Designing Cost-effective Seawater Reverse Osmosis System

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Renewable Energy 33 (2008) 617630

Designing cost-effective seawater reverse osmosis system

under optimal energy options

Asmerom M. Gilau, Mitchell J. Small1

Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA

Received 21 November 2006; accepted 17 March 2007

Available online 11 May 2007

Abstract

Today, three billion people around the world have no access to clean drinking water and about 1.76 billion people live in areas already

facing a high degree of water stress. This paper analyzes the cost-effectiveness of a stand alone small-scale renewable energy-powered

seawater reverse osmosis (SWRO) system for developing countries. In this paper, we have introduced a new methodology; an energy

optimization model which simulates hourly power production from renewable energy sources. Applying the model using the wind and

solar radiation conditions for Eritrea, East Africa, we have computed hourly water production for a two-stage SWRO system with a

capacity of 35 m3/day. According to our results, specific energy consumption is about 2.33 kW h/m3, which is a lower value than that

achieved in most of the previous designs. The use of a booster pump, energy recovery turbine and an appropriate membrane, allows the

specific energy consumption to be decreased by about 70% compared to less efficient design without these features. The energy recovery

turbine results in a reduction in the water cost of about 41%. Our results show that a wind-powered system is the least cost and a PV-

powered system the most expensive, with finished water costs of about 0.50 and 1.00$/m 3, respectively. By international standards, for

example, in China, these values are considered economically feasible. Detailed simulations of the RO system design, energy options, and

power, water, and life-cycle costs are presented.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Reverse osmosis; Energy recovery; Optimal energy options; Energy storage; Power cost; Water cost

1. Background

Today, about three billion people around the world have

no access to clean drinking water. According to the World

Water Council, by 2020, the world will be about 17% short

of the fresh water needed to sustain the world population.

Moreover, about 1.76 billion people live in areas already

facing a high degree of water stress[1]. Water stress is at

the top of the international agenda of critical problems, atleast as firmly as climate change [2]. As a result, the need

for desalination is increasing, even in regions where water

supply is currently adequate.

As part of one of the most affected arid areas of the

world, Eritrea, a moderate size nation located along

the northeastern coast of Africa, has been the victim of

recurrent droughts and water shortage. The problems of

water supply vary from place to place and one of the most

severe problems exists in the coastal areas and islands [3].

Thus, this case study assesses the use of renewable energy

for seawater reverse osmosis (SWRO) for the coastal

village of Beraesoli, located at the Southern Red Sea,Eritrea.

Generally, desalination processes can be categorized

into two major types: (i) phase-change/thermal; and

(ii) membrane process separation. Some of the phase-

change processes include multi-stage flash, multiple effect

boiling, vapor compression, freezing, humidification/dehu-

midification and solar stills. Membrane-based processes

include reverse osmosis (RO) and electrodialysis. Kalogir-

ou [4] has provided details on each process and all

processes are available in the market. Preferred options

ARTICLE IN PRESS

www.elsevier.com/locate/renene

0960-1481/$ - see front matter r 2007 Elsevier Ltd. All rights reserved.

doi:10.1016/j.renene.2007.03.019

Corresponding author. Tel.: +1 412268 3426; fax: +1 412268 3757.

E-mail address: [email protected] (A.M. Gilau).1H. John Heinz III Professor of Environmental Engineering, Carnegie

Mellon University, Civil & Environmental Engineering, and Engineering

& Public Policy, Pittsburgh, PA, USA.
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depend upon the need for, and availability of, energy

sources, as well as local climatic conditions. In Eritrea, for

example, in 1992, Gilau [5] experimented with solar still

desalination in the coastal city of Massawa, Eritrea. That

study reported that, in the month of September, where the

temperature usually reaches about 36 1C, using a glass area

(upper roof area) of 5.27 m2

, about 7 L of desalinated waterper day could be collected. Noted above, this study will

focus renewable energy powered SWRO.

Seawater desalination is an energy-intensive process

[6,7]. Most of the available large-scale desalination plants

around the world are powered by fossil fuel. Due to the

concerns regarding global warming and increasing fuel

costs, alternative energy sources have been proposed for

desalination purposes. For example, the International

Atomic Energy Agency (IAEA) has proposed the use

of nuclear power for large-scale desalination plants [7].

In addition, the use of renewable energy sources for

small-scale desalination plants is emerging. Autonomous

wind-powered seawater RO potentials have been studied

[6,8] and pilot projects are in progress [7]. However,

the application of renewable energy for desalination

has not yet reached sufficient maturity to be applied

widely. Moreover, most of the proposed designs are

connected to the conventional power grids [7,9]. Thus,

the main objective of this research is to design a cost-

effective reverse osmosis system, which considers both

non-renewable and renewable power options, and deter-

mines the optimal mix of energy options. This paper

introduces a new methodology for energy optimization for

an SWRO system.

In the analysis, two major models are applied, includingthe Reverse Osmosis System Analysis (ROSA) model, a

sophisticated RO design program that predicts the

performance of membranes in user-specified systems [10],

and the hybrid optimization model for electric renewables

(HOMER), which is an optimization model for hybrid as

well as stand-alone power systems[11]. Life cycle analyses

are performed to examine the performance of the system,

determine water costs, and undertake comparative analysis

of different power supply options.

2. Situation analysis

2.1. Water demand

Recent studies conduced by the Swiss Federal Institute

for Environmental Science and Technology [1] indicate

that East African countries have renewable freshwater

resources below the calculated threshold of 1500 m3 per

capita per year. Eritrea is already in a condition of water

deficit. According to recent studies, in the coastal parts of

the country, water demand is 116 m3/household/year[12].

Thus, for the Berasoel village of 108 households, we are

assuming an average water demand of 35 m3/day and

13,000 m3/year.

2.2. Energy supply

In Eritrea, there is a strong potential for wind powered

electricity generation [13] and sunshine is abundant. The

Southeast coast of Eritrea has as much as 100200 km of 6

and 7 wind classes. At these sites, wind turbines may

operate at a 4060% capacity factor [14], which impliesthat the wind potential ranges from excellent to exceptional

[15], and could be potentially used for commercial and

industrial purposes as well. The average annual wind speed

and solar radiation are about 6.8 m/s and 6.8 kW h/m2,

respectively.

3. Modeling SWRO design and optimal energy options

3.1. SWRO design considerations

3.1.1. Model description

ROSA 6.0.1 software is the latest version, used in theanalysis to determine the performance of a membrane and

energy requirements for desalination. The use of the model

is influenced by the need to design a technically feasible RO

system. The ROSA model has been used for designing

desalination plants in different parts of the world [1621].

We have extended the application of the model in creating

an operating window for an RO system that could operate

under intermittent power supply. This is done by running

the model multiple times under different water flow rates

and pressures. The main inputs to the model include the

amount of feed water and its chemical characteristics, feed

water flow rate, feed water and concentrate feed pressures,

temperature and pH. Then, a configuration of the number

of membranes, pressure vessels, and type of membrane,

and feed and booster pumps is determined. After perform-

ing calculations, the model provides the amount of water

produced and the energy required. The energy required to

produce an intended amount of drinking water with

acceptable water quality is then determined by running

the model multiple times. Booster pumps and an energy

recovery turbine can also be included in the design.

3.1.2. RO system design and energy consumption

Using ROSA, we determined several RO design options

capable of producing 35 m3/day potable water. After

examining several design alternatives, our preferred design

is a two-stage design with three membrane elements in each

stage (Fig. 1). The reason for choosing a two-stage system

is that this enables an increased water productivity by

applying a booster pump that recovers a significant amount

of energy. The type of the membrane used in the analysis is

FILMTEC SW30HRLE-400. The membrane is widely

used, has a high flow rate capacity (37.2 m3/day), high

boron rejection ability (91%) and resists up to about 83 bar

of pressure. Moreover, the membrane is designed to

properly function under intermittent energy supply, resists

fouling, and enables effective cleaning[22].

ARTICLE IN PRESS

A.M. Gilau, M.J. Small / Renewable Energy 33 (2008) 617630618


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In RO desalination systems, energy is a major con-

sideration. Power consumption by the system includes

power for seawater pumping, high-pressure pumping, i.e. a

booster, and chemical treatment. The total power require-

ment is calculated using Eq. (1) [23]:

Pwn QnPrn

En , (1)

where Pwn (kW) is the power consumed by feed, low-

pressure, high-pressure and chemical water treatment

pumps,Qn (m3/s) the rates of feed water (Q1), fresh water

production (Q5+Q6), boosted water (Q3), Prn (kPa) the

feed pressure (Pr1), boosted pressure (Pr3), rejection

pressure (Pr2 and Pr4); and En (net efficiency of feedpump) Ep (pump efficiency) En (motor efficiency) for

the high-pressure pump (booster) and energy recovery

turbine.

According to Darwish et al. [23], the low-pressure pump

consumes the highest energy (Pw1), and the rest constitutes

about 20% of the LP pump. The power required for the

systems LP pump, at 10 m3/h feed water flow rate, 45 bar

pressure, and 0.85 pump efficiency, is about 14.7 kW. An

additional 2.9 kW is needed for the booster, feed water,

chemical treatment and other pumps, which is about 20%

of the LP power requirement. Thus, the total power

required for the RO system design is about 17.6 kW. Using

ROSA software, we have obtained a similar result,

17.2 kW. The specific work done is about 3.92 kW h/m3

potable water produced. Without a booster pump, the

system requires about 7.87 kW h/m3, and its water quality

deteriorates from 270 to 800 ppm total dissolved solids.

Moreover, if the booster pump is not applied, water

production in the second stage could decrease by about

33% per hour, i.e. from 2.1 to 1.4 m3/h. Thus, in terms of

water production, water quality, and energy recovery, a

two-stage RO design is preferable. The system design has

an average conversion factor of 55% (relation between

product water flow and feed water flow), producing about

4.4m3/h of potable water.

3.1.3. Performance prediction

In designing the SWRO system that uses intermittent

energy sources, it is very important to design an RO system

that can operate under broad operational windows. The

main thresholds of the operational window include the

maximum feed pressure (determined by the membrane

mechanical resistance); maximum brine flow rate (should

not be exceeded to avoid membrane deterioration);

minimum brine flow rate (should be maintained to avoid

precipitation and consequent membrane fouling); and

maximum product concentration (if the applied pressure

is less than a determined value, the permeate concentration

will be too high)[8].

Using chemical characteristics of water of the study area[24], and varying the values of the operational window

thresholds, we have run the model several times. According

to the results of the analysis, at 251C, the maximum

allowable pressure, maximum brine flow rate, minimum feed

flow rate, and minimum pressure of our design are about

50bar, 16m3/h, 7m3/h, and 30 bar, respectively (Fig. 2a).

This design allows the production of potable water with

an average water quality of about 500 ppm total dissolved

solids or less, which is the World Health Organization

(WHO)s water quality acceptable standard. Likewise, in

order to operate under this operational window, the energy

supply or pumping power should not be less than 7 kW and

not exceed 26kW (Fig. 2b). This means that, without

interrupting the operation of the system, it can operate at

as low as 7 kW and as high as 26 kW power supply, which

is a wide operating window. This flexibility is one of the

aspects that could potentially make renewable energy

resources for SWRO systems more attractive.

The average conversion factor of the system, at 25 1C, is

about 55%. Carta et al.[7]indicated that for an increase of

1 1C, water production increases by about 4%. Thus, since

the climatic conditions of the study area are very hot, with

average monthly temperatures varying from 26.5 to 35.5 1C

[25], it is expected that most of the time of the year, the

conversion factor could reach as high as 70%.

ARTICLE IN PRESS

High pressure

pump (Booster)

Low pressure

pump

Product

tank

PostTreatment

Product/

permeate

water

Pretreatment

1st stage

membranes

2nd stagemembranes

Feed water

from Red Sea

Seawater Reverse Osmosis Desalination System for Beraso'ele Village, Southern Red Sea, Eritrea

Energy

Recovery

Turbine

Pr4Q4

Q6

Q7

Q3

Q2

Q5

Q1

Pr2

Pw3

Pw2

Pw1

Pr1

Pr3

Concentrate

Fig. 1. Schematic two-stage RO system for the village of Beraesoli, Southeastern Red Sea, Eritrea.

A.M. Gilau, M.J. Small / Renewable Energy 33 (2008) 617630 619


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3.1.4. Energy recovery

Energy recovery should be considered if brine exits the

system at 300 psig or more, and if system recovery is less

than 80% [26]. Since the brine rejection pressure of our

design is well above 300 psig, with the design pressure

760 psi (52.82bar), the potential for energy recovery is very

high. For example, using an energy recovery turbine with

an efficiency of 0.85, at concentrate pressure of 52.82 bar,

and a concentrate water flow of 5.6 m3/h, about 7 kW

(Eq. (2)) of energy could be recovered. Thus, our design

can potentially reduce power consumption by nearly half,

from 15 kW to about 8 kW.

Pwrn Qn Prn Et, (2)

where Et is the turbine efficiency, Prn (kPa) is the feed

pressure, andQn (m3/s) is the flow rate of the feed brine.

The type of energy recovery turbine under consideration

is the pressure exchange (PX) turbine, PX45s [27]. Using

this energy recovery device, net energy consumption could

be reduced from 17.23 to 10.25 kW, and specific energy

consumption from 3.92 to 2.33 kW h/m3, assuming 45 bar

feed pressure and 10 m3/s feed flow rate. This is about a

40% energy recovery, and it is a substantial energy

recovery opportunity for a small-scale SWRO system.

Therefore, using a booster pump and energy recovery

turbine, energy consumption can be decreased from

about 7.87 kW h/m3 (at maximum flow rate of 16m3/s,

i.e. during high wind speed periods) to about 2.33 kW h/m3.

A specific energy consumption of an RO system in Kuwait

and in the Caribbean (Curacao) islands has been reported

to be about 4.52 and 3.15kWh/m3, respectively, for

5700m3/day desalination water capacity [23]. Compared

with these results, our design results are low, though

compatible.

Thus, depending on the feed flow rate and pressure

exerted, our operating window of the system can poten-

tially recover anywhere from 4 to 12 kW. The RO system is

expected to operate under a semi-instantaneous base load

of 17 kW. Thus, assuming a feed pressure of 45 bar, a

boosting pressure of 10 bar, and a feed water flow rate of

10 m3/h, the system can recover about 47 kW/h (Fig. 3).

Moreover, increasing the feed water flow rate at low

pressure could substantially increase energy recovery and

water production. In this regard, within the operational

window of the system, any other points of operation could

be selected as an initial point of operation.

ARTICLE IN PRESS

Water quality and flowrate threshholds of the SWRO design

0

100

200

300

400

500

600

700

800

6 7 8 9 10 11 12 13 14 15 16 17

Feedwater flow rate (m3/h)

WaterQuality(ppm

oftotalTDS)

35 bar

40 bar45 bar50 bar

30 bar

6 7 8 9 10 11 12 13 14 15 16 17

Feedwater flow rate (m3/h)

Power Thresholds for The SWRO design

5

10

15

20

25

30

PumpingPower(kW)

50 bar

45 bar40 bar

35 bar

30 bar

Fig. 2. (a) Water quality and feed water flow rate and (b) power thresholds of the SWRO system.



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3.2. Modeling optimal energy options

The main objective of this analysis is to determine

cost-effective and feasible energy options to produce the

required amount of water using the SWRO design

discussed in the previous section. The types of energy

options under consideration include stand alone as well as

hybrid energy sources of wind, photovoltaic (PV) cells, and

diesel. To determine least cost energy options, we used an

optimization model, HOMER, developed by the National

Renewable Energy Laboratory (NREL).

3.2.1. Model descriptionHOMER evaluates different energy options by simulat-

ing hourly energy flows for complex hybrid as well as stand

alone power systems. The model simulates power system

configurations and optimizes for lifecycle costs. It simulates

the operation of a system by making energy balance

calculations for each of the 8760 h of the year. For each

hour, the model compares the electric load in the hour

to the energy that the system can supply in that hour.

In the presence of energy storage devices, the model

determines when to discharge and charge electricity. The

model also estimates the lifecycle cost of the system

based on capital, replacement, operation and maintenance,

and fuel costs of each component including PV cells,

wind turbines, batteries, generators, and inverters. After

simulating the system configurations, the model displays

a list of feasible systems, sorted by lifecycle cost,

based on their net present values (NPVs). Then, based

on the results, one may choose from among the least

cost and feasible systems. However, all the least cost

systems are not necessarily feasible. Thus, reliability and

other issues need to be considered in choosing the optimal

energy option. The HOMER model has been used

for different household electrification feasibility studies

[2833]. However, HOMER has not yet been used for the

design of a power system for SWRO.

3.2.2. Determining SWRO base loadIn RO desalination systems, energy is a major con-

sideration. Depending on the capacity of the RO systems,

estimates of energy use range from 2 to 10 kW h/m3 of

water produced [34]. The average base load for our RO

system is 17 kW/h with a specific work done of about

2.33 kW h/m3. In order to make the assumptions of SWRO

energy demands more realistic, 5% and 2% noises are

added in the model for daily and hourly loads, respectively.

The challenge is optimizing to meet the required constant

load using highly variable power supply systems.

In order to solve the challenge, we have designed the

SWRO system to operate anywhere between 7 and 27 kW,which are the allowable operating power thresholds. Any

power below and above about 7 and 27 kW could

ultimately be considered as excess power. Thus, we are

trying to optimize the regular SWRO power load under an

irregular power supply, which makes the analysis complex,

especially when wind energy is considered. Based on the

base load power requirement, different energy models are

simulated with different base load configurations, with and

without energy storage devices. An energy dispatch

strategy is designed to meet the required base load of the

RO system, depending on the type of energy option

selected.

3.2.3. Wind power

3.2.3.1. Implications of wind speed variations. The aver-

age wind speed of the study area is 6.8 m/s[3]. Wind speed

distributions can typically be described in terms of the

Weibull distribution [6]. According to Rosen [35], the

shape parameter for the Southern Red Sea area, particu-

larly Port Assab, is k 2.4. The standard Weibull shape

parameter is k 2.5. Using the Danish Industry Wind

Association power calculator [36], at 25 1C, 10 m above

sea level, 101.21 kPa atmospheric pressure, 1.22 kg/m3

air density and a 2.4 shape parameter, the scale parameter

is c 7.67m/s. Thus, using Eq. (3), the probability

ARTICLE IN PRESS

Initial energy consumption, potential energy recovery, and net energyconsumption at 45bar feed pressure of the RO system

0

5

10

15

20

25

30

6 7 8 9 10 11 12 13 14 15 16 17

Feed water (m3/hr)

Energyconsumption/recovery(kW) Energy recovery(kW)

Initial energy consumption(kW)Net energy consumption(kW)

Fig. 3. Energy recovery potential of the RO system at 45 bar feed pressure.



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distribution function of the wind speed is computed. The

probability density function, fv(v), is given by

fvv k

c

v

c

k1exp

v

c

k , (3)

where v is the wind speed in m/s, kthe shape parameter,

and c the scale parameter (m/s).

The average wind speed is calculated as

Ev cG 11

k

, (4)

where G is the gamma function.

The mean wind speed is thus computed to be 6.8 m/s.

However, wind speeds throughout the seasons are irregu-

lar, and the average wind speed exhibits high seasonalvariation. According to the US Navy Climatic Study of the

Red Sea report conducted in 1982 [35], for 7 months

(OctoberApril), mean wind speeds are between 6 and

10 m/s, and the remaining months (MaySeptember), mean

wind speeds are between 3 and 5 m/s. Assuming an average

wind speed of 8 m/s for season 1 (OctoberApril) and 4 m/s

for season 2 (MaySeptember), the scale parameters are 9

and 4.5 m/s, respectively. The Weibull probability density

function of wind speeds for the two seasons are shown in

Fig. 4. A very high wind speed in one season and a very low

wind speed in the other season make the modeling process

more complex. That is, the irregularity of seasonal wind

speed makes the system more complex to optimize withoutexpecting very high excess electricity during the high wind

speed season, and significant use of energy storage systems

during the low-wind-speed season. Most studies indicate

that to overcome power shortages during the low-wind-

speed seasons, a large number of wind turbines should be

installed[37]. This is one of the issues that we address in

this analysis.

3.2.3.2. Model input. In this analysis, we assume that the

RO system will be powered by a stand-alone wind turbine.

In this model, a 17 kW base load is considered in order to

produce potable water at about 2.33kW h/m3. This

approach allows capturing all wind energy outputs that

are produced whenever the wind is blowing. Taking into

consideration the above-mentioned seasonal wind speedand energy variations, we have considered monthly average

wind speeds, with an annual average wind speed of 6.8 m/s.

The monthly average wind speeds are then used to simulate

hourly wind speeds for the 8760 h of a year. Using a FL2

30 kW wind turbine, the results of the simulation are shown

inFig. 5.

The results indicate that the effective annual number of

hours with adequate wind power for the SWRO operation

is more than 4000 h. Thus, the wind turbine seems to be a

good candidate for the analysis. However, in doing so,

excess electricity is expected, especially during the high

wind speed season. To complete the cost and performance

analysis of the FL 30 wind turbine, we assume a lifetime of

20 years [38,39], a capital cost of $130,000, annual

operation and maintenance costs of $3900 (2.5% of capital

cost) [40], and a replacement cost of 85% of the capital

cost.

3.2.3.3. Results of the analysis. According to the optimi-

zation results, the least cost feasible wind energy option

consists of 1 FL 30 kW wind turbine, 10 batteries, and 10

converters. The cost of this option is about $0.17/kW h

with a capacity shortage of about 51%. This means that

our RO system will be functional at full capacity for about

4000 h of the year, producing about 30,000 m3/year. Sincemost of the high wind speeds are during the day, the system

operates for more than 812 h/day for the whole year to

yield the projected 4000 h/year. In order to deal with water

production increases during high temperature and wind

speed seasons, there might be a need to build a water

storage tank in order to store water to be used during low-

wind-speed periods.

It should be noted that the use of a battery as an energy

storage device is not solely meant to increase energy

ARTICLE IN PRESS

Seasonal variation of wind speed

0.00

0.05

0.10

0.15

0.20

0.25

0 4 8 10 12 14 16 18 20

Wind speed (m/s)

Probability

Density

Season 2 (May toSeptember)Annual distribution

2 6

Season 1(Oct.to April)

Fig. 4. Seasonal variations of wind speed Weibull distribution of the study area.

2Fuhrla nder (FL) 30 kW is a type of 30 kW wind turbine developed by

Fuhrla nder AG.http://www.fuhrlaender.de/start.php.

http://www.fuhrlaender.de/start.phphttp://www.fuhrlaender.de/start.php


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production. The primary objective is to keep the power

supply at a semi-instantaneous condition (Fig. 6) so that

the RO system could produce water continuously. When

wind power is starting to decrease, electricity is dispatched

accordingly to meet the demand. This could also poten-

tially minimize the deterioration of membranes. According

to the results of the model, the lowest wind speeds occur

from midnight up to early in the morning. Thus, there is a

possibility of turning off the RO system or adjusting it to

function with battery power during this time interval.

Annual wind power output, base load, and water produc-

tion scenarios are shown in Fig. 7.

3.2.4. Photovoltaic (PV) power

3.2.4.1. Model input. This analysis assumes simulating a

stand-alone PV power system without applying a sunshine

tracking system. Using a 17 kW base load for about 8 h/day

throughout the year and daily solar radiation at Beraesoli

(131300N and 421430E), the performance of a PV-powered

system has been analyzed. In the analysis, we assume a 25-

year lifetime of the PV cells, $4500/kW capital cost [41],

and $3800 replacement cost.

It is important to realize that the assumptions of RO

base load for the wind powered system, which is

continuous for 24 h (Fig. 7), is different from the PV

powered RO system, which is configured to operate during

the day only. The main reason is, unlike daily predictions

of sunshine, for wind power it is very difficult to predict

when the wind will be blowing. Therefore, in the case of the

wind powered configuration, we have considered a

continuous power demand in order to capture all available

wind energy whenever the wind speed is high. In the case of

ARTICLE IN PRESS

-15

-1

-5

0

5

10

15

20

25

30

35

40

0 50 100 150 200 250 300 350 400

Base Load (kW)

Wind Power (kW)

Water Produced(W+B)(m3)

Battery Power Dispatch(kW)

Fig. 6. Base load, wind power production, battery power dispatched, and water production simulated for the first.

Fig. 5. Daily wind power outputs and the required load of FL 30 kW wind turbines.



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a PV powered system, the optimal load is configured to

operate during the day assuming that the energy load is

only required for 810 h of the day. Thus, this configura-

tion assumes operation during the day only, producing the

intended amount of water.

3.2.4.2. Results of the analysis. The analysis considers a

PV power system with and without battery energy storage.

The result of the analysis shows that unmet load is

substantially decreased when battery energy storage is

applied. Using energy storage, unmet capacity shortage

is decreased from 23% to 0%. Thus, in terms of attaining a

steady power supply for about 8 h/day, the PV with battery

energy storage system might be a good candidate compared

with the PV model without battery. Compared with the

cost of electricity using wind power (0.17$/kW h), the cost

of electricity for the PV system with battery energy storage

is more than double, about 0.40$/kW h.

The RO system base load, PV power produced and

battery power dispatched for the first 2 weeks (330 h) of

January are shown in Fig. 8. According to the simulated

results, most of the time, the PV power is above or equal to

the base load. Since the RO system can operate at up to

27 kW, all the electricity could be used producing as high as

8 m3/h. Under this scenario, on average water production is

about 5 m3/h. Without battery storage, annual water

production is about 11,600 m3 and with battery storage,

about 14,000 m3. Thus, PV power with battery storage

increases water production by about 20%.Fig. 9shows the

annual load, power and water produced. From this

analysis, it can be concluded that the PV-battery config-

uration is an appropriate configuration option, enough to

achieve daily water needs without requiring investment in a

large water storage tank.

3.2.5. Diesel power

3.2.5.1. Model input. In this model a 50 kW diesel

generator is considered. The estimated capital and replace-

ment costs are $14,000, and $10,000, respectively, the

O&M cost is $1.5/h, and the diesel cost in Eritrea is

assumed to be $1.00/l (2006 Eritrean diesel price). The

lifetime of the generator is 20,000 h. In Eritrea, the cost of

electricity produced by a diesel generator is at least twice as

expensive as grid electricity[42]. This is mainly due to the

high diesel transporting cost to remote areas, high

maintenance costs, and high fuel consumption. Despite

ARTICLE IN PRESS

RO Base load, wind power and water production

-5

0

5

10

15

20

25

30

35

40

0 1000 2000 3000 4000 5000 6000 7000 8000

Time for one year (hr)

Power(kW)andWaterProduction(m3/hr)

Wind Power (kW)Base Load (kW)Water Produced(W+B) (m3)

Base Load

Water Produced

Wind Power

Fig. 7. Annual wind power, base load, and water production scenarios.

Baseload of RO, PV Power, Battey Power Storage and Dispatch and Water Production

-15

-10

-5

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 240 250 260 270 280 290 300 310 320 330 340

Time (hr)

Poweroutput(kW)&

WaterProduction(m3/hr)

RO Baseload kWPV Power kWWater ProducedBattery Power kW

Fig. 8. Simulated RO base load for the first 2 weeks of the month of January, PV power produced.



9/14

such high costs, users tend to give high value to the power

generated by diesel generator as it is flexible to meet the

energy needs of both domestic and income generatingactivities.

3.2.5.2. Results of the analysis. According to the results

of the analysis, a 25 kW diesel generator is enough to meet

the intended water demand, operating for about 8 h/day.

The lowest electricity cost for a feasible option using a

diesel generator is about 0.39$/kW h, similar to the result

for the PV system.

3.2.6. Integrated power system

This option simulates the combination of the three

options such as wind, PV and diesel energy sources with a

battery as energy storage. In this scenario, the challenge is

the assumptions made in choosing the base load config-

urations. In the case of stand-alone power systems, it is

possible to configure the base load according to the

behavior of the energy sources. In an integrated case, we

assume that the base load is the same as the wind energy

configuration, 24 h/day and 8760 h/year. Then, based on

the simulation results, in addition to least cost options, we

determine the most feasible options.

In an integrated approach, whenever wind energy is

available, it is the cheapest option. Under this scenario, the

cost of electricity of the feasible options ranges from 0.175

to 0.183$/kW h, for stand alone wind turbine with battery,

and wind turbine and PV with battery (W_PV_B),

respectively. A 5 kW PV, 30 kW wind turbine, and 10 kW

battery are one of the least cost (0.183$/kW h) choices.Moreover, it seems that whenever the wind speed is high

usually during the day, PV energy is also high. Thus,

assuming that water demand will increase, this option

could become more attractive. Wind energy with a battery

is the cheapest option ($0.175/kW h), and it is a feasible

choice with the lowest capacity shortage of about 48%.

While either of the options could be feasible, the PVwind-

battery system might be more reliable for the SWRO

system.

4. Discussion

4.1. Energy options

Based on the renewable energy potential of the study

area, both wind and PV energy resources are feasible. With

respect to power cost, the optimization model does not

incorporate price uncertainty. All costs are simulated based

on the NPV. According to the optimization model, at

about a 6% interest rate, the PV-powered RO system is

more expensive than the wind powered RO system, with

the costs about 0.399 and 0.175$/kW h, respectively

(Table 1). However, the results of our sensitivity analysis

show that PV could be competitive with wind energy as the

interest rate increases. As a result of changes in interest

ARTICLE IN PRESS

RO Base load, PV Power Produced and Water Produced for one year

0

5

10

15

20

25

30

35

40

0 1000 2000 3000 4000 5000 6000 7000 8000

Time (hr)

BaseloadandPVPowe

r(kW),andWater

Produced(m3/hr)

PV Power kW

Water Produced

Water Produced

RO Baseload

PV Power

RO Baseload kW

Fig. 9. Annual RO base load, PV power, and water production.

Table 1

Summary of power and water costs for different energy options

Energy options

W_B (1) W_PV_B (2) W_D_B (3) W_PV_D_B (4) W_D (5) W_PV_D (6) PV (7) D (8) PV_B (9)

Power cost ($/kW h) 0.18 0.18 0.26 0.27 0.29 0.30 0.30 0.40 0.40

Water cost ($/m3) 0.53 0.57 0.74 0.74 0.79 0.82 0.82 1.04 1.05

Note: W_B: wind and battery; W_PV_B: wind, photovoltaic, and battery; W_D_B: wind diesel battery; W_PV_D_B: wind, photovoltaic, diesel, and

battery; W_D: wind and diesel; W_PV_D: wind, photovoltaic, and diesel; PV: photovoltaic; D: diesel only; and PV_B: photovoltaic and battery.



10/14

rates, production, and other factors, energy prices arevolatile, especially for diesel. Thus, assuming about 25%

error, we have calculated the maximum and minimum

power costs (Fig. 10). According to the results, the

minimum and maximum wind power costs are about 0.13

and 0.22$/kWh, respectively. Likewise, for PV power, the

minimum and maximum costs are about 0.30 and 0.50$/

kW h, respectively. In either case, wind power is cheaper

than the PV power. In terms of reliability, for this

particular area of study, it is likely that PV will be more

reliable than wind. This is due to the fact that the period of

availability of sunshine is more predictable than the wind

speed. As a result, it is easier to schedule the operation of

PV-powered RO systems than a wind-powered system.

4.2. Water cost

In the last 20 years, the water cost from SWRO has

dramatically decreased from about $2.8/m3 to $1.5/m3.

This has been attributed to the use of energy recovery

devices, and efficient membranes that allow rejection of salt

at low pressure[43]. Water costs are analyzed based on the

overall life cycle of the RO system, which includes the

capital costs of the initial membrane, pressure vessel,

pumps, energy recovery turbine, and operational and

maintenance costs for membrane replacement and electri-

city. Based on the schematic two-stage RO system design

shown inFig. 1which is analyzed in detail using the ROSA

software package, we have extended the Element Value

Analysis (EVA) model developed by FilmTec Corporation

[22] to determine the life cost of the RO system. The RO

system has two pressure vessels and six system elements, in

which the costs of per vessel and per element (FILMTEC

SW30HRLE-400) are $1000 and $750, respectively. The

total cost of the vessels and system elements is about

$6,500. The capital costs of a pressure exchange (PX)

turbine, PX45s pumps and miscellaneous costs are $12,000,

$5000, and $3000, respectively. We have also assumed a

membrane replacement price of about $750, which gives areplacement cost of $585, assuming a 13% replacement

rate per year per membrane. Based on these assumptions,

the total capital cost of the seawater reverse osmosis system

excluding the cost of the power system is estimated to be

about $27,000. Energy costs are determined using the

HOMER model in Section 3 as shown also in Table 1.

Assuming that the operation period of the system is about

10 years and a 10% interest rate, the net present cost of the

renewable energy powered seawater reverse osmosis system

ranges from $126,000 for wind with energy storage (W_B),

to $250,000 for PV with energy storage (PV).

The power costs (Table 1) are the results of the

optimization model for the selected energy options. With

the assumed 10-year lifetime of the RO system and 10%

interest rate, water costs are computed as shown inTable 1.

According to the results of the analysis, energy expenses

per cubic meter of water produced range from 0.53$/m3 for

wind powered, to 1.05$/m3 for the PV-powered RO system.

PV powered desalination is more expensive than wind

powered by about a factor of two. Recent studies indicate

that today a cost of $1/m3 for seawater desalination would

be feasible and competitive [44]. With an estimated 25%

water cost error, water costs for each option are shown in

Fig. 11.

According to the results, power cost constitutes thehighest proportion of the total costs. Regardless of the type

of energy option chosen, energy expenses are 80% of the

total expenses. The proportion of the expense for the other

costs constitutes less than 20%, including the initial

membrane and pressure vessel (3%), the capital cost of

the energy recovery turbine, pumps and miscellaneous

(8%), and the membrane replacement cost (3%).

4.3. Water productivity

According to the model, wind powered (Option 1) and

PV powered (Option 9) RO systems could produce about

ARTICLE IN PRESS

Power Costs of Different Energy Options

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0 2 3 4 5 6 7 8 9 10

Energy Options

Powercost($

/kWh)

1

Fig. 10. Power costs with 25% error.



11/14

30,000 and 15,000 m3/year, respectively. PV produces

about the exact demand at high price and wind produces

more than double of the required amount at the lowest

price. Wind powered water production for the months of

November through March is predicted to be about

4000 m3/month, and for the months of April through

October, about 1600m3/month (Fig. 12). The PV-powered

RO system produces a constant amount of water, 1200 m3/

month. Based on the potential of water productivity and

water cost, the wind-powered RO system is indicated to be

the best option.

4.4. Implications of battery storage

We have tried to compare the implications of energy

storage in wind and PV-powered systems. For wind and PV

systems with energy storage, the average water production

increases by about 6% and 11%, respectively (Fig. 13).

This implies that, using our model, the use of battery

storage in an RO system is more important for the PV-

powered than the wind-powered RO system. Moreover, in

addition to increasing the water production at a minimum

incremental cost of about 6% for battery in wind and 2%

for battery in PV, it helps to decrease the intermittency of

the treated water flow.

4.5. Implication of energy recovery

An attempt has also been made to compare the impact of

energy cost with and without the energy recovery system

(Fig. 14). The results show that using a pressure exchange

(PX) 45s energy recovery turbine, the energy expenses for

the wind powered option, for example, could be reduced

by about 41% from 0.69 to 0.41$/m3. However, it should

ARTICLE IN PRESS

Water Costs at different Energy Options

0.00

0.25

0.50

0.75

1.00

1.25

1.50

Energy Options

Watercos

ts($/m3)

0 2 3 4 5 6 7 8 9 101

Fig. 11. Water costs with 25% error. (Note: the number of the energy options corresponds to the types of energy options shown in Table 1.)

PV and Wind Powered RO Systems' Monthly Water Production

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Months

WaterProduction(m3/month)

PV Powered Wind Powered

Janu

ary

Febr

auary

March

April

May

June Ju

ly

Augu

st

Septembe

r

Octobe

r

Novembe

r

Decembe

r

Fig. 12. Monthly PV- and wind-powered water production.



12/14

be noted that the PX 45 turbine has some limitations

with respect to its use for the water flow rates considered.

An upgraded PX 45 turbine to cover all flow rates would

be critical and important for successful and wide

application. The capital cost of a PX 45s energy recovery

turbine, which is about $12,000, could be paid back within

a year.

5. Conclusion

This paper has analyzed the performance of a renewable

energy powered small-scale seawater reverse osmosis

(SWRO) system particularly in terms of water productivity

and energy cost. The RO system has been designed with a

flexible operating system capable of operating under

intermittent energy supply. Results of our analysis show

that the contribution of the booster pump and energy

recovery is not negligible in increasing water productivity

and decreasing energy consumption per cubic meter

of water produced. Our results show that using the

available technologies, it is possible now to produce

water at about 2.33 kW h/m3, an amount that is below

previous estimates [14,45]. Using a booster pump and

energy recovery turbine, energy consumption can be

decreased from about 7.87 kW h/m3 to about 2.33 kW h/m3.

The results indicate that wind powered water production

(0.50$/m3) is economically feasible. According to [46], in

China, 1.0$/m3 desalinated water is considered as economic-

ally feasible. This implies that even a PV powered system

could be competitive, and much of the low latitude world,

with consistent solar radiation, could benefit. Generally, in

Eritrea, water production and tariff costs are about $0.30/m3

ARTICLE IN PRESS

Percentage of water production Increase using battery storage system

0%

2%

4%

6%

8%

10%

12%

14%

WaterProductionPerce

ntageIncrease PV Powered Wind Powered

Months

January

Febr

auary

March

April

May

June Ju

ly

Augu

st

Septembe

r

Octobe

r

Novembe

r

Decembe

r

Fig. 13. Water productivity and energy storage.

$0.0

$0.1

$0.2

$0.3

$0.4$0.5

$0.6

$0.7

$0.8

$0.9

$1.0

$1.1

$1.2

$1.3

$1.4

$1.5

$1.6

W_B W_PV_B W_D W_D_B W_PV_D_B W_PV_D D PV_B PV

Energy options

$

perm

3ofwater

Energy expenses withER ($/m3)

Energy expenseswithout ER($/m3)

Energy Expense with and without the energy recovery(ER) system under different energy options

Fig. 14. Energy cost with and without energy recovery.



13/14

and $0.43/m3, respectively. This implies that the wind-

powered system could be competitive.

Our energy optimization model for RO desalination

system is a first step toward facilitating its wider applica-

tion. Moreover, the energy optimization model, which has

not been used before for such a purpose, provides a useful

and relatively straight forward approach, particularly forsimulating hourly renewable energy production and con-

sequently synchronizing this with the energy load in order

to operate under the wide operating system parameters of

the RO plant. However, in order to determine the

robustness of the methodology, we believe that the model

requires further testing, especially for the design of an

actual SWRO system. With current results, we recommend

that, since the availability of energy recovery systems

capable of operating under highly variable conditions is

limited, for higher water productivity and continuous

energy recovery, it is important to operate above 10 m3/h

feed water at low pressures between 30 and 45 bar. The

lower the pressure, the lower the energy required for

producing a limited quantity of water. In contrast, if a

greater rate of water production is needed, then a higher

energy/higher pressure design is required.

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