**2. The modelling exercise**

The modelling exercise was conducted in 3 main stages as shown in **Figure 2**.

#### **2.1. Stage 1**

**1. Introduction**

178 Desalination and Water Treatment

This chapter:

2011.

use of 50,000 people.

between 1981 and 2010 is around 600 mm.

**Figure 1.** Rainfall map of Eritrea.

**1.1. The location**

Renewable energy is currently considered by many to only have viability for a small portion

This intermittency potentially undermines the environmental and energy security advantages

• Sets out the investigation of the use of renewable energy sources in such a way that they could be justified for use without reliance on conventional energy sources and to stand

• Is a continuation of research initially conducted in 2011 and subsequently published in 2014 [1], to reflect the impact of changes to diesel fuel and solar photovoltaic prices since

The scenario used to investigate the technical and financial viability of renewable energy was its use to power reverse osmosis (RO) desalination plants to provide water for the personal

Eritrea was selected due to its susceptibility to droughts, and consequential loss of life. The hypothetical pretext for the need for municipal desalination is that Eritrea has a substantial coastline, and the sea level rise expected due to climate change has the potential to hasten the intrusion of saline water into the fresh groundwater aquifers in the coastal zone. The focus of this research will be the island of Massawa, shown below, which is in a particularly dry part of Eritrea with, typically, less than 200 mm of annual rainfall as shown in **Figure 1**. This is in comparison to the UK, where according to the Metrological Office [2], the minimum rainfall

alone as an independent and viable power source in their own right; and

of energy delivery within a larger system due to intermittency.

on offer from renewable energy and decentralisation of supply.

Stage 1 employed Solar PV with the No Brine Stream Recovery (BSR) RO plant only as shown in **Figure 3**.

The methodology used to identify the minimum number of membranes that the RO plant would require is shown in **Figure 4**.

**Figure 2.** Three stages of modelling exercise.

**Figure 3.** Single source of renewable energy to power RO plant.

**Figure 4.** Methodology to identify minimum number of membranes that the no BSR RO plant requires.

#### *2.1.1. Results*

The initial results (shown in **Figure 5**) gave the minimum number of membranes required to produce 7000 m3 /day, if the plant were run for 24 h continuously at each recovery ratio.

It was decided that the RO plant would operate where the minimum number of membranes required was consistent between 15 and 24% recovery ratios, as shown in **Figure 5**.

A schematic diagram of the No BSR plant employed for the modelling within this research is shown in **Figure 6**.

The resulting No BSR RO plant operating profile, including impacts on efficiency as load changes as expected due to intermittent power as indicated in the US DOE Tip sheet 2 [3], is shown in **Figure 7**.

This surface was mapped mathematically using polynomial equations and the method used to calculate the amount of water produced, was a 'for' loop in Matlab, as shown below:

$$\begin{aligned} \text{amount of water produced, was a } & \text{for' loop in Matlab, as shown below:} \\\\ \text{for i = 1:rwr} \\ \text{newwater1(i) = polyval(\text{polycoef(index(i),:}), \text{Pg1(i,:)}) \\ \text{end} \end{aligned} $$

where *Pg 1* = the power available to operate the RO plant at each hour during the year; *index(i)* identifies the location of the prevailing seawater temperature for each hour of the year; *ppolycoeff* is a file that contains all the polynomial equations relating to each 0.01°C step from 3 to 42 °C; *i=1:rwr* defines the number of times that the calculation should be conducted before stopping; *i*=the number of the calculation being conducted, in this case, conducted in sequence from 1 – (rwr) the max number of which is 8760 (the number of hours in a year); *Polyval* is the matlab function that then evaluates the polynomial equation identified by *(index(i))* making the

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181

**Figure 7.** No BSR RO plant water production profile at varying power and feedwater temperature.

Massawa is one of the hottest inhabited places in the world, so solar PV was adopted.

HOMER (energy modelling software for renewable energy systems) was employed to derive the solar irradiance on an hour-by-hour basis based on the monthly averages from [4], as

The solar array for this process assumes that 10% of the available radiation, at any time when the sun is shining, is captured and converted to usable DC electrical power. This DC power is then be converted, by an inverter, to AC power, suitable for use by the RO plant. The effi-

Sufficient solar photovoltaic power was installed so that the maximum power output during the year from the solar PV would achieve the maximum flowrate of the RO plant. Additional power was then added in discrete levels, up to (and including), the power required to achieve

Stage 2 employed the same methodology as Stage 1 (application of solar PV only), but for the

corresponding *Pg* at *(i)* the subject.

*2.2.1. Renewable energy system employed within model*

five times maximum flowrate of the RO plant.

BSR RO plants (Pelton wheel and Pressure exchanger).

ciency of this power conversion was taken as between 90 and 95%.

**2.2. Solar power**

shown in **Table 1**.

**2.3. Stage 2**

**Figure 5.** Minimum number of pairs of membranes at each site for maximum temperature at various recovery ratios.

**Figure 6.** No BSR RO plant.

**Figure 7.** No BSR RO plant water production profile at varying power and feedwater temperature.

where *Pg 1* = the power available to operate the RO plant at each hour during the year; *index(i)* identifies the location of the prevailing seawater temperature for each hour of the year; *ppolycoeff* is a file that contains all the polynomial equations relating to each 0.01°C step from 3 to 42 °C; *i=1:rwr* defines the number of times that the calculation should be conducted before stopping; *i*=the number of the calculation being conducted, in this case, conducted in sequence from 1 – (rwr) the max number of which is 8760 (the number of hours in a year); *Polyval* is the matlab function that then evaluates the polynomial equation identified by *(index(i))* making the corresponding *Pg* at *(i)* the subject.

#### **2.2. Solar power**

*2.1.1. Results*

produce 7000 m3

180 Desalination and Water Treatment

shown in **Figure 6**.

shown in **Figure 7**.

**Figure 6.** No BSR RO plant.

for i = 1:rwr newwater1

end

The initial results (shown in **Figure 5**) gave the minimum number of membranes required to

It was decided that the RO plant would operate where the minimum number of membranes

A schematic diagram of the No BSR plant employed for the modelling within this research is

The resulting No BSR RO plant operating profile, including impacts on efficiency as load changes as expected due to intermittent power as indicated in the US DOE Tip sheet 2 [3], is

This surface was mapped mathematically using polynomial equations and the method used to calculate the amount of water produced, was a 'for' loop in Matlab, as shown below:

**Figure 5.** Minimum number of pairs of membranes at each site for maximum temperature at various recovery ratios.

(i) <sup>=</sup> polyval(ppolycoef(index(i), :), Pg1(i, :)) ;

(1)

required was consistent between 15 and 24% recovery ratios, as shown in **Figure 5**.

/day, if the plant were run for 24 h continuously at each recovery ratio.

Massawa is one of the hottest inhabited places in the world, so solar PV was adopted.

HOMER (energy modelling software for renewable energy systems) was employed to derive the solar irradiance on an hour-by-hour basis based on the monthly averages from [4], as shown in **Table 1**.

#### *2.2.1. Renewable energy system employed within model*

The solar array for this process assumes that 10% of the available radiation, at any time when the sun is shining, is captured and converted to usable DC electrical power. This DC power is then be converted, by an inverter, to AC power, suitable for use by the RO plant. The efficiency of this power conversion was taken as between 90 and 95%.

Sufficient solar photovoltaic power was installed so that the maximum power output during the year from the solar PV would achieve the maximum flowrate of the RO plant. Additional power was then added in discrete levels, up to (and including), the power required to achieve five times maximum flowrate of the RO plant.

#### **2.3. Stage 2**

Stage 2 employed the same methodology as Stage 1 (application of solar PV only), but for the BSR RO plants (Pelton wheel and Pressure exchanger).


\*The 'clearness index' is a dimensionless number between 0 and 1 indicating the fraction of the solar radiation at the top of the atmosphere that is able to pass through the atmosphere to the Earth's surface.

**Figure 8.** Pelton wheel BSR RO plant.

**Figure 10.** Pressure exchanger BSR RO plant.

**Figure 9.** Pelton wheel BSR RO plant water production profile at varying power and feedwater temperatures.

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**Table 1.** Average monthly irradiance.

#### *2.3.1. Pelton wheel*

The Pelton wheel RO plant system modelled is shown in **Figure 8**.

As shown in **Figure 8**, the Pelton wheel BSR RO plant design utilises the brine/concentrate stream to power a Pelton wheel turbine, which is mechanically linked to a high pressure pump arrangement and partially pressurises the incoming feedwater. This reduces the external power required to raise the feedwater pressure. The resulting Pelton wheel BSR RO plant water production profile, at varying input power and feedwater temperatures, is shown in **Figure 9**.

#### *2.3.2. Pressure exchanger*

The pressure exchanger RO plant system modelled is shown in **Figure 10**.

As shown in **Figure 10**, the pressure exchanger BSR RO plant uses the brine/concentrate stream to pressurise a hydraulic chamber. This hydraulic chamber acts on a piston arrangement, which in turn is used to partially pressurise the incoming feedwater. A booster pump then raises the now partially pressurised feedwater to the correct pressure to combine with the feedwater pressurised by the high pressure pump for desalination by the RO plant membranes.

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**Figure 8.** Pelton wheel BSR RO plant.

*2.3.1. Pelton wheel*

**Table 1.** Average monthly irradiance.

**Month Original monthly average (W/m2**

**that day)**

182 Desalination and Water Treatment

**Figure 9**.

membranes.

*2.3.2. Pressure exchanger*

The Pelton wheel RO plant system modelled is shown in **Figure 8**.

of the atmosphere that is able to pass through the atmosphere to the Earth's surface.

**/day during** 

Jan 303 7.272 0.895 Feb 357 8.568 0.954 Mar 366 8.784 0.884 Apr 376 9.024 0.855 May 337 8.088 0.754 Jun 306 7.344 0.686 Jul 300 7.2 0.674 Aug 301 7.224 0.684 Sep 330 7.92 0.784 Oct 319 7.656 0.830 Nov 308 7.392 0.891 Dec 295 7.08 0.905

**Conversion to kW/h Clearness index\***

**HOMER**

 **applied by** 

The pressure exchanger RO plant system modelled is shown in **Figure 10**.

As shown in **Figure 8**, the Pelton wheel BSR RO plant design utilises the brine/concentrate stream to power a Pelton wheel turbine, which is mechanically linked to a high pressure pump arrangement and partially pressurises the incoming feedwater. This reduces the external power required to raise the feedwater pressure. The resulting Pelton wheel BSR RO plant water production profile, at varying input power and feedwater temperatures, is shown in

\*The 'clearness index' is a dimensionless number between 0 and 1 indicating the fraction of the solar radiation at the top

As shown in **Figure 10**, the pressure exchanger BSR RO plant uses the brine/concentrate stream to pressurise a hydraulic chamber. This hydraulic chamber acts on a piston arrangement, which in turn is used to partially pressurise the incoming feedwater. A booster pump then raises the now partially pressurised feedwater to the correct pressure to combine with the feedwater pressurised by the high pressure pump for desalination by the RO plant

**Figure 9.** Pelton wheel BSR RO plant water production profile at varying power and feedwater temperatures.

**Figure 10.** Pressure exchanger BSR RO plant.

As was the case in the previous Stages, additional wind power was added in discrete levels up to (and including) the power required to achieve five times maximum flowrate of each of

The Use of Renewable Energy for the Provision of Power to Operate Reverse Osmosis…

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There was limited success in identifying scenarios that were able to meet the water demands of the local population without increasing the capacity of the RO plant to compensate for intermittency. So, each of the RO and Power plant scenarios were scaled up by the ratio of water shortfall, i.e. if the combined RO plant and Power scenario made 50% of required water, both the RO plant and installed power are doubled in size to fully meet the water demand requirements.

Prices are based on exchange rate of \$1–£0.636 as was the case in 2011, when much of the

**Table 2** shows the CAPEX and OPEX costs associated with the unscaled RO plants employed

Reservoir costing was taken as £82,115,200 based on extrapolation of various reservoir costs

Intermittent operation of desalination plants is possible and has already been realised in smaller systems as shown in [12, 13]. According to Rizzuti [14], however, it is understood that for large-scale seawater desalination plants, the plant's lifetime could be reduced by increased

This said, there is potential for the mechanical wear aspects on the plant to be reduced due to the increased size of the scaled up renewable RO plant, as the components will not experience

**) No BSR Pelton wheel Pressure exchanger**

Capital costs 9.27 10.38 11.12 Total costs over 25 years 48.8 79.1 56.0

/day output

185

**2.5. Scenarios modelled and scaling of renewable energy scenarios**

capacity with varying installed solar PV and wind capacity.

Sixty scenarios were modelled with BSR and No BSR RO plants limited to 7000 m3

the RO plants.

**3. Costs**

based on [6–10].

**(£x106**

original research was conducted.

**3.1. RO plant and reservoir costs**

*3.1.1. Impacts of intermittency*

scaling, fouling and corrosion.

from [11] to meet the required holding capacity.

**Table 2.** Capital, O&M and total costs over 25 years for RO plants.

**Figure 11.** Pressure exchanger BSR RO plant water production profile at varying power and feedwater temperatures.

The resulting pressure exchanger BSR RO plant water production profile, at varying input power and feedwater temperatures, is shown in **Figure 11**.

As was the case in Stage 1, additional solar PV power was added in discrete levels up to (and including) the power required to achieve five times maximum flowrate of each of the RO plants.

#### **2.4. Stage 3**

Stage 3 modelled the addition of wind power in an attempt to make the renewable powered scenario competent to produce the correct amount of potable water for the Massawa residents.

#### *2.4.1. Wind resource available Massawa*

The monthly average wind speed data at Massawa was taken from monthly average data over 4 years based on local weather reports [5] and applied to HOMER to derive the wind speed for each hour of the year, shown in **Figure 12**.

**Figure 12.** Wind speeds at Massawa over 1 year.

As was the case in the previous Stages, additional wind power was added in discrete levels up to (and including) the power required to achieve five times maximum flowrate of each of the RO plants.

#### **2.5. Scenarios modelled and scaling of renewable energy scenarios**

Sixty scenarios were modelled with BSR and No BSR RO plants limited to 7000 m3 /day output capacity with varying installed solar PV and wind capacity.

There was limited success in identifying scenarios that were able to meet the water demands of the local population without increasing the capacity of the RO plant to compensate for intermittency.

So, each of the RO and Power plant scenarios were scaled up by the ratio of water shortfall, i.e. if the combined RO plant and Power scenario made 50% of required water, both the RO plant and installed power are doubled in size to fully meet the water demand requirements.
