Validating the performance simulation program “SOLDES” using data from an operating solar desalination plant

ELSEVIER Desalination 130 (2000) 235-253

DESALINATION

www.elsevier.com/locate/desal

Validating the performance simulation program "SOLDES" using data from an operating solar desalination plant

Ali M. E1-Nashar Desalination Laboratory, The Research Center, Abu Dhabi Water and Electricity Authority,

PO Box 41375, Abu DhabL UAE Fax +971 (2) 443-4096; email: [email protected]

Received 7 April 2000; accepted 20 July 2000

Abstract

A computer program (named SOLDES) was developed to simulate the operation of solar desalination plants which utilize evacuated tube collectors, heat accumulators and multiple-effect distillation (MED) systems. The heat accumulator used is of the thermally stratified type using pure water as the storage fluid. The procedure was written in Fortran language and consists of a main program, 22 sub-programs, two system data files and four meteorological data files. The absorber area of the solar collector field can be varied between 500 m 2 and 20,000 m2; the storage capacity per unit collector area of the heat accumulator can vary between 0.05 and 1.00m3/m2; the capacity of the evaporator can be varied between 100 m3/d to 2000 m3/d. The heat collecting system uses a bypass circuit to allow the heat collecting fluid (pure water) to recirculate back to the solar collector field when the outlet temperature from the collector field is below a set- point. When the collector outlet temperature rises above the set-point, operation is switched over to the accumulator side. A solar-cell- type controller is used to start and stop the water circulating pump of the collector field. The operation of the MED evaporator is controlled by the state of charge of the heat accumulator by the use of set-point switches which allow the evaporator to start up when the accumulator water temperature is above a set-point and to shut down if the water temperature drops below the set point. In order to validate the SOLDES program, a comparison was made between the predicted results of the program and the actual measured data from a solar plant of similar design features to the simulation program. The selected plant was the one in actual operation in Abu Dhabi, UAE, which has almost identical design features as the simulation program and has been in operation since 1984. The data from the plant collected during 1985 were used to compare the simulation results for the months of January and June. These two months were found to be typical of a winter month (January) and of summer months (June). Except for days when a plant interruption took place, such as a power failure, the agreement between the measured and simulation data appears to be quite good.

Keywords: Solar desalination; Performance simulation; Solar distillation; Program validation; Seawater desalination

1. Introduction The performance o f a desalination plant which

uses solar energy as the heat source is affected by

the weather conditions prevailing in the plant site. Among the meteorological parameters which affect the performance are the solar radiation,

0011-9164/00/$- See front matter © 2000 Elsevier Science B.V. All rights reserved PII: S0()I 1 -9164 (00 )00089-8

236 A.M. EI-Nashar / Desalination 130 (2000) 235-253

ambient temperature, wind velocity, dust content in the air and humidity. These parameters are subject to continuous change from hour to hour. In order to simulate the operating performance of such a plant to some degree of accuracy, a computer-based program is indispensable if, to cope with these changes, the system operation states are to be grasped and the amount of product water annually produced is to be forecast.

One of the programs which was developed to simulate the operating performance of solar desalination plants which uses the multiple-effect distillation (MED) process for seawater desalination and solar thermal collectors of the evacuated-tube type and thermally-stratified heat storage is SOLDES (for solar desalination), which written in the Fortran language [1,2]. The program is intended to simulate solar desalination plants of this type having different rated capacity, collector area and heat storage capacity. The program is designed to take into consideration such operational factors as the timing of collector cleaning, evaporator start-up and shut-down set- points and collector bypass set-points.

The objective of this paper is to verify the validity of this simulation program by comparing its results with actual measurements from a demonstration plant having an essentially identical design to that used in the simulation program. The demonstration plant used for this purpose is the Abu Dhabi solar desalination plant which is currently in operation near Abu Dhabi City, UAE.

2. The simulation program

2.1. Solar desalination system considered

Fig. 1 is a schematic diagram of the solar desalination system under investigation [3]. A field of evacuated tube collectors is used to provide thermal energy required by a multiple- effect, vertically-stacked seawater evaporator. A

heat accumulator is provided between the collector field and the evaporator in order to allow the evaporator to achieve continuous running throughout day and night and during overcast periods.

The collector field has a by-pass line to allow the fluid discharged from the field to return back for further heating when the fluid temperature is too low. Two motorized valves are used in the collector field to control the temperature of water entering the heat accumulator, one valve installed in the by-pass line and the other in the supply line to the accumulator. When one valve is open, the other is closed. A temperature sensor (RTD) installed in the discharge line of the collector field monitors the water temperature leaving the collectors; if it is below a set-point, the by-pass valve will be open and the accumulator supply valve will be closed. If the temperature is above the set-point, the by-pass valve will close and the supply valve will open. This will ensure that the water temperature entering the accumulator tank will always be above a set-point.

The operation of the boat collector pump is controlled by a controller which provides a start- up (when pump is shut down) or shut-down (when pump is operating) signals to the pump, depending on the intensity of solar radiation measured by a solar sensor. After sunrise, as soon as the solar radiation intensity reaches a certain value (which depends on the water temperature at the bottom of the accumulator), the controller sends a start-up signal to the pump to begin pumping water through the col lectors. Just before sunset and as soon as the radiation intensity reaches another low value, the controller sends a shut-down signal to the pump to stop operation.

The heat accumulator used in this system is a thermally stratified water tank. By virtue of density variation between the top and bottom layers, the higher temperature water is located in the upper region of the accumulator tank while the lower temperature water occupies the lower region. The lower temperature water is drawn

Temperature controller Heat accumulator

Solar controller ~ ." .~ .) I~u

Solar£r

A.M. EI-Nashar / Desalination 130 (2000) 235-253

RTD Heat collecting

pump

Heating Water pump

~ m

Seawater in

Fig. 1. Schematics of solar desalination system.

237

MES evaporator

L

Seawater out

from the bottom of the tank and pumped through the collector field by the heat-collecting pump. The hot water returning from the collector field is forced to flow to the top of the tank. The hot water from the top region of the accumulator is drawn from this region by another pump - - called the heating water pump - - which supplies this water to the first effect of the multiple-effect evaporator. As this water flows through the tube bundle of the first effect, it cools down, thus providing the thermal energy required by the evaporator. The return water from the first effect flows to the bottom of the accumulator tank.

The MED evaporator has a number of effects that can be varied by the designer according to the desired performance ratio and top brine temperature. Each effect, with the exception of the first, consists of a tube bundle where vapor generated in the previous effect flows through the tubes. The first effect, as was mentioned earlier, has heating water from the accumulator flowing through the tubes. In addition to the effects, the

evaporator has a number of feed water preheaters - - equal to the number of effects minus one - - and a condenser. The absolute pressure to be maintained in the final condenser is designed to be 50mmHg. The pressure to be maintained in each effect varies from slightly below atmos- pheric in the first effect to about 50 mm Hg in the last effect.

Seawater is used to condense the vapor generated in the last effect. Part of the discharged warm seawater leaving the final condenser returns to the sea, while the other part constitutes the evaporator feedwater. The feedwater flows through all the preheaters before being admitted to the first effect.

2.2. Program structure

Fig. 2 is an abbreviated flow chart of the SOLDES simulation program [ 1 ]. The equipment specifications, calculation conditions and other data are divided into two groups: system data no.

238 A.M. El-Nashar / Desalination 130 (2000) 235-253

Next hour

{ START J

~'~put syst~n c~ta I 1

I ~ u t meteorological data I

I I

calculations

Solar altitude I Solar azimuth

I Houdy ambient temperature I (ambient temp. model) . )

Hourly direct and diffuse radial~n on tilled surface

(SO ar radiation model)

I Shadow influence on ab,s,,orber plate I

I Solar radiation on absorber plate I

Heat supplied to evaporator Product water flow

I Temp. distribution in accumulator I

Fig. 2. Flow chart of the simulation program for the solar desalination plant.

1 (SYDT1) and system data no. 2 (SYDT2), and they are supplied to the program as input. The data input with SYDT1 serve to output error messages and suspend the execution of calculation in cases where there are errors in the input

data or where allowable ranges are exceeded. The climatic data can be selected from among four types of data, MEDT1, MEDT2, MEDT3 and MEDT4, depending on whether hour-by-hour data or day-by-day data are used. In each meteorological data file, the following additional data are included at the beginning of the file: • Location data: site name, latitude, longitude

and principal meridian longitude. • Monthly average seawater temperature. • Solar radiation sensor angle: tilt angle and

azimuth angle.

Any calculation period ranging from a day to a year can be designated, and an energy balance in the system is calculated every 30 min in relation to the calculation loop. The calculation results can be output either by the day or by the month.

The SOLDES program is composed of 22 subroutine programs, two sets of system data and four types of climatic data. The programs and the data involved are listed in Table 1.

Once the input data are read by the program, execution of the heat collection calculations starts. This involves calculating the solar declination and equation of time which are estimated once every day. The rest of the calculations are carried out on an hourly basis. For each hour of the day, the solar altitude, solar azimuth, hourly direct and diffuse radiation components on the absorber plate, heat collection amount, temperature distribution in the heat accumulator, heat supplied to evaporator and evaporator production rate are estimated [7].

Mathematical models were developed for each major plant component in order to predict the performance characteristics of each component in terms of output as a function of component input. Details of these models were given in [1,2]. Detailed mathematical models were developed for the following entities: • Numerical model to estimate solar radiation

on tilted surface.

A.M. E1-Nashar / Desalination 130 (2000) 235--253 239

Table 1 Program and data file names

Item Name Item Name

Main program SOLDES Dust effect model Subroutine programs: Input SYDT1 SDIN 1 Input SYDT2 SDIN2 Input location data SDIN3 Select piping dimensions PIPE Evaporator performance EVAP Echo back of input data ECBAK Solar declination and SODEC

extraterrestrial radiation Solar altitude and solar azimuth SOALT Radiation model No. 1 RADML1 Radiation model No. 2 RADML2 Radiation model No. 3 RADML3 Radiation model No. 4 RADML4 Ambient temp. model TEMPML Shadow dimension SHADOW Transmissivity of glass tube TRNGL

Shadow effect Solar controller operation Temp. distribution in heat accumulator Heat collection amount Printout of data output Adjustment of significant figures System data files: System data file No. 1

System data No. 2 Meteorological data: Meteorological data No. 1 Meteorological data No. 2 Meteorological data No. 3 Meteorological data No. 4

EFDUST TRAN S SCONT TDSTOR HCOLL DTPRI EFF1G

SYDT1

SYDT2

MEDT1 MEDT2 MEDT3 MEDT4

• Model to predict the effect of shade on the solar radiation on collector absorber plate.

• Ambient temperature model. • Effect of dust on transmissivity of collector

glass tubes. • Model for the control of heat collecting

operation. • Model to predict amount of heat collected by

collector field. • Model to predict piping heat loss from solar

collector field. • Model to predict operation of by-pass valve. • Model to predict operation of stratified heat

accumulator. • Model to predict performance of evaporator.

2.3. Input data and their range

One of four types of meteorological data can be used in the simulation program as shown in

Table 2. In each meteorological data file, the following additional data are included at the beginning of the file: • Location data: site name, latitude, longitude

and principal meridian longitude. • Monthly average seawater temperature. • Solar radiation sensor angle: tilt angle and

azimuth angle.

In conducting a computer simulation of a solar desalination plant, input data are revised according to changes in plant specifications such as absorber area, accumulator capacity, or evaporator capacity. Details changeable with the input data SYDT1 are as follows: • title of simulation • starting and finishing dates of simulation

(periods from 1 day to one whole year are permitted)

• specification of daily printout for each month

240 .4.M. El-Nashar / Desalination 130 (2000) 235-253

Table 2 Types of meteorological data which can be used in simulation program

Data name Measured solar radiation data Measured ambient temperature data

MEDT1 Hourly total solar radiation on tilted surface (data Hourly ambient temperature (data obtained obtained from the Abu Dhabi solar plant site) from Abu Dhabi solar plant site)

Hourly solar radiation on horizontal surface

Daily total solar radiation on tilted surface

MEDT2

MEDT3

MEDT4 Daily total solar radiation on horizontal surface

Hourly ambient temperature

Daily mean, daily maximum, and daily minimum ambient temperature

Daily mean, daily maximum and daily minimum ambient temperature

• correction coefficient of ambient temperature by month

• absorber area (500 m2-20,000 m 2) • Azimuth angle of collector ( - 180°-+180 °) • collector support angle (0.000-90.00 °) • tilt angle of absorber plate (equal to site

latitude) • heat collecting water flow rate per unit

absorber area (0.0285-0.0735 m3/h m 2) • heat collecting pump rated power consump-

tion • heat accumulator capacity per unit absorber

area (0.05-1.00 m3/m 2) • initial temperature distribution of heat

accumulator • evaporator rated capacity (100-2000 m3/d) • maximum brine temperature in evaporator

(60.0-80.0°C) • number of effects of evaporator (13-32) • heating water flow rate • seawater flow rate into evaporator condenser • power consumption of vacuum pump and

other evaporator pumps • by-pass valve open/stop temperature set-point • evaporator start/stop temperature set-points • correction coefficient of dust influence • specification of collector cleaning day

The second input data file, SYDT2, includes information on the following:

• specifications of hourly data printout • collector specifications • collector cleaning water amount • specifications of piping and

materials • heat accumulator material and

specifications • evaporator specifications • solar controller specifications

insulation

insulation

2.4. Output results

The following three types of data can be output by the program: • echo-back of values set in program and input

data • totaled data by the day • totaled data by the month

The daily totaled data include solar radiation on horizontal and tilted planes, amount of heat collected, amount of heat delivered to accumulator, amount of heat delivered to evaporator, amount of distillate produced and amount of electricity consumed by the pumps. The program output also includes average ambient temperature, average of accumulator water temperature at the end of the day and m a x i m u m average a c c u m u l a t o r wa te r temperature during the day.

A.l : Ei.Nashar / Desalination 130 (2000) 235-253 241

The monthly totaled data give tl:e monthly integrated amounts of" • solar radiation incident on horizontal plane • solar radiation incident on tilted plane • solar radiation incident on absorber plane

after subtracting the amount lost :lue to shading

• amount of heat collected by solar collector field

• amount of heat collected duri:g by-pass operation

• amount of heat loss to ambient by collector piping

• amount of heat supplied to accumulator

Table 3 Specifications ofAbu Dhabi solar desalination plant

Equipment Specification

Solar collectors: Type Evacuated tube, flat plate Total absorber area 1862 m 2 Tilt angle 21 ° due south Heat accumulator: Capacity 300 m 3 Heat storage fluid Distilled water Evaporator: Type Multiple-effect stack Design capacity 120 m3/d Maximum brine temp. 68°C Number of effects 18 Performance ratio 13

3. Experimental plant

3.1. Plant description and its design specifications

In order to validate the computer simulation, a comparison was made between the results of the simulation program and the measured data of the Abu Dhabi solar desalination plant. The specifications of the plant are shown in Table 3. A bank of evacuated tube collectors - - whose orientation (21 ° due south) with respect to the sun has been optimized in order to collect the maximum amount of solar radia t ion-- is used to heat the collector fluid (water) to a maximum temperature of about 95°C. The effective collector area of the bank is 1862 m s.

The heat collecting water leaving the collector bank flows into the top of the heat accumulator, which consists of three tanks connected in series and has a total capacity of 300m 3. The heat accumulator system is a stratified liquid type where, by virtue of density variation between the top and bottom layers, the higher temperature water is located in the upper region of the accumulator tank while the lower temperature water occupies the lower region.

The heat collecting water is drawn from the

top of the accumulator tank by the heating water circulating pump and is forced to flow into the evaporating tube bundle of the first effect of a MED-type evaporator. This evaporator is designed for a rated distillate production of 120m3/d from seawater having a salinity of 55,000 ppm and consists of 18 effects. By transferring heat to the cooler brine flowing on the outside of tube bundle of the first effect tube bundle, the heating water is cooled from its original temperature and is returned to the heat accumulator.

The 18 effects of the MED evaporator are stacked one on top of the other in a two-tier arrangement where the top brine temperature is located in the first effect while the bottom brine temperature is at the lower end of the stack. In addition to the 18 effects, the evaporator has 17 preheaters in series where feedwater is heated before being introduced to the first effect. It also has a final condenser where the vapor generated in the last (18th) effect is condensed. The MED evaporator operates under vacuum maintained by a water seal vacuum pump operated by an electric motor.


3.2. Measurements and data acquisition system

The performance of the solar collector field was monitored by measuring the following parameters: • instantaneous solar radiation on a tilted

surface with a tilt angle identical to the tilt angle of the collector absorber plate

• water temperatures at the inlet and outlet of the collector field

• water flow rate through the collector field • instantaneous heat collected by the solar

collector field n kWhs consumed by the heat collecting pump • daily number of hours the heat collecting

pump has been in operation

Solar radiation was measured by a star-shaped pyranometer (Lambrecht, Germany) tilted at an angle equal to the tilt angle of the absorber plates of the collectors (21 ° due south). The output signal from this sensor (in millivolts) is amplified and then converted to a pulse signal with a frequency proportional to the input voltage. The output pulse signal is input to the data acquisition system (DAS) for recording. The water temperatures at inlet and outlet terminals of the collector field were measured with platinum RTDs which are connected to resistance-to- voltage converters which convert the RTD resistance to a DC voltage signal (0-5 V) that are supplied to the DAS. The water flow rate through the field was measured by a vortex flow meter

H e a t i n g W a t e r I n l e t T e m p . to

D A S

t 1

1 0 0 V A C [ R T D - t o -

1 Voltage

Converter

i i i ,,

H e a t i n g W a t e r T e m p . i n l e t R T D ( T E - 1 0 4 )

Chart Recorder

t " i

Heating Water 100 VAC O u t l e t T e m p . to

D A S

+ i i I 1 0 0 V A C

2 - ~ V o l t a g e - - - i oo C o n v e r t e r ] -5 V D C i- . . . . . . - -

l , | '_ . . . . . . . . L . . . . . . . . . . . . . . . "

= I - 5 V D C I i

H e a t i n g W a t e r T e m p O u t l e t , R T D ( T E - 1 0 5 )

H o u r l y H e a t S u p p l i e d to D A S

i

I n t e g r a t o r I

1"

Programmable . . . . . , Computing

Unit

# I

[ • - J 4 - 2 0 m A

- I t II ' Legend

Inst. Heat S u p p l y to

D A S

,Ib

1-5 V D C o r 4 - 2 0 m A s i g n a l

100 V A C p o w e r s u p p l y

D A S d a t a a c q u i s i t i o n s y s t e m

Fig. 3. Measuring the heat supply to the first effect (heater).

A.M. El-Nashar / Desalination 130 (2000) 235-253 243

Table 4 Measuring instruments and their accuracy

Channel Detection point Instrument tag Output signal Instrument type Accuracy, number number %

1 Ambient temp. TE-111 1-5 V DC RTD 0.1

2 Collector outlet temp. TE-102-1 1-5 V DC RTD 0.1 3 Accumulator inlet temp. TE- 102-2 1-5 V DC RTD 0.1 4 Accumulator outlet temp. TE-102-3 1-5 V DC RTD 0.1

5 Heating water inlet temp. TE-104 1-5 V DC RTD 0.1 6 Heating water outlet temp. TE-105 1-5 V DC RTD 0.l 7 First effect temp. TE-206-1 1-5 V DC RTD 0.1

8 First preheater outlet temp. TE-203 1-5 V DC RTD 0.1 9 18th effect temp. TE-206-2 1-5 V DC RTD 0.1 10 Seawater temp. TE-202 1-5 V DC RTD 0.1 11 Empty collector header temp TE-301 mV Thermocouple 0.75

12 Empty collector absorber TE-302 mV Thermocouple 0.75 plate temp.

13 Humidity HUE- 111 1-5 V DC Human hair sensor 14 Heat collecting water flow FIT-101 l-5 V DC Vortex flow meter

15 Heating water low FIT-105 1-5 V DC Vortex flow meter

16 Product water flow FQ-205 24 V DC pulse Vortex flow meter

17 Solar radiation SQ-I 11 24 v DC pulse Pyranometer

18 Heat collected CAQ-102 24 V DC pulse Programmable computing unit

19 Heat used by evaporator CAQ-105 24V DC pulse Programmable 0.5 computing unit

20 Heat collected by Block A CAQ-101-1 24 V DC pulse Programmable 0.5 computing unit

21 Heat collected by Block F CAQ-101-2 24V DC pulse Programmable 0.5 computing unit

22 Heat collecting pump time (h) N/A On/offpulse 23 Product water pump time (h) N/A On/offpulse 24 Power consumption N/A 24 V DC pulse

5 1 plus 1 of full scale 1 plus 1 of full scale 1 plus 1 of full scale 0.5

0.5

(Yokogawa, Japan). In order to evaluate the performance o f the evaporator, temperature, f low rate and input heat rate were measured using RTD transducers (for temperature), a vortex flow meters (for f low rate) and an electronic programmable computing unit for heat rate

measurement. The measuring devices used are shown in Table 4. The output from the RTD sensors is connected to resistance-to-voltage converters which give a 1 -5V DC output signal. Measurement o f the instantaneous and hourly heat supply to the first effect is shown in Fig. 3.


I Chart 100 VAC I~ Recorder Integrator

t t I

_ _ J ' 2 2 2 . . . . . . i

Product Water Vortex Flow Meter

Fig. 4. Product water flow measurement.

t '" " "~"1 Counter

- - Hou"rl-y'~roduction to DAS

Legend

. . . . . . . . ÷ 4-20 mA signal

1 O0 VAC power supply

DAS data acquisition system

Heating water inlet and outlet temperature signals which are measured by two RTD sensors (1-5 V DC) and the heating water flow signal (4-20 mA) are supplied to a programmable computing unit which evaluates the instantaneous heat supplied to the first effect. The output signal from this computing unit is supplied to an integrator which evaluates heat input by integrating the instantaneous heat input values over hourly periods.

Both instantaneous and hourly values of distillate production were measured (see Fig. 4). A chart recorder is used for continuous recording of the instantaneous production rate and an integrator is used to integrate the instantaneous values over hourly intervals. Also a counter is used to measure the accumulated production of distillate. All measured data are supplied to a DAS (Thermodac 32, Eto Denki, Japan) which scans all the data every 15 min and prints out the data on a built-in printer. The hourly data are transferred to a PC through a RS 232 interface for processing and storage on floppy discs.

3.3. Data analysis

The measured data are shown in Table 5. These data are used to calculate the following parameters:

Table 5 Items of measured data

Measurement Name of stream or effect number

Flow rate: Heating water flow Feedwater flow Seawater flow Product water flow Heating water inlet Heating water outlet First effect vapor temperature 18th effect vapor temperature First preheater outlet water temperature Condenser SW inlet temperature Condenser SW outlet temperature Heat supplied to first effect Seawater TDS at condenser inlet

Temperature:

Heat rate Salt concentration

• overall heat transfer coefficient (OHTC) of first effect (heater)

• average OHTC of evaporator bundles in effects 2 through 18

• average OHTC of all preheaters 1 through 17 • OHTC of condenser • specific heat consumption (SHC) of

evaporator,


~ _ _ _ _ ~ O p e r a t i n g data ~ TDS in each effect input ~ [ ~ - q

Calculate temp. of II brine in 1 8th effect

Tev(18)* I"

l I ITs(18)* - T~(18)~.I <0.01 ?

Yes

I Average OHTC of effects 2-18

I(a) Each effect brine temp. I (b)Each effect vapor temp. I [

be ow demister. l(c) Each effect vapor temp. I T [ L above demister ] I

No

Yc$ Average OHTC

of preheaters

OHTC of [ condenser ]

OHTC of first I effect (heater) I

Initial ATe, of ] evaporator

t Initial AT e of I l preheaters

No

I ITp~(l)* - Tp+(l),~,~.l,z.07 ?

t Outlet temp. of each preheater

Calculate outlet temp. of No. 1 preheater

Tpr ( 1 ) *

I Specific heat -~ consumption

(sHe)

Fig. 5. Calculation procedure of evaporator performance.

Based on the assumption of equal inter-effect and equal inter-preheater temperature difference (AT), a computer program was developed to use the measured input data to evaluate the OHTCs and SHC of the evaporator [3,4]. The sequence of the calculation procedure is shown in the flow chart of Fig. 5. As can be seen from this flow chart, two iterative procedures are used: one to calculate the inter-effect temperature difference for the evaporator (ATev) and one to calculate the corresponding value for the preheaters (ATpr), both of which are average values for the evaporators (except first effect) and preheaters. The calculation program takes into consideration the variation of the brine concentration from effect to effect and its influence on the latent heat and boiling point elevation. The demister pressure drop in each effect was also considered in the calculations.

The OHTC of the first effect (heater) is calculated using the following equation:

Qh (1) Uh = Aevl x L M T D ev I

where Qh is the rate of heat transfer, Aevl is surface area of the tube bundle of the first effect (Aevl=63.1m2) and LMTDevl is the log-mean temperature difference of the first effect which is calculated from

LMTDev 1 = Thw I - Tev(1 ) - Thw 2 + Tp~(1)

in [ Th~- Tev(1) 1 (2)

The rate of heat transfer was calculated from the

246 A.M. E1-Nashar / Desalination 130 (2000) 235-253

heating water flow rate and heating water temperature difference as follows:

Qh = mhCp(Th,-Th2 ) (3)

The average OHTC of the calculated from the equation

Upr = Qpr

A pr X LMTDpr x 17

preheaters was

(4)

where Qpr is the heat transfer rate in all 17 preheaters, Apt is the surface area of each preheater (Ap, = 19.5 m 2) and LMTDpr is the log- mean temperature difference for each preheater (it is assumed that the LMTD for all preheaters are identical). For the ith preheater, we have

latent heat at the average evaporator temperature, Aev is the tube surface area of each evaporator (Aev=63.1 m 2) and LMTD~v is the log-mean temperature difference of each evaporator (it is assumed that all evaporators have the same LMTD) which is calculated from the equation

L rD = (8)

T~v(1)-Te~(18)- £ BPE(i)-£ 6Td~,(i)- £ 6Td.~t i = l i=1 i = l

17

where BPE(i) is the boiling point elevation in effect i and 8Tdemis(i ) is the temperature drop corresponding to the pressure drop, 6Pdemi,(i), across the demister and 6Td,ct(i ) is the duct inlet temperature drop corresponding to the pressure drop of vapor in the inlet of the duct between the demister and the next effect. 6Pdemis(i) is calculated from

LMTDpr(i) : [Tev(i)- Tpr(i)]-[Tev(i)- Tp r(i+ ])] In Tev(i)-rpr(i)

rev(i)_rpr(i+l ) (5)

The heat transfer rate in the 17 preheaters was calculated from the measured feedwater flow rate and the temperature difference between first preheater outlet temperature and condenser seawater outlet temperature:

f× Vg 6Paemis = xtXpgX(1-~) gc×d

(9)

where f is the friction factor, v is the vapor superficial velocity through demsiter pad, t is the demister thickness, pg is the vapor density, ~ is the demister porosity, gc is the gravitational acceleration and d is the demsiter wire diameter. The friction factor, f can be expressed in terms of the Reynolds number as

Qpr: mfCp(Tpr(1)-T~2) (6) f : 5.3Re-0.32 (10)

The average OHTC of effects 2 through 18 is calculated from an energy balance over these effects:

where the Reynolds number is defined as Re = (d Vg pg)/l.t~.

t~Pduct(i ) is calculated from the equation

Ue v : mdL- Qpr (7) 17 x S ev x LMTDev

where m d is the distillate production, L is the

L ~ D = (Tev (18)- ~1)- (Tev (18)- ~2)

In [Tev(1 g)- T~2 J

(11)

A.M. EI-Nashar / Desalination 130 (2000) 235-253 247

The temperature drop corresponding to the pressure drop was calculated from the Clausius- Clapeyron equation. The condenser OHTC was calculated from the relation

Oc U - (12)

A LMTDc

where Qo is the condenser heat transfer rate, A¢ is condenser surface area and LMTD, is the log- mean condenser temperature difference which is obtained from the following equation

LMTD c = (T~v(18)- T1)- (Tev(18)- T~2)

ha [T v(18)- Tc ] (13)

The heat transfer rate was calculated from the measured condenser flow and temperature difference as follows:

Qc = mcCp (T2- T~,) (14)

where Tot and To2 are the condenser seawater inlet and outlet temperatures, respectively. The specific heat, Cp, is calculated at the mean seawater temperature.

The specific heat consumption is calculated by dividing the distillate production, md, by the heat input to the first effect:

m d

4. Results and discussion

In order to check the validity of the SOLDES program, the actual operating data of the solar

plant during two typical months, one month during winter and one during summer, were selected as test periods for comparison with simulation results. The selected months were January 1985 and June 1985. The reason why 1985 was selected for this validation is that the plant was then in a clean condition with no evaporator tube fouling or collector vacuum level deterioration detected. Although the plant is currently in operation, its performance level is somewhat below the 1985 level.

The daily solar radiation on a tilted surface with the same tilt angle as the collector absorber plates for each of these months is shown in Fig. 6. For the month of June, the solar radiation can be seen to be high and with few fluctuations due to clear skies, while for January, large fluctuations in solar radiation are observed due to cloud cover.

A comparison between the measured and simulation values of the daily heat supplied to the accumulator for January is shown in Fig. 7. It can be seen that both measured and simulation results closely follow the fluctuations in solar radiation and that the program is clearly able to predict these fluctuations very well.

The measured and simulation values of the daily distillate production for January are shown in Fig. 8. It can be seen that both measured and simulation values follow the same trend. The simulation program predicted that the plant will be shutdown three times during this month on the 4th, 7th and 17th of January due to an insufficient amount of heat in the accumulator. This is exactly what happened: the plant was in automatic shutdown during these three days and no distillate was produced.

The measured and simulation values of the evaporator daily average specific heat consumption (SHC) for January are shown in Fig. 9. Days during which the evaporator was running continuously (no shutdown due to insufficient accumulator charge) had a specific heat consumption of about 40kcal/kg of distillate

248 A.M. El-Nashar I Desalination 130 (2000) 235-253

qPMh

m= |

1 3 8 7 9 1t t3 15 17 19 21 23 25 27 29 31

day hum ber

Fig. 6. Daily solar radiation for January and June, 1985.

6

j V . . . . . . . MmUnKI

81mulatlofll

• , w , , , , . , ' , , • , , r , • , , , , , , , , , , , ,

1 3 8 ? 9 11 13 18 17 19 21 23 28 27 29 31

day of month, January 1986

Fig. 7. Daily heat supply to accumulator- comparison of measured and simulation results for January 1985.

! ! i ! ' 1 11

1 3 6 7 9 1t 13 t6 17 19 2t 23 28 27 29 31

day of month, January 198S -~ Measured

. . . . . . . Simulation

Fig. 8. Comparison between measured and simulated distillate production, January 1985.

A.M. El-Nashar / Desalination 130 (2000) 235-253

80 I ~. • . * . , , , . ,

6 0 , ", : ,

"~ 20 0 . . . . . . . S i m u l a t i o n

1 3 6 7 9 11 13 15 17 19 21 23 26 27 29 31


Fig. 9. Daily average evaporator specific heat consumption (SHC) for January 1985.

249

26

16

ii al

J

o |

e *

"1 j,j i o

J I

0 • • , , , , • , I I . , • • , , i , , • • i , i

1 3 5 7 9 11 13 15 17 19 21 23 26 27 29 31

day of m onth. January 85 -~ Meaeured

. . . . . . . 81m ulation

Fig. 10. Evaporator daily operating time - - comparison of measured and simulation values for January 1985.

whereas days in which the evaporator was automatically shutdown due to insufficient accumulator heat demonstrated high SHC values. This is attributed to the fact that whenever an evaporator starts up from cold after an automatic shutdown, heat has to be absorbed by the evaporator to bring its temperature to normal operating temperature before it can begin production. The amount of heat which is added to the evaporator without producing any distillate results in a high SHC during days with automatic shutdown.

A comparison between the measured evaporator on-line time (hours per day) and the corresponding value from the simulation program are shown in Fig. 10 for January. Due to the fluctuating nature of solar radiation during this month, frequent evaporator shutdowns and subsequent startups took place. The number of full-day operation during this month amounts to only 17 days as can be seen from the figure. The agreement between the simulation prediction and actual plant operating is satisfactory.

The daily electrical power consumption of the


1000 •

aoo!

i _ 000

8 ,mo 200

J o

4" ~ ( 9 "=. | • w • i . • i • , • • ! w w | | ~ w i ~ i • | ~ w | J i J i |

3 5 7 0 11 13 111 17' 10 21 23 25 27 29 31


-~ Measured

. . . . . . . Sire ulation Fig. 11. Daily electricity consumption for January 1985.

Is,

4

! 1

0 4 1

~ D w

Measured

. . . . . . . 81m ulatlon

3 5 ? 9 1t 13 111 1"/ 19 21

day of month, Juno 86

ID 211 27 ~

Fig. 12. Daily heat supplied to accumulator-- comparison of measured and simulation values for June 1985.

plant for January is shown in Fig. 11, which demonstrates the close agreement between measured and simulation results. Days with 24-h evaporator operating time resulted in consumption of about 860 kWh of electrical energy. This electrical energy consumption covers the requirement of all pumps but does not include the electrical energy consumed for lighting, air- conditioning and other small demands. As can be expected, the daily electrical consumption essentially depends on the number of hours the evaporator is in operation since the power

consumption of the evaporator represents the dominant part of the total plant consumption.

The daily heat supply to the accumulator during June is shown in Fig. 12, which displays both the measured values and the values produced by the simulation program for June 1985. Two power failures occurred during this month which resulted in an interruption of the test program: one happened on June 16 at 00:41 and continued to 02:32 and the other on June 24 at 13:15 and ended at 14:54. The first interruption (June 16) did not affect the daily heat input


ili t l "0

2O

IS

10

8

0 +

Measured

. . . . . . . 8im ulatlon

, , , , , , , , , , , , , , ! • , , , , , , 0 , • , ,

3 6 7 9 11 18 18 17 19 21 23 25 27 29 day of m onth, June 11)85

Fig. 13. Daily operating time of evaporator - - comparison measurement and simulation for June 1985.

140

1201

t00

i ° 1 29

0

1

" I 1" ~ /1" I . . . * = * = - o ° - *o * .

M e s u r e d

. . . . . . . 81m ulation

3 E 7 9 11 13 16 t7 19 21 23 2!1 27 29

day of month, June 86

Fig. 14. Daily distillate production - - comparison of measurement and simulation for June 1985.

to the accumulator since it happened at night, but the second (June 24) caused a clear drop in the daily heat supplied to the accumulator since it happened during the middle of the day (see Fig. 10). A third interruption occurred on June 22 when the evaporator went through an emergency shutdown at 09:35 due an operational problem; the evaporator was subsequently started at 12:15 on the same day.

A comparison of the measured and simulation values of the daily operating time of the evaporator during June is shown in Fig. 13. The discrepancy between the measurement and simulation values for June 16, 22, 24 and 25 can be attributed to the three interruptions mentioned above, but for the other days the agreement appears to be good.

The daily distillate production for June is shown in Fig. 14, which shows a reasonably good agreement between measured and simulation values for most days with the exception of the four days (June 16, 22, 24 and 25) which were affected by the three plant interruptions.

The measured and simulation values of the daily average SHC of the evaporator for the month of June are shown in Fig. 15. It can be seen that the agreement between measured and simulation results is generally good except for days when interruption of plant operation took place.

The daily power consumption of the plant for June is displayed in Fig. 16.

A comparison of the measured values and calculated values of the total heat supply to


70 eO 50

3O -~ 20

10 0

~- Memured '

. . . . . . . 81m uletion

t 3 5 7 9 11 13 15 17 19 21 23 28 27 29


Fig. 15. Daily specific heat consumption for June 1985.

: 1000 ~1"1

0 • 1

- " Meuured

. . . . . . . Simulation , , , | , , ~ r ,

3 5 7 9 11 • , , , • , • , , • • , , , • • •

13 18 17 19 21 23 25 2"/ 29


Fig. 16. Daily electricity consumption for June 1985.

Table 6 Comparison if measured and calculated values of heat supply to accumulator and distillate production for January 1985 and June 1985

January June 1985 1985

Heat supplied to heat accumulator, kcal/month:

Simulation Measurement % error

120,100,000 115,100,000 4.3

Distilled water production, m3/month:

Simulation 2390 Measurement 2340 % error 2.1

152,400,000 153,100,000 -0.46

3340 3430 -2.6

accumulator and total distillate production during January and June is shown in Table 6. The error in predicting the monthly heat supply to the accumulator is 4.3% for January and - 0.46% for June, and the corresponding error for the distillate production is 2.1% for January and 2.6% for June.

5. Conclusions

Based on the comparisons between measured and simulation results shown above, it can be concluded that the SOLDES simulation program can be used confidently to predict the performance of solar desalination plants that use evacuated tube collectors as a heat source and MED distillation system for desalination of seawater. The program can also be used in


optimizing the operation o f existing plants or in the design o f new plants.

6. Symbo l s

A B P E - -

C o

d

f - - gc

i

L

L M T D - -

m

P Q - -

Re

S H C - -

t

T

A T - -

U

Heat transfer area, m 2

Boiling point elevation, °C Specific heat, kcal/kg °C Demister wire diameter, m Friction factor Gravitational acceleration, m/s 2 Index o f effect number Latent heat, kcal/kg Log-mean-temperature difference, °C Mass f low rate, kg/h Pressure, bar Rate o f heat transfer, kcal/h Reynolds number Specific heat consumption, kcal/kg Demister thickness, m Temperature, °C Inter-effect temperature difference, o C

Overall heat transfer coefficient, kcal/h m2 °C

Greek

p - - Density, kg/m 3 ].t - - Dynamic viscosity, kg/ms v - - Velocity, m/s

- - Demister porosity

Subscr ip ts

c - - Condenser d - - Distillate demis - - Demister duct - - Vapor duct ev - - Evaporator g - - Vapor hw - - Heating water pr - - Preheater

References

[1] ENAA and WED, Research and development cooperation on solar energy desalination plant, Final Report, 1986.

[2] A.M. EI-Nashar, Solar Energy, 44(4) (1990) 193. [3] A.M. EI-Nashar and A. Qamhiyeh, Desalination, 79

(1990) 65. [4] A.M. E1-Nashar, Desalination, 101 (1995) 231.

Documents

Validating the performance simulation program “SOLDES” using data from an operating solar desalination plant