cost per unit aperture area of the collector increases with

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increase in pressure. This implies that the cost optimal turbine inlet pressure should be always lesser than the thermodynamically optimum. Therefore, the thermodynamically optimal turbine inlet pressure is about 4.5-7.5 MPa. It may also be noted that, the aperture specific net design power output increases with increase in turbine inlet temperature (Tmax). This is expected because higher turbine inlet temperature increases the Rankine cycle efficiency. However, its maximum value is limited by the maximum HTF temperature. The effect of turbine inlet pressure on LCOE is studied using the cost data given in Table 2 and Table 3. DNI data for the simulations are taken from Ramaswamy et al. (2013) and the results are shown in Fig. 5. Results show that the cost optimal turbine inlet pressure is about 6 10

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MPa which is lesser than the thermodynamically optimal value (7.5 MPa), as explained. It may be observed that for turbine inlet pressure within 3.5-10 MPa, the LCOE remains within 1% of the maximum value. However, the higher pressure is limited by the thermodynamically optimal

the cost optimal turbine inlet pressure is about 3.5-7.5 MPa.

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value. Therefore, based on the assumptions of equipment characteristic parameters and cost data,

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3. Effect of design radiation on overall efficiency and levelized cost of energy

The effect of design radiation on aperture specific net design power output as function of turbine

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inlet pressure is shown in Fig. 6, which demonstrates that the power output increases with increase in design radiation. This is expected because higher design radiation decreases the collector aperture area, for the fixed design power output requirement. However, very high design radiation results in low capacity factor of the plant and very low design radiation results in excessive unutilized energy (Desai et al. 2014). Therefore, there exists an optimal design DNI for a CSP plant which minimizes the LCOE. Fig. 7 demonstrates the effect of design radiation on

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LCOE as function of turbine inlet pressure. It may be noted that LCOE is the lowest for design radiation of 600 W/m2. It may also be observed that, there is no significant change in the thermodynamically as well as cost optimal turbine inlet pressure with variation in design

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radiation.

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4. CSP plant with regenerative Rankine cycle

Regenerative feed-water heating is commonly used for increasing the thermal efficiency of the steam Rankine cycle. Simplified schematic of a PTC based CSP plant using regenerative Rankine cycle is shown in Fig. 8. It should be noted that steam, at some intermediate pressure, is withdrawn from the turbine (state 9). This is mixed directly with feed water (at state 8) in a direct contact heater and the resultant mixture (at state 10) is fed to second feed water pump. The other state points are same as explained earlier.

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Variations of net design power output and LCOE as function of turbine inlet pressure, for basic and regenerative Rankine cycles, are shown in Fig. 9. This figure demonstrates that the cycle modification increases the net design power output and decreases the LCOE, as expected. In case of regenerative Rankine cycle, the thermodynamic and cost optimum range (for 1 MWe

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plant) is about 6.2-10 MPa and 4.5-10 MPa, respectively. It may also be noted that, the thermodynamically optimal as well as cost optimal turbine inlet pressure increases with regeneration. The increase in aperture specific net design power output is about 7.9% with single regeneration (at Prth,opt= 10 MPa) compared to CSP plant without regeneration (at Prth,opt = 7.5

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MPa). Moreover, the decrease in LCOE is about 3.9% with regeneration (at Prcost,opt= 8 MPa)

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compared to CSP plant without regeneration (at Prcost,opt = 6 MPa).

5. Effect of plant size on overall efficiency and levelized cost of energy

Isentropic efficiency of the turbine increases with the size of turbine. The effects of plant size and resulting higher isentropic efficiency of the turbine on aperture specific net design power

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output are shown in Fig. 10, which demonstrates that the power output increases with increase in plant size. It may also be noted that the optimal turbine inlet pressure increases with increase in plant size. Increase in turbine inlet pressure increases the overall thermal efficiency of the Rankine cycle, and simultaneously, increases the moisture content of steam, at the outlet of the

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turbine, to an unacceptable level (see Fig. 2). Typically, the minimum dryness fraction at the outlet of a turbine is kept around 80-90%. To satisfy the minimum dryness fraction at outlet of

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turbine, the steam at inlet of turbine should be superheated to high temperature. However, in a PTC based CSP plant with synthetic or organic oil based HTF, the temperature limit is about 400°C with a resulting steam temperature at the turbine inlet about 350-370°C. Therefore, the optimal turbine inlet pressure is limited by the minimum dryness fraction at outlet of turbine (a limit for 88% dryness fraction is shown in Fig 10). With the use of molten salt as HTF, the steam temperature (Tmax) up to 540°C is achievable. As a result, higher steam turbine efficiency, higher dryness fraction at the outlet of turbine, and lower LCOE can be achieved. Fig. 11 shows the variation of aperture specific net design power output as function of turbine inlet pressure, for PTC based CSP plant using molten salt as HTF. It 12

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may be observed that, the thermodynamically optimal turbine inlet pressure increases with the plant size and typical operating pressure (about 18 MPa) of a conventional steam power plant can be achieved. The effect of plant size on LCOE is shown in Fig. 12; LCOE decreases with increase in plant

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size. The cost optimal turbine inlet pressure also increases with plant size. Typically, in larger plants the steam is expanded in two stages, and reheating the steam in between these two stages of the turbine helps in achieving the minimum desirable dryness fraction at the outlet of the last

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stage of the turbine.

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5.1 CSP plant with reheat Rankine cycle

Concentrating solar power plant with reheat Rankine cycle can take the advantage of increased efficiency as well as it avoids the low-quality steam at turbine exhaust. Simplified schematic of a PTC based CSP plant using reheat Rankine cycle is shown in Fig. 13. It should be noted that steam is expanded up to some intermediate pressure in the first stage turbine (state 11). This is reheated in a reheater (from state 11 to state 12), using a small fraction of HTF (state 13) from

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outlet of the collector field. The reheated steam (at state 12) then expands in the second stage of turbine to the condenser pressure. The HTF coming out of the reheater (state 14) is mixed with the main line HTF and the resultant mixture (at state 15) is fed to HTF pump. The other state points are same as explained earlier.

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The effect of plant size and resulting higher isentropic efficiency of the turbine on aperture specific net design power output is shown in Fig 14. It may be noted that the thermodynamically

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optimal turbine inlet pressures for 5 MWe, 25 MWe and 50 MWe plants are 7.5-11.5 MPa, 913.5 MPa and 9-13.5 MPa, respectively. Fig. 15 illustrates the variation of LCOE as function of turbine inlet pressure, for different sizes of the plant. It may be noted that the cost optimal turbine inlet pressures for 5 MWe, 25 MWe and 50 MWe plants are 6-11.5 MPa, 7.5-13.5 MPa and 8-13.5 MPa, respectively.

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5.2 CSP plant with reheat-regenerative Rankine cycle

Reheating and regeneration are the most commonly used modifications in the basic steam Rankine cycle. Simplified schematic of a PTC based CSP plant using reheat-regenerative

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Rankine cycle is shown in Fig. 16. All the state points are same as explained earlier.

Fig. 17 demonstrates the variation of aperture specific net design power output as function of turbine inlet pressure, for different sizes of the plant. It may be noted that the thermodynamically optimal turbine inlet pressures for 5 MWe, 25 MWe and 50 MWe plants are 9-13 MPa, 10.5-15

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MPa and 10.5-15 MPa, respectively. Fig. 18 illustrates the variation of LCOE as function of turbine inlet pressure, for different sizes of the plant. The cost optimal turbine inlet pressures for

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5 MWe, 25 MWe and 50 MWe plants are 7-13 MPa, 9-15 MPa and 9.5-15 MPa, respectively. In case of a 50 MWe CSP plant with reheat-regenerative Rankine cycle, increase in aperture specific net design power output is about 7% and decrease in LCOE is about 5.3% compared to reheat Rankine cycle. Fig. 19 shows the comparison of LCOE as function of turbine inlet pressure, for three different places in India. It may be noted that the minimum LCOE of 11.3

6. Conclusions

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Rs./kWh (18.8 ¢/kWh) is estimated for Jodhpur, India.

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In this paper, effects of turbine inlet pressure, turbine inlet temperature, design radiation, plant size, and various modifications of Rankine cycle on overall efficiency as well as LCOE for the

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PTC based CSP plant, without hybridization and storage, are presented. Moreover, the variation in optimal turbine inlet pressure with turbine inlet temperature, design radiation, plant size, and various modifications of Rankine cycle are also determined. The important observations are summarized in Table 4. In case of a PTC based plant with basic Rankine cycle, thermodynamically and cost optimal turbine inlet pressures for 1 MWe plant are about 4.5-7.5 MPa and 3.5-7.5 MPa, respectively. The optimal turbine inlet pressure is a weak function of design radiation. However, the optimum value increases with plant size and various modifications of Rankine cycle. The optimal turbine inlet pressures for 5 MWe, 25 MWe and 50 MWe plants (with reheat14

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regenerative Rankine cycle) are 7-13 MPa, 9-15 MPa and 9.5-15 MPa, respectively. The aperture specific net design power output increases and LCOE decreases with increase in turbine inlet temperature, plant size, and various modifications of Rankine cycle. Additionally, there is a cost optimal design radiation that minimizes the cost of electricity generation.

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The estimated minimum LCOE is about Rs. 11.3 per kWh (18.8 ¢/kWh). This cost is higher compared to coal (Rs. 2.5 per kWh), nuclear (Rs. 3 per kWh) as well as natural gas (Rs. 5.5 per kWh) based thermal power plants in India (Nature, 2014). The LCOE for PTC based CSP plant may further decrease with higher plant size, multiple extractions from the steam turbine, thermal

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storage as well as clean development mechanism benefits. Moreover, the use of molten salt as

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HTF has the potential of decreasing the LCOE significantly.

Acknowledgments

Authors would like to thank the Ministry of New and Renewable Energy (MNRE), Government of India for the financial support given to the Development of a Megawatt-scale Solar Thermal

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doi:10.1016/j.solener.2013.05.021).

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List of Figure Captions

Fig. 1. Simplified schematic of a PTC based CSP plant.

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Fig. 2. Typical T-h diagrams for a PTC based CSP plant for two different values of turbine inlet pressure.

Fig. 3. Typical variation in the product of enthalpy difference ratio and isentropic efficiency of the turbine at design condition ((∆his/∆h)· ηis,D) as a function of turbine inlet pressure.

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Fig. 4. Aperture specific net design power output as function of turbine inlet pressure at different turbine inlet temperature.

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Fig. 5. Levelized cost of energy as function of turbine inlet pressure at different turbine inlet temperature.

Fig. 6. Aperture specific net design power output as function of turbine inlet pressure at different design DNI.

Fig. 7. Levelized cost of energy as function of turbine inlet pressure at different design DNI. Fig. 8. Simplified schematic of a PTC based CSP plant using regenerative Rankine cycle.

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Fig. 9. Aperture specific net design power output and LCOE as function of turbine inlet pressure for basic and regenerative Rankine cycles. Fig. 10. Aperture specific net design power output as function of turbine inlet pressure for different plant size.

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Fig. 11. Aperture specific net design power output as function of turbine inlet pressure for PTC based CSP plant using molten salt as HTF.

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Fig. 12. Levelized cost of energy as function of turbine inlet pressure for different plant size. Fig. 13. Simplified schematic of a PTC based CSP plant using reheat Rankine cycle. Fig. 14. Aperture specific net design power outputs as function of turbine inlet pressure for different plant size with reheat Rankine cycle.

Fig. 15. Levelized cost of energy as function of turbine inlet pressure for different plant size with reheat Rankine cycle. Fig. 16. Simplified schematic of a PTC based CSP plant using reheat-regenerative Rankine cycle.

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Fig. 17. Aperture specific net design power output as function of turbine inlet pressure for different plant size with reheat-regenerative Rankine cycle. Fig. 18. Levelized cost of energy as function of turbine inlet pressure for different plant size with reheat-regenerative Rankine cycle.

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Fig. 19. Levelized cost of energy as function of turbine inlet pressure for different places with

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reheat-regenerative Rankine cycle.

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5

Water/Steam Circuit (Rankine Cycle)

HTF Circuit 2

Power

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Turbine 2 PTC Field

6

3

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Heat Exchanger

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Condenser

Feed Water Pump

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Fig. 1. Simplified schematic of a PTC based CSP plant.

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Water/Steam Circuit (Rankine Cycle)

HTF Circuit 2

5 Power Turbine

6

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PTC Field

2

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Heat Exchanger

Condenser 3

4 7

1

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Feed Water Pump

Fig. 1. Simplified schematic of a PTC based CSP plant. (In print: black/white)

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400

2 2'

HTF Profile (for Pr'higher)

Prhigher TP

3

250

Pr'higher

T'P

3'

Constant Entropy

200 Rankine cycle 150 100 Prlower

6s'

6s

7 0 500

1000

∆h'is

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0

5'

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Temperature (°C)

300

5

HTF Profile (for Prhigher)

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350

1500

2000

∆his 2500

3000

3500

Enthalpy (kJ/kg)

Fig. 2. Typical T-h diagrams for a PTC based CSP plant for two different values of turbine inlet

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400

2 2'

HTF Profile (for Pr'higher)

Prhigher TP

3

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Pr'higher

T'P

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Constant Entropy

200 Rankine cycle 150 100 Prlower

6s'

6s

7 0 500

1000

∆h'is

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0

5'

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Temperature (°C)

300

5

HTF Profile (for Prhigher)

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350

1500

2000

∆his 2500

3000

3500

Enthalpy (kJ/kg)

Fig. 2. Typical T-h diagrams for a PTC based CSP plant for two different values of turbine inlet

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pressure.

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0.240

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0.230

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0.215 2

3

4

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Product of enthalpy difference ratio with isentropic efficiency of the turbine at design condition ((∆his /∆h)· ηis,D)

0.245

6

7

8

9

10

11

12

13

14

15

Turbine Inlet Pressure (MPa)

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Fig. 3. Typical variation in the product of enthalpy difference ratio and isentropic efficiency of the turbine at design condition ((∆his/∆h)·ηis,D) as a function of turbine inlet pressure.

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Tmax = 380°C Tmax = 370°C

ID = 600 W/m2 PD = 1 MWe 88

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87

86

Tmax = 350°C 85

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Tmax = 330°C

84

Optimum Range

83 3

4

5

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Aperture specific net design power output (W/m2)

89

6 7 8 Turbine Inlet Pressure (MPa)

9

10

11

Fig. 4. Aperture specific net design power output as function of turbine inlet pressure at different turbine inlet temperature.

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Tmax = 380°C Tmax = 370°C

ID = 600 W/m2 PD = 1 MWe 88

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87

86

Tmax = 350°C 85

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Tmax = 330°C

84

Optimum Range

83 3

4

5

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Aperture specific net design power output (W/m2)

89

6 7 8 Turbine Inlet Pressure (MPa)

9

10

11

Fig. 4. Aperture specific net design power output as function of turbine inlet pressure at different turbine inlet temperature.

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(In print: black/white)

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0.346 Place: Jodhpur (26.28°N, 73.02°E) PD = 1 MWe

Tmax = 350°C

0.342

Tmax = 330°C

0.340

0.336

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0.338

Tmax = 370°C

Tmax = 380°C

0.334 3

4

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0.344

5

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Levelized Cost of Energy ($/kWh)

Optimum Range

6

7

8

9

10

11

Turbine Inlet Pressure (MPa)

Fig. 5. Levelized cost of energy as function of turbine inlet pressure at different turbine inlet temperature.

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0.346 Place: Jodhpur (26.28°N, 73.02°E) PD = 1 MWe

Optimum Range

Tmax = 330°C

0.340

0.336

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0.338

Tmax = 370°C

Tmax = 380°C

0.334 3

4

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Tmax = 350°C

0.342

5

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Levelized Cost of Energy ($/kWh)

0.344

6

7

8

9

10

11

Turbine Inlet Pressure (MPa)

Fig. 5. Levelized cost of energy as function of turbine inlet pressure at different turbine inlet temperature.

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(In print: black/white)

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100

ID = 700 W/m2

Tmax = 350°C PD = 1 MWe

95

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ID = 600 W/m2 90 85 80

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ID = 500 W/m2

75 70 65 3

4

5

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Aperture specific net design power output (W/m2 )

105

6 7 8 Turbine Inlet Pressure (MPa)

Optimum Range

9

10

11

Fig. 6. Aperture specific net design power output as function of turbine inlet pressure at different design DNI.

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100

ID = 700 W/m2

Tmax = 350°C PD = 1 MWe

95

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ID = 600 W/m2 90 85 80

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ID = 500 W/m2

75 70 65 3

4

5

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Aperture specific net design power output (W/m2 )

105

6 7 8 Turbine Inlet Pressure (MPa)

Optimum Range

9

10

11

Fig. 6. Aperture specific net design power output as function of turbine inlet pressure at different design DNI.

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(In print: black/white)

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0.365 Place: Jodhpur (26.28°N, 73.02°E) Tmax = 350°C PD = 1 MWe

Optimum Range 0.360

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0.355

0.350

0.345

ID = 600 W/m2

0.340

0.335 3

4

5

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ID = 700 W/m2

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Levelized Cost of Energy ($/kWh)

ID = 500 W/m2

6 7 8 Turbine Inlet Pressure (MPa)

9

10

11

Fig. 7. Levelized cost of energy as function of turbine inlet pressure at different design DNI.

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0.365 Place: Jodhpur (26.28°N, 73.02°E) Tmax = 350°C PD = 1 MWe

Optimum Range 0.360

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0.355

0.350

0.345

ID = 600 W/m2

0.340

0.335 3

4

5

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ID = 700 W/m2

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Levelized Cost of Energy ($/kWh)

ID = 500 W/m2

6 7 8 Turbine Inlet Pressure (MPa)

9

10

11

Fig. 7. Levelized cost of energy as function of turbine inlet pressure at different design DNI.

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5

Water/Steam Circuit (Rankine Cycle)

HTF Circuit 2

Power Turbine

2 6

Heat Exchanger

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PTC Field

9

Condenser

3

4

7

10

8

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1

Feed Water Pump-I

Feed Water Direct Contact Pump-II Heater

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HTF Pump

Fig. 8. Simplified schematic of a PTC based CSP plant using regenerative Rankine cycle. (Web only: colour)

Water/Steam Circuit (Rankine Cycle)

HTF Circuit

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2

5 Power Turbine

PTC Field

2

9

6

EP

Heat Exchanger

3

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1

HTF Pump

Condenser 4 7 10 Feed Water Direct Contact Pump-II Heater

8 Feed Water Pump-I

Fig. 8. Simplified schematic of a PTC based CSP plant using regenerative Rankine cycle. (In print: black/white)

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0.345

96 94

0.340

0.335

92 Cost of Energy (Basic Cycle) 90

Pnet,D/Ap (Basic Cycle)

0.330

SC

88 86 84

Levelized Cost of Energy ($/kWh)

98

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Place: Jodhpur (26.28°N, 73.02°E) Optimum Range ID = 600 W/m2 PD = 1 MWe Tmax = 370°C Pnet,D/Ap (Cycle with Regeneration)

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Aperture specific net design power output (W/m2 )

100

0.325

Cost of Energy (Cycle with Regeneration) 82 3

4

5

6 7 8 Turbine Inlet Pressure (MPa)

9

0.320 10

11

Fig. 9. Aperture specific net design power output and LCOE as function of turbine inlet pressure

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for basic and regenerative Rankine cycles.

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0.345

96 94

0.340

0.335

92 Cost of Energy (Basic Cycle) 90

Pnet,D/Ap (Basic Cycle)

0.330

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88 86 84

Levelized Cost of Energy ($/kWh)

98

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Place: Jodhpur (26.28°N, 73.02°E) Optimum Range ID = 600 W/m2 PD = 1 MWe Tmax = 370°C Pnet,D/Ap (Cycle with Regeneration)

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Aperture specific net design power output (W/m2 )

100

0.325

Cost of Energy (Cycle with Regeneration) 82 3

4

5

6 7 8 Turbine Inlet Pressure (MPa)

9

0.320 10

11

Fig. 9. Aperture specific net design power output and LCOE as function of turbine inlet pressure

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for basic and regenerative Rankine cycles.

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ID = 600 W/m2 Tmax = 350°C

91 PD = 1.5 MWe

xout = 0.88

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90 89 88

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PD = 1.2 MWe

87 86 85

PD = 1 MWe

84 3

4

5

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Aperture specific net design power output (W/m2 )

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6 7 8 Turbine Inlet Pressure (MPa)

Optimum Range

9

10

11

different plant size.

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Fig. 10. Aperture specific net design power output as function of turbine inlet pressure for

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ID = 600 W/m2 Tmax = 350°C

91 PD = 1.5 MWe

xout = 0.88

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90 89 88

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PD = 1.2 MWe

87 86 85

PD = 1 MWe

84 3

4

5

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Aperture specific net design power output (W/m2)

92

6 7 8 Turbine Inlet Pressure (MPa)

Optimum Range

9

10

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different plant size.

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Fig. 10. Aperture specific net design power output as function of turbine inlet pressure for

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HTF: Molten Salt Tin,CL = 300°C Tout,CL = 570°C U l = 0.2 W/(m2 ·K) ID = 600 W/m2 Tmax = 540°C

102

PD = 10 MWe

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Prmax,Allowed = 18 MPa

100

96 PD = 5 MWe 94 92 90 5

6

7

8

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Aperture specific net design power output (W/m2 )

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9 10 11 12 13 14 Turbine Inlet Pressure (MPa)

Optimum Range

15

16

17

18

Fig. 11. Aperture specific net design power output as function of turbine inlet pressure for PTC

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based CSP plant using molten salt as HTF.

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HTF: Molten Salt Tin,CL = 300°C Tout,CL = 570°C U l = 0.2 W/(m2·K) ID = 600 W/m2 Tmax = 540°C

102

PD = 10 MWe

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104

Prmax,Allowed = 18 MPa

100

96 PD = 5 MWe 94 92 90 5

6

7

8

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98

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9 10 11 12 13 14 Turbine Inlet Pressure (MPa)

Optimum Range

15

16

17

18

Fig. 11. Aperture specific net design power output as function of turbine inlet pressure for PTC

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based CSP plant using molten salt as HTF.

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0.345

Place: Jodhpur (26.28°N, 73.02°E) ID = 600 W/m2 Tmax = 350°C

Optimum Range

0.335

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PD = 1 MWe

xout = 0.88

0.330

PD = 1.2 MWe

0.325

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Levelized Cost of Energy ($/kWh)

0.340

PD = 1.5 MWe

0.315 3

4

5

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Turbine Inlet Pressure (MPa)

Fig. 12. Levelized cost of energy as function of turbine inlet pressure for different plant size.

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0.345

Place: Jodhpur (26.28°N, 73.02°E) ID = 600 W/m2 Tmax = 350°C

Optimum Range

0.335

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PD = 1 MWe

xout = 0.88

0.330

PD = 1.2 MWe

0.325

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Levelized Cost of Energy ($/kWh)

0.340

PD = 1.5 MWe

0.315 3

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Turbine Inlet Pressure (MPa)

Fig. 12. Levelized cost of energy as function of turbine inlet pressure for different plant size.

HTF Circuit 2

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5 Water/Steam Circuit (Rankine Cycle)

Turbine

Power

PTC Field

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13

11 6

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12 Reheater Condenser

4 14 7

15

HTF Pump

Feed Water Pump

Fig. 13. Simplified schematic of a PTC based CSP plant using reheat Rankine cycle. (Web only: colour) 42

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5 Water/Steam Circuit (Rankine Cycle)

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13 11

Power

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Fig. 13. Simplified schematic of a PTC based CSP plant using reheat Rankine cycle.

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ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

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PD = 50 MWe

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PD = 25 MWe

110

PD = 5 MWe

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108 106 104 102 4

5

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8 9 10 11 Turbine Inlet Pressure (MPa)

Optimum Range

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Fig. 14. Aperture specific net design power outputs as function of turbine inlet pressure for different plant size with reheat Rankine cycle.

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ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

116

PD = 50 MWe

112

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PD = 25 MWe

110

PD = 5 MWe

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7

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118

8 9 10 11 Turbine Inlet Pressure (MPa)

Optimum Range

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13

14

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Fig. 14. Aperture specific net design power outputs as function of turbine inlet pressure for different plant size with reheat Rankine cycle.

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0.240 Place: Jodhpur (26.28°N, 73.02°E) ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

Optimum Range

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PD = 25 MWe

0.210

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Levelized Cost of Energy ($/kWh)

0.230

0.200

0.190 4

5

6

7

M AN U

PD = 50 MWe

8

9

10

11

12

13

14

Turbine Inlet Pressure (MPa)

Fig. 15. Levelized cost of energy as function of turbine inlet pressure for different plant size with

TE D

reheat Rankine cycle.

AC C

EP

(Web only: colour)

46

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0.240 Place: Jodhpur (26.28°N, 73.02°E) ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

Optimum Range

RI PT

PD = 5 MWe 0.220

PD = 25 MWe

0.210

SC

Levelized Cost of Energy ($/kWh)

0.230

0.200

0.190 4

5

6

7

M AN U

PD = 50 MWe

8

9

10

11

12

13

14

Turbine Inlet Pressure (MPa)

Fig. 15. Levelized cost of energy as function of turbine inlet pressure for different plant size with

TE D

reheat Rankine cycle.

AC C

EP

(In print: black/white)

47

ACCEPTED MANUSCRIPT

5 Water/Steam Circuit (Rankine Cycle)

HTF Circuit 2

Turbine Power

13 11 Heat Exchanger

RI PT

PTC Field

6

3

Condenser

4

SC

14 1

10

15 HTF Pump

9

12

Reheater

7

8

M AN U

Feed Water Pump

Fig. 16. Simplified schematic of a PTC based CSP plant using reheat-regenerative Rankine cycle.

(Web only: colour) 5 Water/Steam Circuit (Rankine Cycle)

HTF Circuit

TE D

2

Turbine Power

PTC Field

13

EP

Heat Exchanger

1

AC C

3

6 Reheater

9

12

Condenser

4

14

7 10

15

HTF Pump

11

8

Feed Water Pump

Fig. 16. Simplified schematic of a PTC based CSP plant using reheat-regenerative Rankine cycle. (In print: black/white)

48

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ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

124

PD = 50 MWe

122

RI PT

120 PD = 25 MWe 118 116

SC

114 112 PD = 5 MWe

110 108 106 4

5

6

7

M AN U

Aperture specific net design power output (W/m2 )

126

8

9

10

11

12

Optimum Range 13

14

15

Turbine Inlet Pressure (MPa)

Fig. 17. Aperture specific net design power output as function of turbine inlet pressure for

TE D

different plant size with reheat-regenerative Rankine cycle.

AC C

EP

(Web only: colour)

49

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ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

124

PD = 50 MWe

122

RI PT

120 PD = 25 MWe 118 116

SC

114 112 PD = 5 MWe

110 108 106 4

5

6

7

M AN U

Aperture specific net design power output (W/m2)

126

8

9

10

11

12

Optimum Range 13

14

15

Turbine Inlet Pressure (MPa)

Fig. 17. Aperture specific net design power output as function of turbine inlet pressure for

TE D

different plant size with reheat-regenerative Rankine cycle.

AC C

EP

(In print: black/white)

50

ACCEPTED MANUSCRIPT

0.230 Place: Jodhpur (26.28°N, 73.02°E) ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

0.220

RI PT

PD = 5 MWe 0.210

PD = 25 MWe 0.200

SC

Levelized Cost of Energy ($/kWh)

Optimum Range

0.190

0.180 4

5

6

7

M AN U

PD = 50 MWe

8

9

10

11

12

13

14

15

Turbine Inlet Pressure (MPa)

Fig. 18. Levelized cost of energy as function of turbine inlet pressure for different plant size with reheat-regenerative Rankine cycle.

AC C

EP

TE D

(Web only: colour)

51

ACCEPTED MANUSCRIPT

0.230 Place: Jodhpur (26.28°N, 73.02°E) ID = 600 W/m2 Tmax = 370°C Treheat = 370°C

0.220

RI PT

PD = 5 MWe 0.210

PD = 25 MWe 0.200

SC

Levelized Cost of Energy ($/kWh)

Optimum Range

0.190

0.180 4

5

6

7

M AN U

PD = 50 MWe

8

9

10

11

12

13

14

15

Turbine Inlet Pressure (MPa)

Fig. 18. Levelized cost of energy as function of turbine inlet pressure for different plant size with reheat-regenerative Rankine cycle.

AC C

EP

TE D

(In print: black/white)

52

ACCEPTED MANUSCRIPT

0.230 Rankine Cycle with Reheat-Regeneration Tmax = 370°C Treheat = 370°C

RI PT

Jaipur

0.220

0.210 Hyderabad 0.200

SC

Levelized Cost of Energy ($/kWh)

Optimum Range

0.190

0.180 4

5

6

7

M AN U

Jodhpur

8

9

10

11

12

13

14

15

Turbine Inlet Pressure (MPa)

Fig. 19. Levelized cost of energy as function of turbine inlet pressure for different places with reheat-regenerative Rankine cycle.

AC C

EP

TE D

(Web only: colour)

53

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0.230 Rankine Cycle with Reheat-Regeneration Tmax = 370°C Treheat = 370°C

RI PT

Jaipur

0.220

0.210 Hyderabad 0.200

SC

Levelized Cost of Energy ($/kWh)

Optimum Range

0.190

0.180 4

5

6

7

M AN U

Jodhpur

8

9

10

11

12

13

14

15

Turbine Inlet Pressure (MPa)

Fig. 19. Levelized cost of energy as function of turbine inlet pressure for different places with reheat-regenerative Rankine cycle.

AC C

EP

TE D

(In print: black/white)

54

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List of Table Captions

Table 2. Equipment cost data for economic analysis.

RI PT

Table 1. Data used for the simulation.

Table 3. Financial parameters, operation and maintenance data for economic analysis.

AC C

EP

TE D

M AN U

SC

Table 4. Summary of results.

55

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Table 1. Data used for the simulation. Input Parameter

Value/Type

Reference

Collector field

Parabolic Trough Collector (PTC)

-

Collector field efficiency model

ηo = 0.7; Ul = 0.1 W/(m2·K)

Desai et al. (2013)

Collector tracking mode

RI PT

parameters

Focal axis N-S horizontal and E-W tracking Therminol VP-1

-

Collector outlet temperature

390°C (controlled)

Ambient temperature

30°C (design value)

Turbine isentropic efficiency

A = a1 + (a2·Tin,sat); B = b1 + (b2·Tin,sat)

model parameters

For turbine size <= 1.5 MW:

-

Shang (2000)

M AN U

SC

Collector field HTF

-

a1 = -0.0981 (MW); a2= 0.001 (MW/°C) b1 = 1.2059; b2 = 0.0006 (1/°C) For turbine size > 1.5 MW:

a1 = -0.0376 (MW); a2 = 0.0014 (MW/°C);

TE D

b1 = 1.1718; b2 = 0.0003 (1/°C) Turn down ratio of the turbine

0.2

-

Temperature driving force (∆Tmin)

10°C

-

Isentropic efficiency of the pump

0.6

-

0.1 bar

-

EP

(Pmin/Pmax)

AC C

Condensing pressure

56

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Table 2. Equipment cost data for economic analysis (Note: Parameters for cost correlations have been updated to 2014 using Chemical Engineering Plant Cost Index). Equipment

Cost correlation

Variable of cost correlation Reference

PTC field and

-

280 ($/m2)

HTF system Turbine

a ⋅ ( kW )

RI PT

Krishnamurthy et al. (2012)

a = 31093; b = 0.41

b

Gutiérrez-Arriaga et al.

(2014)

a = 2447; b = 0.49

b

a ⋅ ( kWth )

a = 597; b = 0.68

b

(

SC

Condenser

a ⋅ ( kWe )

)

M AN U

Generator

Boiler feed pump F ⋅ a + b ⋅ (kW ) + c ⋅ (kW )2 a = 6607; b = 485; P c = -0.417; FP = 2.12 Heat exchanger

0.65 a ⋅ AreaHX ⋅ ( Fc + 2.29)

Fc = ( Fd + F p ) ⋅ Fm

a = 533;

Gutiérrez-Arriaga et al.

(2014)

Gutiérrez-Arriaga et al. (2014) Gutiérrez-Arriaga et al. (2014) Douglas (1988)

Fd = 1.35 (kettle type),

0.85 (U-tube);

TE D

Fm = 1 (CS/CS material); Fp=0.25 (pressure 2.5 MPa), 0.52 (pressure 5.5 MPa), 0.55 (pressure > 6.9 MPa)

cost

AC C

Miscellaneous

a ⋅ kWe + b ⋅ (kWe)2

EP

Civil works

Land and site

a = 169; b = -0.00053

Krishnamurthy et al. (2012)

183 ($/kWe)

IIT Bombay (2012)

20 ($/m2)

IIT Bombay (2012)

development cost

57

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Table 3. Financial parameters, operation and maintenance data for economic analysis.

Operation and maintenance 2.5% of solar field cost

Annual operation and maintenance cost

4% of equipment cost

RI PT

Annual solar field component replacement cost

Discount rate (%)

10

Lifetime (years)

30

Table 4. Summary of results. Energy

Maximum

Cost

Minimum

Size

Optimum

Aperture Specific

Optimum

Levelized Cost

(MWe)

Range

Net Design Power

Range

of Energy

Output (W/m2)

(MPa)

(¢/kWh)

87.9

3.5-7.5

33.6

6.2-10

94.9

4.5-10

32.3

7.5-11.5

108.2

6-11.5

22.9

(MPa) CSP plant with

1

4.5-7.5

basic Rankine

CSP plant with

1

regenerative Rankine cycle

reheat Rankine

25

9-13.5

115.6

7.5-13.5

20.4

50

9-13.5

116.5

8-13.5

19.9

AC C

cycle

5

EP

CSP plant with

TE D

cycle

M AN U

Plant

SC

Financial parameters

CSP plant with

5

9-13

115.7

7-13

21.9

reheat-regenerative

25

10.5-15

123.5

9-15

19.4

Rankine cycle

50

10.5-15

124.7

9.5-15

18.8

58

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Highlights:

Energy-economic analysis of parabolic trough based solar power plant is reported

•

Effects of various parameters on overall efficiency and levelized cost of energy

•

Effects of turbine inlet pressure/temperature and design radiation are studied

•

Variations in plant capacities and Rankine cycle modifications are included

•

Optimum range of turbine inlet pressure for 1 MWe plant is about 3.5-7.5 MPa

AC C

EP

TE D

M AN U

SC

RI PT

•