Solar thermal power plant simulation.pdf

Solar Thermal Power Plant Simulation

Mohammad Abutayeh, Yogi D. Goswami, and Elias K. Stefanakos

Clean Energy Research Center, University of South Florida, Tampa, FL 33620; abutayeh@mail.usf.edu (for correspondence)

Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ep.11636

ferred to high pressure water generating high pressure steam.

The solar-generated steam is then used to propel a steam tur-

bine connected to a generator producing electricity.

A detailed model of a real solar thermal power plant has

been built using a steady-state power plant simulation soft-

ware. The plant includes numerous parabolic trough collectors

tracking the sun on a single axis. A heat transfer ﬂuid ﬂows

in the focal line of the troughs collecting solar heat, which is

transferred to high pressure water from the power block gener-

ating high pressure steam that is sent to a steam turbine to

generate electricity via an attached generator. In addition, a

spreadsheet has been formulated to work in tandem with the

simulation software to model the daily operation of the plant.

The spreadsheet is populated with 1 min increment time-

stamped operating data where computations are carried out to

estimate the thermal energy contribution of the warm up and

the cool down transient operations. Solar radiation offsets are

calculated based on those transient heats and then incremen-

tally added to the real-solar radiation data to produce effective

solar radiation records. Data columns of the effective solar

radiation, ambient temperature, humidity, wind speed, time

of day, day of year, and other geographical and optical con-

stants are incrementally passed from the spreadsheet to the

simulation program, which executes and outputs results back

into the same spreadsheet. Simulation results matched well

with plant data including data collected during warm up and

cool down transient operations. 2012 American Institute of

Chemical Engineers Environ Prog, 00: 000–000, 2012

Keywords: sustainability, solar energy, solar power, solar

thermal, transient modeling, power plant

OBJECTIVE

Several computer programs have been developed over

the years to model power plant performance such as Gate

Cycle TM , HYSYS TM , IPSEpro TM , Thermoﬂex TM , and others.

These software codes are geared toward modeling steady-

state operations, which is usually sufﬁcient for conventional

power plants. Solar thermal power plants undergo lengthy

start-up and shut-down operations due to the sporadic nature

of solar radiation; therefore, valid modeling of their perform-

ance must address those transient operations.

The start-up operation involves drawing heat from the

collected thermal energy in the early morning hours to warm

up the HTF and the metallic elements of its network, such as

pipes and vessels, which have cooled down overnight by

losing their heat to the ambient. The shut-down operation

involves exploiting the thermal energy stored in the HTF and

the metallic elements of its network to further the production

of steam, and consequently power, beyond sunset.

The purpose of this study is to accurately model the daily

performance of a PTC solar thermal power plant including

start-up and shut-down operations. A spreadsheet has been

built to pass data to and receive data from a detailed model

of an actual solar thermal power plant. The model will per-

form steady state simulations of discrete data received from

the spreadsheet in 1-minute increments. The spreadsheet

data correspond to real records that have been conditioned

to account for the transient start-up and shut-down opera-

tions.

INTRODUCTION

Solar power generation can be accomplished directly via

photovoltaic cells (PV) or indirectly via concentrating solar

power systems (CSP). PV technology involves DC power

generation from sunlight using the photoelectric effect. Sev-

eral solar panels composed of numerous PV cells generate

electricity due to emitted electrons from semiconductors

absorbing electromagnetic solar radiation. CSP technology

involves AC power generation using generators attached to

turbines supplied with solar-generated steam. Several sun-

tracking mirrors focus sunbeams onto a small aperture pro-

ducing immense heat that is used to generate steam to drive

the turbines of conventional Rankine cycle power plants.

At utility scale, CSP systems are currently more deployed

than PV systems due to the high cost, the low efﬁciency, and

the small energy storage capability of PV systems. CSP systems

are also more appealing because they use the familiar Rankine

power cycle and can be directly integrated into existing power

plants. The most economical and commercially available CSP

technology is parabolic trough collector systems (PTC). PTC

systems include numerous parabolic trough mirrors tracking

the sun on a single axis. A heat transfer ﬂuid (HTF) ﬂows in

the focal line of the troughs collecting solar heat that is trans-

SCHEMATICS

A distributed control system (DCS) is constantly collecting

and archiving plant data in mass storage servers. PI Process-

Book TM [1] is the database program used in retrieving plant

data so it can be processed in a spreadsheet. Microsoft

Excel TM [2] is the spreadsheet program used in requesting and

obtaining plant data so it can be processed in a modeling pro-

gram. IPSEpro TM [3] is the modeling program used in running

sequential simulations based on data supplied by the spread-

sheet. A general data ﬂow schematic is outlined in Figure 1.

The solar thermal power plant simulation process can be

illustrated by tracing the data streams mapped out in Figure

1. Stream 1 represents the date of the plant operation to be

modeled. Stream 2 represents time-stamped data of direct

normal insolation (DNI), ambient temperature, humidity,

wind speed, solar ﬁeld (SF) availability, and produced

power. Stream 2 also includes ﬂow rates, temperatures, and

pressures of the water and the HTF going into and out of the

heat exchanger train (HXT). Calculations are then performed

in the spreadsheet to compute direct incident insolation (DII)

plus start-up and shut-down heats for each time increment.

2012 American Institute of Chemical Engineers

Environmental Progress & Sustainable Energy (Vol.0000, No.0000) DOI 10.1002/ep

Month 2012

[4–6]. TC is a time correction term needed to adjust regular

time to solar time. TC is a function of time zone, longitude

angle, and day of year and is estimated by:

365 ðDay 81Þ

Figure 1. Data ﬂow schematic.

TC ¼ 4ð15TZ LongitudeÞþ9

87sin

365 ðDay 81Þ

7:53cos

1:5sin

Effective DII values representing the solar insolation that is

essentially used to generate power are then generated in the

spreadsheet. Stream 3 represents discrete data sets of date,

time, DNI, effective DII, ambient temperature, humidity, wind

speed, SF availability, and temperatures and pressures of the

water going into the HXT. The solar thermal power plant

model is sequentially executed using the discrete data sets of

Stream 3 producing results that are forwarded to the spread-

sheet as discrete data sets in Stream 4. Stream 4 represents dis-

crete data sets of heat collected by the SF and power pro-

duced. Stream 4 also includes ﬂow rates, temperatures, and

pressures of water and HTF going into and out of the HXT.

(1)

SD is the solar day which is also needed to adjust regular

time to solar time and is given by:

Day; 0 Hour þ TC=60 24

Day 1; Hour þ TC=60 < 0 AND Day > 1

Day þ 364; Hour þ TC=60 < 0 AND Day 1

Day þ 1

SD ¼

(2)

;

Hour þ TC

24 AND Day

365

;

Hour þ TC

24 AND Day 365

SPREADSHEET

The spreadsheet has been designed to retrieve time-

stamped operating data in 1-minute increments from plant

servers upon providing a speciﬁc date. This adds up to 1440

data sets, one set for every minute of the day. Each set

includes ambient weather data such as solar insolation, ambi-

ent temperature, humidity, wind speed, as well as other data

to be compared to model output later. In addition, the fol-

lowing constants are included in the spreadsheet: Longitude,

Latitude, Tilt, Orientation, N, L, FL, AW, RD, TZ, C Mirror ,

h Optical ,M HTF ,T Operation ,V Metal , q Metal , and Cp Metal .

The preceding data set records and constants represent a

complete list of inputs that can be forwarded to the model

for execution; however, the warm up and the cool down

transient operations will not be reﬂected in that execution.

Alternately, solar insolation records will need to be adjusted

to account for heat used in warming up the HTF and the me-

tallic elements of its network at the beginning of the day and

to account for the thermal energy stored in the HTF and the

metallic elements of its network at the end of the day. This

adjustment will produce effective solar insolation records

reﬂecting those transient operations, which will be forwarded

to the model for execution.

The following calculations are carried out for each data

set in the spreadsheet to compute the corresponding DII

SH is the solar hour used to calculate the annual solar

hour and is given by:

60 24

24 þ Hour þ TC=60; Hour þ TC=60 < 0

Hour þ TC=60 24; Hour þ TC=60 > 24

Hour þ TC

;

0 Hour þ TC

SH ¼

(3)

ASH is the annual solar hour given by:

ASH ¼ 24ðSD 1ÞþSH

(4)

Declination, hour, altitude, azimuth, and altitude trans-

verse solar angles are given by:

Declination ¼ sin 1

ð0:39795Þcosð0:98563ðp=180ÞðSD 173Þ (5)

HA ¼ðp=180Þð15ðSH 12ÞÞ

(6)

Altitude ¼ sin 1

ðsinðDeclinationÞsinðLatitudeÞÞ

þ cosðDeclinationÞcosðHAÞcosðLatitudeÞ

(7)

Azimuth ¼ p sin 1

ðcosðDeclinationÞsinðHAÞ=

cosðAltitudeÞÞ;

cosðHAÞtanðDeclinationÞ=

tan ðTCÞ

(8)

2p þ sin 1

ðcosðDeclinationÞsinðHAÞ=cosðAltitudeÞÞ; cosðHAÞ < tanðDeclinationÞ=tan ðTCÞ

(

Shadow efﬁciency is a multiplier used to adjust incident

solar radiation to account for PTC shadow eclipsing the solar

ﬁeld around sunrise and sunset.

Altitude; jAzimuth pj < 1

AT ¼

(9)

tanðAltitudeÞ

jcosðp=

tan 1

;

jAzimuth p 1j

2þAzimuthÞj

SA 1

SA is the shadow argument needed to evaluate shadow

effects on incident solar radiation. SA is a function of PTC

row distance and aperture width plus the altitude transverse

solar angle.

h Shadow ¼

;

(11)

SA;

0 SA < 1

IA is the incident angle deﬁned as the angle between so-

lar beams and the line normal to the PTC aperture. It is con-

stantly changing and can be calculated by:

AW cosðp=2 ATÞ

SA ¼

(10)

1 ðcosðAltitude TiltÞcosðTiltÞ cosðAltitudeÞð1 cosðAzimuth OrientationÞÞÞ

IA ¼ cos 1

(12)

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IAM is the incident angle modiﬁer multiplier used to

adjust incident solar radiation to account for direct and indi-

rect losses due to incident angle. IAM can be estimated by

the following correlation.

IAM ¼ cosðIAÞ0:0300802842443682:IA

0:0938882616103359:IA 2

Q MetalWU ¼ V Metal q Metal Cp Metal ðT Operaion T Start Þ=3:6

(19)

The thermal energy gained by cooling down the metallic

elements of the HTF network to the minimum operating tem-

perature is given by:

Q MetalCD ¼ V Metal q Metal Cp Metal ðT End T Operation Þ=3:6

(13)

(20)

End loss efﬁciency is a multiplier used to adjust incident

solar radiation to account for radiation incident on and

reﬂected off PTC periphery that does not

The total thermal energy lost to the warm up transient

operation is given by:

Q WU ¼ Q HTFWU þ Q MetalWU

land on the

(21)

absorber.

The total thermal energy gained by the cool down tran-

sient operation is given by:

Q CD ¼ Q HTFCD þ Q MetalCD

h EndLoss ¼ 1

tanðIAÞ

(14)

(22)

Absolute efﬁciency is the overall multiplier used to adjust

incident solar radiation given by:

h Absoulte ¼ h Optical

Subscripts: Operation, Start, and End in the above equa-

tions refer to minimum operating temperature, HTF tempera-

ture at the beginning of the day or sunrise, and HTF temper-

ature at the end of the day or sunset, respectively. An HTF

temperature of 2758C is a typical minimum operating temper-

ature. Therefore, the start-up operation at the beginning of

the day involves circulating the HTF in the SF while bypass-

ing the HXT until the HTF is warmed up from T Start to 2758C.

Conversely, the shut-down operation at the end of the day

involves circulating the HTF through the HXT until the HTF

is cooled down from T End to 2758C.

The following calculations are carried out for each data

set in the spreadsheet to compute its effective DII by offset-

ting its actual DII based on the overall start-up and shut-

down heat loads. At ﬁrst, the heat absorbed by the SF is cal-

culated for each data set in the spreadsheet by:

q DII ¼ N A Availability DII

h Shadow h EndLoss

C Mirror

IAM

(15)

DII represents the solar radiation available and exploited

to heat the HTF.

DII ¼ h Absoulte DNI

(16)

The following calculations are carried out collectively for

the entire data set in the spreadsheet to compute the overall

start-up and shut-down heat loads. Start-up heat is the ther-

mal energy needed to warm up the entire stock of HTF and

the metallic elements of its network at the beginning of the

day to a speciﬁed minimum operating temperature. Shut-

down heat is the thermal energy exploited by cooling down

the entire stock of HTF and the metallic elements of its net-

work at the end of the day to a speciﬁed minimum operating

temperature.

The thermal energy lost to warming up the HTF to the

minimum operating temperature is given by:

Q HTFWU ¼ M HTPF ðh Opertaion h Start Þ=

(23)

Warm up DII offsets are calculated for each data set in the

spreadsheet as follows:

(17)

Q WU R 0 q DII

N AAvailabilityDt g;

R 0 q DII < Q WU

The thermal energy gained by cooling down the HTF to

the minimum operating temperature is given by:

Q HTFCD ¼ M HTF ðh End h Operation Þ=

minfDII;

DII WU ¼

(24)

R 0 q DII Q WU

(18)

The thermal energy lost to warming up the metallic ele-

ments of the HTF network to the minimum operating tem-

perature is given by:

Cool down DII offsets are calculated for each data set in

the spreadsheet as follows:

R t

D DII CD

;

R t

q Previous

maxf ^

DII g

N AAvailability DII

q DII ;

Q CD

N AAvailabilityD

min

;

q DII < q DII :

1hr

DII CD ¼

(25)

R t q DII q DII :1hr

Integration limits: 0, 1, and t in the above equations refer

to ﬁrst, last, and current time increments, respectively. Super-

script: Previous refers to the previous time increment and

Accent ^ refers to an average value.

The last two relationships can be demystiﬁed by track-

ing their progression chronologically. Warm up DII offsets

equal zero until sunrise, upon which they equal DII until

the integrated amount of heat absorbed by the SF totals

up to the overall start-up heat load, after which they revert

back to zero for the rest of the day. In contrast, cool

down DII offsets equal zero until just before sunset (when

the remaining integrated amount of heat absorbed by the

SF is less than the average amount of heat absorbed by

the SF in 1 hour), upon which they equal a speciﬁed

amount of DII (the maximum of: the average daily DII or

the last DII value upon starting the cool down offsets)

until the integrated amount of cool down DII have caused

the SF to absorb an amount of heat equal to the overall

shut-down heat load, after which they revert back to zero

for the rest of the day.

Finally, the effective DII is calculated for each data set in

the spreadsheet as follows:

DII Effective ¼ DII DII WU þ DII CD

(26)

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Figure 2.

Input–output spreadsheet. [Color ﬁgure can be viewed in the online issue, which is available at wileyonlinelibrary.com .]

Figure 3.

IPSEpro model schematic. [Color ﬁgure can be viewed in the online issue, which is available at wileyonlinelibrary.

com .]

The distinction between DII and effective DII is analogous

to the distinction between the qualitative properties: concen-

tration and activity. Activity of a specie is a variation of its

concentration to account for its deviation from ideal behavior

at a certain thermodynamic state. Effective DII can be

thought of as a variation of DII to account for transient start-

up and shut-down heats.

The transient start-up and shut-down heats are now incor-

porated into these effective solar insolation records. In other

words, DII Effective represents the power block (PB) supply

source of thermal energy actually used for power generation.

Note that warm up DII offsets are calculated in a more objec-

tive approach, while cool down DII offsets are determined in

a more subjective manner. This will be evident later in the

smoothness of effective DII records at warm up and bumpi-

ness of effective DII records at cool down.

A screen shot of the beginning part of the spreadsheet is

shown in Figure 2. The columns of the spreadsheet extend

horizontally to cover the whole day, one column for every mi-

nute. The yellow region (second block from top) includes the

input operating data to be forwarded to the model for execu-

tion. The green region (third block from top) includes the out-

put data resulting from model execution. The gray region

(fourth block from top) includes the above calculation to

determine the effective DII for each data column, which is

then written in the yellow region to be forwarded to the

model for execution.

the shell side giving up heat to the process loop to produce

the needed high pressure steam before it is pumped back to

the SF. An expansion vessel is placed before the HTF pump to

both accommodate the extra HTF volume due to its thermal

expansion in the SF and to provide the necessary head for the

HTF pump to overcome its net positive suction head.

The model would normally calculate DII using input DNI,

time, date, and cleanliness records; however, this approach

overlooks the warm up and the cool down transient opera-

tions. Consequently, the equation relating DII to DNI in the

model is deactivated whereas the DII Effective calculated above

is input to the model. This will render the DNI records for-

warded to the model useless or dummy values. The solution

algorithm of the model is extensive due to the large number of

equations characterizing all the process equipment. In a nut-

shell, the HTF mass ﬂow required to attain a set

point temperature out of or into the SF is calculated knowing

DII Effective as well as PTC and piping characteristics, that is

dimensions plus heat and pressure loss coefﬁcients. The water

mass ﬂow is calculated knowing ambient conditions as well as

the many characteristics of the process equipment: steam tur-

bine, condenser, cooling tower, feed water pump, and HXT.

This modeling approach closely resembles actual solar thermal

power plant operation where the DCS manipulates HTF ﬂow,

via manipulating HTF pump speed, to attain a set HTF outlet

temperature. The HTF pump speed control logic usually com-

bines a temperature feedback control loop and a DII feedfor-

ward control loop for optimum control. One common mistake

in operating solar thermal power plants is the use of DNI as a

control variable; conversely, it is DII that should be used to

control operation instead because it is the variable that deter-

mines how much heat will be absorbed by the SF.

MODEL

A detailed model of a real solar thermal power plant has

been built using IPSEpro TM modeling software. A simpliﬁed

schematic of the plant is shown in Figure 3. The PB consists of

a two-stage steam turbine, a cooling tower driven condenser,

and a high pressure feed water pump. The SF comprises

numerous parabolic trough collectors with a 51 hectare com-

bined aperture area tracking the sun on a single North–South

axis in the East–West direction. Dowtherm TM A HTF ﬂows in

the focal line of the troughs collecting solar heat that is then

transferred to the process loop via the HXT. The HXT is made

up of an economizer, an evaporator, and a super heater con-

nected in series where the water and the HTF ﬂow in a coun-

ter-current pattern. High pressure water enters the economizer

to be heated to near saturation then evaporated to steam in the

evaporator then turned into superheated steam in the super

heater before it is forwarded to the steam turbine. Hot HTF

coming from the SF enters the super heater on the shell side,

then the evaporator on the tube side and the economizer on

RESULTS

Metrological and operational data from a newly built

PTC power plant was obtained for four days with smooth

uninterrupted operation. The plant does not include any

thermal energy storage system; therefore, it was on during

sunlight hours plus sometime afterward during the cool

down operation and it was off the rest of the day. HTF

heat losses during the night are not uniform as they

depend on the location within the SF. HTF present in the

header pipes and vessels loses only a small amount of its

heat due to good insulation, while HTF present in the

absorber tubes of the PTC assemblies loses a signiﬁcant

amount of its heat due to exposure. The normal operation

the plant

involves starting the HTF pump about an

Environmental Progress & Sustainable Energy (Vol.0000, No.0000) DOI 10.1002/ep

Month 2012

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