solar thermal power plant simulation

Solar Thermal Power Plant SimulationMohammad Abutayeh, Yogi D. Goswami, and Elias K. StefanakosClean Energy Research Center, University of South Florida, Tampa, FL 33620; [email protected] (for correspondence)

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

A detailed model of a real solar thermal power plant hasbeen built using a steady-state power plant simulation soft-ware. The plant includes numerous parabolic trough collectorstracking the sun on a single axis. A heat transfer fluid flowsin the focal line of the troughs collecting solar heat, which istransferred to high pressure water from the power block gener-ating high pressure steam that is sent to a steam turbine togenerate electricity via an attached generator. In addition, aspreadsheet has been formulated to work in tandem with thesimulation 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 toestimate the thermal energy contribution of the warm up andthe cool down transient operations. Solar radiation offsets arecalculated based on those transient heats and then incremen-tally added to the real-solar radiation data to produce effectivesolar radiation records. Data columns of the effective solarradiation, ambient temperature, humidity, wind speed, timeof day, day of year, and other geographical and optical con-stants are incrementally passed from the spreadsheet to thesimulation program, which executes and outputs results backinto the same spreadsheet. Simulation results matched wellwith plant data including data collected during warm up andcool down transient operations. � 2012 American Institute of

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

Keywords: sustainability, solar energy, solar power, solarthermal, transient modeling, power plant

INTRODUCTION

Solar power generation can be accomplished directly viaphotovoltaic cells (PV) or indirectly via concentrating solarpower systems (CSP). PV technology involves DC powergeneration from sunlight using the photoelectric effect. Sev-eral solar panels composed of numerous PV cells generateelectricity due to emitted electrons from semiconductorsabsorbing electromagnetic solar radiation. CSP technologyinvolves AC power generation using generators attached toturbines 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 drivethe turbines of conventional Rankine cycle power plants.

At utility scale, CSP systems are currently more deployedthan PV systems due to the high cost, the low efficiency, andthe small energy storage capability of PV systems. CSP systemsare also more appealing because they use the familiar Rankinepower cycle and can be directly integrated into existing powerplants. The most economical and commercially available CSPtechnology is parabolic trough collector systems (PTC). PTCsystems include numerous parabolic trough mirrors trackingthe sun on a single axis. A heat transfer fluid (HTF) flows inthe focal line of the troughs collecting solar heat that is trans-

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.

OBJECTIVE

Several computer programs have been developed overthe years to model power plant performance such as GateCycleTM, HYSYSTM, IPSEproTM, ThermoflexTM, and others.These software codes are geared toward modeling steady-state operations, which is usually sufficient for conventionalpower plants. Solar thermal power plants undergo lengthystart-up and shut-down operations due to the sporadic natureof solar radiation; therefore, valid modeling of their perform-ance must address those transient operations.

The start-up operation involves drawing heat from thecollected thermal energy in the early morning hours to warmup the HTF and the metallic elements of its network, such aspipes and vessels, which have cooled down overnight bylosing their heat to the ambient. The shut-down operationinvolves exploiting the thermal energy stored in the HTF andthe metallic elements of its network to further the productionof steam, and consequently power, beyond sunset.

The purpose of this study is to accurately model the dailyperformance of a PTC solar thermal power plant includingstart-up and shut-down operations. A spreadsheet has beenbuilt to pass data to and receive data from a detailed modelof an actual solar thermal power plant. The model will per-form steady state simulations of discrete data received fromthe spreadsheet in 1-minute increments. The spreadsheetdata correspond to real records that have been conditionedto account for the transient start-up and shut-down opera-tions.

SCHEMATICS

A distributed control system (DCS) is constantly collectingand archiving plant data in mass storage servers. PI Process-BookTM [1] is the database program used in retrieving plantdata so it can be processed in a spreadsheet. MicrosoftExcelTM [2] is the spreadsheet program used in requesting andobtaining plant data so it can be processed in a modeling pro-gram. IPSEproTM [3] is the modeling program used in runningsequential 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 beillustrated by tracing the data streams mapped out in Figure1. Stream 1 represents the date of the plant operation to bemodeled. Stream 2 represents time-stamped data of directnormal insolation (DNI), ambient temperature, humidity,wind speed, solar field (SF) availability, and producedpower. Stream 2 also includes flow rates, temperatures, andpressures of the water and the HTF going into and out of theheat exchanger train (HXT). Calculations are then performedin 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 1

Effective DII values representing the solar insolation that isessentially used to generate power are then generated in thespreadsheet. Stream 3 represents discrete data sets of date,time, DNI, effective DII, ambient temperature, humidity, windspeed, SF availability, and temperatures and pressures of thewater going into the HXT. The solar thermal power plantmodel is sequentially executed using the discrete data sets ofStream 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, andpressures of water and HTF going into and out of the HXT.

SPREADSHEET

The spreadsheet has been designed to retrieve time-stamped operating data in 1-minute increments from plantservers upon providing a specific date. This adds up to 1440data sets, one set for every minute of the day. Each setincludes ambient weather data such as solar insolation, ambi-ent temperature, humidity, wind speed, as well as other datato 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, CMirror,hOptical, MHTF, TOperation, VMetal, qMetal, and CpMetal.

The preceding data set records and constants represent acomplete list of inputs that can be forwarded to the modelfor execution; however, the warm up and the cool downtransient operations will not be reflected in that execution.Alternately, solar insolation records will need to be adjustedto account for heat used in warming up the HTF and the me-tallic elements of its network at the beginning of the day andto account for the thermal energy stored in the HTF and themetallic elements of its network at the end of the day. Thisadjustment will produce effective solar insolation recordsreflecting those transient operations, which will be forwardedto the model for execution.

The following calculations are carried out for each dataset in the spreadsheet to compute the corresponding DII

[4–6]. TC is a time correction term needed to adjust regulartime to solar time. TC is a function of time zone, longitudeangle, and day of year and is estimated by:

TC ¼ 4ð15TZ� LongitudeÞ þ 9:87sin4p365

ðDay� 81Þ� �

� 7:53cos2p365


� 1:5sin2p365


(1)

SD is the solar day which is also needed to adjust regulartime to solar time and is given by:

SD ¼

Day; 0 � Hourþ TC=60 � 24Day� 1;Hourþ TC=60 < 0 AND Day > 1Dayþ 364;Hourþ TC=60 < 0 AND Day � 1Dayþ 1;Hourþ TC=60 > 24 AND Day < 365

1;Hourþ TC=60 > 24 AND Day � 365

8>>>><>>>>:

(2)

SH is the solar hour used to calculate the annual solarhour and is given by:

SH ¼Hourþ TC=60; 0 � Hourþ TC=60 � 2424þ Hourþ TC=60;Hourþ TC=60 < 0Hourþ TC=60� 24;Hourþ TC=60 > 24

8<: (3)

ASH is the annual solar hour given by:

ASH ¼ 24ðSD� 1Þ þ SH (4)

Declination, hour, altitude, azimuth, and altitude trans-verse solar angles are given by:

Declination ¼ sin�1ð0:39795Þcosð0:98563ðp=180ÞðSD� 173ÞÞ(5)

HA ¼ ðp=180Þð15ðSH � 12ÞÞ (6)

Altitude ¼ sin�1ðsinðDeclinationÞsinðLatitudeÞÞþ cosðDeclinationÞcosðHAÞcosðLatitudeÞ (7)

Azimuth ¼ p� sin�1ð�cosðDeclinationÞsinðHAÞ=cosðAltitudeÞÞ; cosðHAÞ � tanðDeclinationÞ=tan ðTCÞ2pþ sin�1ð�cosðDeclinationÞsinðHAÞ=cosðAltitudeÞÞ; cosðHAÞ < tanðDeclinationÞ=tan ðTCÞ

�(8)

AT ¼Altitude; jAzimuth� pj < 1

tan�1 tanðAltitudeÞjcosðp=2þAzimuthÞj

� �; jAzimuth� p � 1j

((9)

SA is the shadow argument needed to evaluate shadoweffects on incident solar radiation. SA is a function of PTCrow distance and aperture width plus the altitude transversesolar angle.

SA ¼ RD

AWcosðp=2� ATÞ (10)

Shadow efficiency is a multiplier used to adjust incidentsolar radiation to account for PTC shadow eclipsing the solarfield around sunrise and sunset.

hShadow ¼1; SA � 10; SA < 0SA; 0 � SA < 1

8<: (11)

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:

IA ¼ cos�1ðffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1� ðcosðAltitude� TiltÞ � cosðTiltÞ cosðAltitudeÞð1� cosðAzimuth�OrientationÞÞÞ2

qÞ (12)

Figure 1. Data flow schematic.

2 Month 2012 Environmental Progress & Sustainable Energy (Vol.0000, No.0000) DOI 10.1002/ep

IAM is the incident angle modifier multiplier used toadjust incident solar radiation to account for direct and indi-rect losses due to incident angle. IAM can be estimated bythe following correlation.

IAM ¼ cosðIAÞ � 0:0300802842443682:IA

� 0:0938882616103359:IA2(13)

End loss efficiency is a multiplier used to adjust incidentsolar radiation to account for radiation incident on andreflected off PTC periphery that does not land on theabsorber.

hEndLoss ¼ 1� FL

LtanðIAÞ (14)

Absolute efficiency is the overall multiplier used to adjustincident solar radiation given by:

hAbsoulte ¼ hOptical � hShadow � hEndLoss � CMirror � IAM (15)

DII represents the solar radiation available and exploitedto heat the HTF.

DII ¼ hAbsoulte � DNI (16)

The following calculations are carried out collectively forthe entire data set in the spreadsheet to compute the overallstart-up and shut-down heat loads. Start-up heat is the ther-mal energy needed to warm up the entire stock of HTF andthe metallic elements of its network at the beginning of theday to a specified minimum operating temperature. Shut-down heat is the thermal energy exploited by cooling downthe entire stock of HTF and the metallic elements of its net-work at the end of the day to a specified minimum operatingtemperature.

The thermal energy lost to warming up the HTF to theminimum operating temperature is given by:

QHTFWU ¼ MHTPFðhOpertaion � hStartÞ=3:6 (17)

The thermal energy gained by cooling down the HTF tothe minimum operating temperature is given by:

QHTFCD ¼ MHTFðhEnd � hOperationÞ=3:6 (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:

QMetalWU ¼ VMetalqMetalCpMetalðTOperaion � TStartÞ=3:6 (19)

The thermal energy gained by cooling down the metallicelements of the HTF network to the minimum operating tem-perature is given by:

QMetalCD ¼ VMetalqMetalCpMetalðTEnd � TOperationÞ=3:6 (20)

The total thermal energy lost to the warm up transientoperation is given by:

QWU ¼ QHTFWU þ QMetalWU (21)

The total thermal energy gained by the cool down tran-sient operation is given by:

QCD ¼ QHTFCD þ QMetalCD (22)

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 HTFtemperature of 2758C is a typical minimum operating temper-ature. Therefore, the start-up operation at the beginning ofthe day involves circulating the HTF in the SF while bypass-ing the HXT until the HTF is warmed up from TStart to 2758C.Conversely, the shut-down operation at the end of the dayinvolves circulating the HTF through the HXT until the HTFis cooled down from TEnd to 2758C.

The following calculations are carried out for each dataset 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:

qDII ¼ N � A � Availability � DII (23)

Warm up DII offsets are calculated for each data set in thespreadsheet as follows:

DIIWU ¼ minfDII; QWU�R t

0qDII

N �A�Availability�Dtg;R t

0 qDII < QWU

0;R t

0 qDII � QWU

8<: (24)

Cool down DII offsets are calculated for each data set inthe spreadsheet as follows:

DIICD ¼ minmaxfqDII;qPreviousDII gN �A�Availability � DII

�� ; QCD

N �A�Availability�Dt �R t

DDIICD

Dt

� �;

R1t qDII < qDII:1 hr

0;R1t qDII � qDII:1 hr

8><>: (25)

Integration limits: 0, 1, and t in the above equations referto first, last, and current time increments, respectively. Super-script: Previous refers to the previous time increment andAccent ^ refers to an average value.

The last two relationships can be demystified by track-ing their progression chronologically. Warm up DII offsetsequal zero until sunrise, upon which they equal DII untilthe integrated amount of heat absorbed by the SF totalsup to the overall start-up heat load, after which they revertback to zero for the rest of the day. In contrast, cooldown DII offsets equal zero until just before sunset (whenthe remaining integrated amount of heat absorbed by the

SF is less than the average amount of heat absorbed bythe SF in 1 hour), upon which they equal a specifiedamount of DII (the maximum of: the average daily DII orthe last DII value upon starting the cool down offsets)until the integrated amount of cool down DII have causedthe SF to absorb an amount of heat equal to the overallshut-down heat load, after which they revert back to zerofor the rest of the day.

Finally, the effective DII is calculated for each data set inthe spreadsheet as follows:

DIIEffective ¼ DII� DIIWU þ DIICD (26)


Figure2.

Input–outputspread

sheet.[Colorfigure

canbeviewedin

theonlineissue,whichisavailable

atwileyonlinelibrary

.com.]


The distinction between DII and effective DII is analogousto the distinction between the qualitative properties: concen-tration and activity. Activity of a specie is a variation of itsconcentration to account for its deviation from ideal behaviorat a certain thermodynamic state. Effective DII can bethought 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 otherwords, DIIEffective represents the power block (PB) supplysource 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 ina more subjective manner. This will be evident later in thesmoothness 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 isshown in Figure 2. The columns of the spreadsheet extendhorizontally to cover the whole day, one column for every mi-nute. The yellow region (second block from top) includes theinput 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 todetermine the effective DII for each data column, which isthen written in the yellow region to be forwarded to themodel for execution.

MODEL

A detailed model of a real solar thermal power plant hasbeen built using IPSEproTM modeling software. A simplifiedschematic of the plant is shown in Figure 3. The PB consists ofa two-stage steam turbine, a cooling tower driven condenser,and a high pressure feed water pump. The SF comprisesnumerous parabolic trough collectors with a 51 hectare com-bined aperture area tracking the sun on a single North–Southaxis in the East–West direction. DowthermTM A HTF flows inthe focal line of the troughs collecting solar heat that is thentransferred to the process loop via the HXT. The HXT is madeup 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 economizerto be heated to near saturation then evaporated to steam in theevaporator then turned into superheated steam in the superheater before it is forwarded to the steam turbine. Hot HTFcoming from the SF enters the super heater on the shell side,then the evaporator on the tube side and the economizer on

the shell side giving up heat to the process loop to producethe needed high pressure steam before it is pumped back tothe SF. An expansion vessel is placed before the HTF pump toboth accommodate the extra HTF volume due to its thermalexpansion in the SF and to provide the necessary head for theHTF pump to overcome its net positive suction head.

The model would normally calculate DII using input DNI,time, date, and cleanliness records; however, this approachoverlooks the warm up and the cool down transient opera-tions. Consequently, the equation relating DII to DNI in themodel is deactivated whereas the DIIEffective calculated aboveis input to the model. This will render the DNI records for-warded to the model useless or dummy values. The solutionalgorithm of the model is extensive due to the large number ofequations characterizing all the process equipment. In a nut-shell, the HTF mass flow required to attain a setpoint temperature out of or into the SF is calculated knowingDIIEffective as well as PTC and piping characteristics, that isdimensions plus heat and pressure loss coefficients. The watermass flow is calculated knowing ambient conditions as well asthe many characteristics of the process equipment: steam tur-bine, condenser, cooling tower, feed water pump, and HXT.This modeling approach closely resembles actual solar thermalpower plant operation where the DCS manipulates HTF flow,via manipulating HTF pump speed, to attain a set HTF outlettemperature. 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 mistakein operating solar thermal power plants is the use of DNI as acontrol variable; conversely, it is DII that should be used tocontrol operation instead because it is the variable that deter-mines how much heat will be absorbed by the SF.

RESULTS

Metrological and operational data from a newly builtPTC power plant was obtained for four days with smoothuninterrupted operation. The plant does not include anythermal energy storage system; therefore, it was on duringsunlight hours plus sometime afterward during the cooldown operation and it was off the rest of the day. HTFheat losses during the night are not uniform as theydepend on the location within the SF. HTF present in theheader pipes and vessels loses only a small amount of itsheat due to good insulation, while HTF present in theabsorber tubes of the PTC assemblies loses a significantamount of its heat due to exposure. The normal operationof the plant involves starting the HTF pump about an

Figure 3. IPSEpro model schematic. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]


hour before sunrise to homogenize the HTF temperaturethroughout the SF. PTC assemblies start tracking the sunupon sunrise adding heat to the HTF which is circulatingthroughout the SF but bypassing the HXT to bring up itstemperature to the operating point. Once the HTF reachesthe operating temperature of 2758C, it starts to runthrough the HXT to make steam. The DCS aims to attaina 3958C HTF temperature out of the SF by manipulatingits residence time in the absorber tubes running in thefocal line of the PTC assemblies via regulating its flowrate. This thermal energy flow into the HXT is what

determines how much steam gets made and thereforehow much power is produced. This operation continuesuntil sunset when the thermal energy source heads offand the HTF begins to cool down. The plant keeps run-ning afterward until the HTF cools down to 2758C beforeit is shut.

Solar insolation records are shown in Figures 4-7. DNIrepresents normal insolation encountered during daylighthours while DII represents the fraction of DNI that is incidenton the absorber tube. DII is obtained by multiplying DNI byseveral efficiency factors accounting for mirror cleanliness,

Figure 4. Insolation on March 11, 2011. [Color figure can beviewed in the online issue, which is available at wileyonlinelibrary.com.]




Figure 8. HTF temperature on March 11, 2011. [Color figurecan be viewed in the online issue, which is available atwileyonlinelibrary.com.]

Figure 9. HTF temperature on March 18, 2011. [Color figurecan be viewed in the online issue, which is available atwileyonlinelibrary.com.]


reflectivity, shadow effects, and incident angle as seen earlier.Effective DII is a variation of DII representing the supplysource of the thermal energy actually used for power genera-tion as seen earlier. Effective DII lags DII during start-up toaccount for warm up heat, equals DII during normal operat-ing period, and leads DII during shut-down to account forcool down heat. This is consistent with the PTC power plantrecords where, on good sunny days, start-up usually occursabout 1 h after sunrise and production usually continues forabout 2 h after sunset. Daylight savings time for 2011 startedon March 13th, hence the apparent one hour discrepancybetween Figure 4 and Figures 5-7.

HTF temperature coming from the SF correlates with theamount of steam produced by the HXT; therefore, it indi-rectly gages electric power generation. HTF temperaturerecords coming from the SF and heading for the HXT areshown in Figures 8-11. Plant records outside of the operatingrange do not represent true values for comparison withmodel predictions since the HTF is not circulating; however,they demonstrate the small amount of HTF heat loss fromthe insulated header pipes and vessels. On the other hand,the sudden drop of HTF temperature upon starting HTF cir-culation is due to the much cooler HTF coming from theexposed absorber tubes of the PTC assemblies in the SF. SSModel records correspond to results obtained by running amodel that does not employ the DIIEffective method outlinedabove; therefore, it is dubbed steady state (SS) model. Incontrast, QT Model records correspond to results obtainedby running a model that employs the DIIEffective method out-lined above; therefore, it is dubbed quasi transient (QT)model. QT Model records are clearly a lot closer to plant

data than SS Model records indicating a significant improve-ment to model simulations gained by implementing the pro-posed DIIEffective method outlined above.

Gross electrical energy output is obtained by integratingthe produced power over the entire day. Table 1 demon-strates how close model predictions of gross electrical energyproduction are to actual plant data for the four simulateddays.

CONCLUSION

A novel technique has been developed to simulate theperformance of solar thermal power plants. The techniqueinvolves importing time–stamped operating data into aspreadsheet, adjusting real solar insolation records to pro-duce effective insolation records that reflect transient start-upand shut-down operations, incrementally passing theadjusted records to a SS model of the solar thermal powerplant to be executed, and forwarding simulation results tothe spreadsheet. Simulation results obtained by applying thistechnique matched well with the plant data, unlike simula-tion results obtained without solar insolation records adjust-ment, including the data collected during the warm up andcool down transient operations.

Slight discrepancy is still present between plant data andmodel results during the warm up and cool down transientperiods requiring further investigations. This discrepancycould be attributed to a physical phenomenon not accountedfor the model or to an inefficiency in plant operation or pro-cess control.

NOTATION

A PTC Aperture area, m2

Altitude Altitude angle, radiansASH Annual solar hour, hAT Altitude transverse, radiansAvailability PTC loops operating, %AW PTC aperture width, mAzimuth Azimuth angle, radiansC PTC mirror cleanliness, %CD Cool downCp Heat capacity, kJ/kg8CCSP Concentrating solar powerDay Day of year, dayDCS Distributed control systemDeclination Declination angle, radiansDII Direct incident insolation, W/m2

DNI Direct normal insolation, W/m2

FL PTC focal length, mh Enthalpy, kJ/kgHA Hour angle, radiansHour Hour of day, hHTF Heat transfer fluidHXT Heat exchanger trainIA Incident angle, radiansIAM Incident angle modifier, %L PTC length, mLatitude Latitude angle, radiansLongitude Longitude angle, degreesM Mass, kg

Figure 11. HTF temperature on March 25, 2011. [Colorfigure can be viewed in the online issue, which is availableat wileyonlinelibrary.com.]

Figure 10. HTF temperature on March 22, 2011. [Colorfigure can be viewed in the online issue, which is availableat wileyonlinelibrary.com.]

Table 1. Gross electricity production in MWh.

DateActualOutput

ModelPrediction

Difference(%)

March 11, 2011 658 685 4March 18, 2011 653 679 4March 22, 2011 561 596 6March 25, 2011 553 570 3


N PTC countOrientation PTC orientation angle, radiansPB Power blockPTC Parabolic trough collectorPV Photovoltaicq Heat flow, WQ Heat, W hQT Quasi transientRD PTC row distance, mSA Shadow argumentSD Solar day, daySF Solar fieldSH Solar hour, hSS Steady statet Time, hT Temperature, 8CTC Time correction term, minTES Thermal energy storageTilt PTC tilt angle, radiansTZ Time zone, hV Volume, m3

WU Warm upDt Time increment, hh Efficiency, %q Density, kg/m3

LITERATURE CITED

1. (2010). PI ProcessBook—Part of PI software developmentkit. Version 3.2. San Leandro, CA: OSIsoft LLC.

2. (2006). Excel—Part of microsoft office professional plus.Version 2007. Redmond, WA: Microsoft Corporation.

3. (2003). IPSEpro—Integration process simulation environ-ment. Version 4.0. Graz, Austria: SimTech SimulationTechnology.

4. Lippke, F. (1995). Simulation of the part load behavior ofa 30-MWe SEGS plant, SAND95-1293, Albuquerque, NM:Sandia National Laboratories.

5. Cohen, G.E., Kearney, D.W., & Kolb, G.J. (1999). Finalreport on the operation and maintenance improvementprogram for concentrating solar power plants, SAND99-1290. Livermore, CA: Sandia National Laboratories.

6. Rheinlander, J., Bergmann, S., & Erbes, M.R. (2008).Technical and economic performance of parabolic troughsolar power plants—A computational tool for plant feasi-bility studies. 14th SolarPACES International Symposiumon Concentrated Solar Power and Chemical Energy Tech-nologies, Las Vegas, NV.


solar thermal power plant simulation

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