1. Introduction
As global demand for freshwater increases, desalination technology becomes indispensable because natural supplies of fresh water are limited. Currently, the world population affected by water shortages is nearly 40% [
1]. The current global desalination capacity is 90 million m
3 per day, far too small to offset these shortages [
2]. Most of the desalination power plants are concentrated in the Middle East, where dry Arab countries use desalination to meet their fresh water demands [
3].
The Kingdom of Saudi Arabia (KSA) is the largest producer of desalinized seawater, with 17% (17.2 million m
3 per day) of the worldwide capacity. Over the next 20 years it is predicted that the KSA will need to increase this output by 6 million m
3 per day [
4]. Burning oil supplies creates the energy needed for this desalination process. The KSA currently consumes more than 1.5 million barrels of oil per day for this purpose [
5]. A barrel of oil has enough energy to produce about 5 m
3 of desalinized water [
4]. The fossil-fuel energy consumed for desalination raises concerns about greenhouse gas (GHG) emissions. Before 2016, electricity from oil production was very low, effectively subsidized by the government, which started to reduce the support gradually. The use of renewable energy for powering desalination is therefore of great interest, although currently, only about 0.02% of the world’s freshwater production from desalination is renewable-powered [
6]. Solar photovoltaic (PV) or solar thermal represents most of this fraction, and these technologies are appropriate for the Middle East due to the abundant solar resources. Consideration by the Persian Gulf countries to move to sustainable renewably powered solar desalination is a current effort. However, the technology is presently expensive relative to burning oil, and it can be difficult to implement.
In the KSA, desalination plants are dual-purpose, producing both electricity and water for coastal urban centers. To avoid transportation costs, large-scale plants are mostly located on the Red Sea or the Persian Gulf, where there is both an ample supply of seawater and dense populations. Inland KSA cities sometimes incur a high cost for pumping water from coastal plants. To avoid these pumping costs, isolated cities or facilities such as hotels, hospitals, offshore platforms, ships, etc., can use small-scale desalination plants (mobile or stationary) to supply fresh water. In remote communities that have periodic water shortages, small mobile desalination units are often used. There are two basic types of desalination: thermal and membrane. Globally, 68% of desalination is membrane-based, 30% is thermal, and the remainder uses other processes [
7]. Within the thermal desalination sector, multi-stage flash (MSF) technology is the most common, and reverse-osmosis (RO) is the most common membrane process [
8]. MSF operates by passing heated seawater into a sequence of vacuum chambers, to promote flash evaporation. The resulting vapour condenses onto heat exchangers, which transfer thermal energy to the incoming feed seawater. Because MSF is reliable and easy to operate and can be powered by burning fossil fuels, it is frequently used in Middle Eastern nations [
3]. The performance of an MSF system depends on many factors, such as the temperature of the feedwater [
8]. If the feedwater temperature is too low, then the salinity of the product water is too high [
9]. This creates a seasonal effect on the quality of water produced from this process. Researchers have concluded that production is higher in summer than in winter due to the higher summer feedwater temperatures [
10].
RO operates by allowing the passage of water molecules, excluding salts and other impurities, through special membranes by applying high pressure. RO is the most common membrane process because of its low energy requirements and greater recovery percentage [
11]. RO desalination is also affected by feedwater temperature, including the recovery ratio, consumed energy per cubic meter, and salt rejection [
12]. Higher feedwater temperatures have been shown to improve the recovery ratio and reduce power consumption [
13]. MSF requires a mix of thermal and electric energy (for pumping), whereas RO primarily requires electrical energy. However, if the RO feedwater requires heating to improve performance, then RO also requires thermal energy. Solar energy conversion into thermal or electric energy is credible and is the most prevalent renewable energy source in the Middle East. Consequently, the greatest attention for renewable desalination has focused on solar-based systems. Renewable desalination is appropriate for dry, sunny, and remote regions where no other mode of power is possible. Photovoltaic (PV) cells convert solar radiation into electrical power, but their efficiency reduces when their temperature increases. One way to overcome this problem is to cool the solar cells with a circulating flow of coolant, which improves electrical efficiency while producing thermal energy. The result is a hybrid photovoltaic/thermal (PVT) unit [
14,
15,
16,
17]. Because electricity production is most often the priority, PVT is not widely used as a PV or a solar collector units alone. However, PVT systems have a lower cost per unit of electricity and heat produced for the same total surface area needed for their installation [
15]. The total requirement area for a PVT collector system is about 40% less than separate PV and solar thermal collectors with the same total capacity. In many applications of hybrid PVT systems, the prioritization of electrical output is as such that the operating conditions of the heat transfer unit are controlled, thereby maximizing electrical output, not thermal output. However, PVT designed to optimize heat transfer is possible, creating higher outlet fluid temperatures while sacrificing some PV efficiency [
18]. Therefore, PVT is very attractive to numerous applications because it is flexible in terms of thermal versus electric energy outputs. Besides, PVT could be appropriate for desalination applications in KSA, where high ambient and operating temperatures reduce the efficiency of PV systems.
The goal of the research described herein is to optimize the integration of PVT for a small-scale desalination plant appropriate for a remote community in the KSA. The design uses a mix of PVT and conventional electrical power to drive RO desalination. The PVT thermal output can raise the feedwater temperature, thus reducing the viscosity and the power required for pumping, improving RO performance, and the PVT electrical output provides some of the RO power needs. Excess PVT electrical power may be stored in a battery for nighttime desalination, along with grid power as needed, to maintain continuous RO production. The following describes the structure of this paper. First, a detailed illustration of the methodology and the model used in this study is present in
Section 2. Second,
Section 3 shows the dispatching algorithm for the PVT while
Section 4 presents a detailed economic model. An optimization algorithm for the proposed system is in
Section 5. The results of the cost objective optimized function are present in
Section 6. Lastly,
Section 7 summarizes the research outcomes and major findings.
3. Electrical Power Dispatching
Referring to
Figure 1, the electrical side of the system requires a dispatching algorithm that allocates PVT electrical power
to the load and battery, decides when to discharge the battery, and decides when to use grid power. The plant electrical load and the battery storage charge level determines the dispatching process hourly. If the plant electrical load exceeds the PVT electrical output, then all of the PVT electrical power is dispatched to the plant and, if possible, the battery satisfies the remainder. Utilization of grid power occurs if the PVT and battery cannot meet the load. When PVT electrical output exceeds the load, the excess power is stored in the battery.
The PVT electrical output is split at each hour
into energy
sent directly to the load, and energy
to charge the battery. Therefore,
The total electrical load,
for the plant must be satisfied at each hour, such that:
where
is the battery output to the load and
is the energy purchased from the grid. The battery charge level is
, which is updated each hour according to
Characterization of the battery storage includes the following three parameters: a maximum storage capacity
, a minimum storage capacity
, and the number of hours
required to charge or discharge the battery. This means that there is a limit on the hourly energy transfer to and from the battery, accordingly:
Additionally, the battery charging and discharging at the same time is not allowable. At each hour, the dispatching proceeds based on Equations (19)–(22) and a few simple rules. If the electrical load exceeds PVT output, then all of the output is dispatched to the system and the battery satisfies as much of the remainder as possible, with grid power used as a last resort. If PVT output exceeds the load, then as much of the excess PVT power as possible is stored in the battery, and any remaining power is sold back to the grid.
System Simulation
Using the models for the PVT, thermal storage tank, RO, and electrical dispatching, a single dynamic model simulation for the system is constructed. The system is characterized by a fixed production level of 362 m
3/day of distilled water, a location for the TMY3 data, and four system parameters:
,
,
, and
. To illustrate the action of the system, plots are included here for a single location in KSA with the following conditions:
,
,
, and
.
Figure 5 shows the total system electrical load along with the PVT electrical output, indicating the peaks due to solar activity during each day. Also shown is the tank temperature, and it is clear that the load decrease for higher temperatures. The variations in tank temperature are about 5 degrees, causing a power variation of about 10 kW, which represents about 15% of the peak load.
The PVT electrical output is only large enough to meet the full load during part of the day. At other times, either the battery or the grid power makes up the rest of the load.
Figure 6 illustrates the power dispatching from each source to the load. This clearly shows a similar daily cycle, where PVT output can meet the load during the sunny hours, the battery then meets the load in the early evening and night hours, and the grid meets the load in the early morning hours after the battery has drained and before the solar activity begins again.
The battery and PVT array sizes chosen as such that the load (zero curtailed PVT power) can utilize all of the PVT electrical power output. Therefore, it is notable that expanding the size of the PVT system to function completely on renewable energy significantly adds to the system cost.
To get a sense of average system performance,
Figure 7 illustrates monthly totals for the year in terms of three categories of power used to meet the load: power directly from the PVT to the load, power indirectly to the load from the PVT via the battery, and grid power. This figure shows that for the system parameters selected, the typical monthly PVT power penetration is about 70%. In other words, about 70% of the load satisfies the renewable power generated by the PVT array.
The system performance as illustrated by
Figure 7 is a function of the PVT array size, the tank volume, and the battery capacity. Average renewable penetration for the year is a single performance measure that can characterize the system as a function of the system parameters. The next section develops an economic model for the system as another measure of performance. This model can be used to cost optimally size the PVT system for a specific application.
4. System Cost Model
This section presents a model for total annual plant cost, represented as the sum of payment towards an amortized loan and annual operating costs (grid-power purchases plus maintenance). Both the loan payment and operating costs are functions of the PVT array size, the battery capacity, and the tank size. The up-front system capital cost functions as an investment repaid via a loan with a fixed interest. Operating costs are determined by simulating for one year.
Table 1 lists variables required to determine system cost. It also shows the unit costs (with references) employed for the study [
27].
The full system capital cost is determined by the following components: PVT array, batteries, RO, storage tank, high-pressure pumps for the RO, and low-pressure pumps for moving water through the PVT. The PVT capital cost computes as the product of the number of panels with a per-panel price. Similarly, the battery capital cost is proportional to its storage capacity
, and the storage tank capital cost is proportional to its volume. The RO capital cost is proportional to production capacity
. All of the individual component costs sum the full capital cost, as follows.
KSA encourages and offers incentives to effectively reduce this up-front cost burden, modelled here as a renewable credit
. Additionally, KSA offers lower interest rates
for financing renewable-energy projects [
28]. The entire system is assumed to operate for a lifetime
, and the loan is amortized over this period of time, leading to the following loan payment.
The annual grid cost is found by running the dispatch model for the full year and summing all of the hourly grid energy purchases
. Currently, KSA electrical prices are increasing, which serves to further motivate the renewable approach [
29]. The grid electrical purchases are computed on a flat price per-kWh basis
. The total annual cost for the plant is the sum of the annual loan payment, and the grid energy purchases.
5. Optimization Process
The total cost viewable as a nonlinear objective function, which depends on the PVT array size, the tank volume, and the battery storage capacity. The total cost optimization over these variables, while keeping all other parameters (interest rate, prices, plant location, production level, etc.) constant is a necessity. Furthermore, it is possible to perform cost optimization while constraining the average renewable penetration level. Evaluating the cost objective function requires the following steps.
Input the PVT array size, tank volume, and battery capacity.
Compute the hourly PVT useful heat and electrical energy output, tank temperatures, and RO electrical demand
Operate the hourly electrical dispatching simulation to determine system energy flows, grid purchases, etc.
Determine the average renewable penetration
Evaluate the total system cost using Equations (21)–(25).
The cost objective function is optimized using Matlab’s “fmincon” package, which implements sequential quadratic programming to find the two PVT array dimensions, tank volume, and battery capacity to minimize cost with constraints on the renewable penetration.
7. Conclusions
In this research, a theoretical approach to building a low energy cost desalination system powered by renewable energy is an optimistic proposal. The research contributes to the knowledge in the design of a low-cost desalination system and that building this in remote areas in the Mediterranean region is beneficial. In particular, this work presents a design for optimizing the integration of PVT into small-scale desalination. This is appropriate for a remote community in KSA, such that the PVT electrical output and conventional grid power will satisfy the electrical load for the plant and the excess PVT electrical power may be stored in a battery for nighttime desalination, along with grid power as needed to maintain continuous RO production. The PVT thermal output can raise the feedwater temperature, improving RO performance. The energy demands for RO reduces by preheating the feed brine. The non-linear cost objective function minimizes with constraints on renewable energy penetration. When the PVT supplies 70% of the total system energy needs (70% penetration), the cost decreases. The dynamic modeling for this study indicates that the optimal PVT, hot water tank, and battery capacities are , , and , respectively. In this case, on average, the PVT system serves to reduce costs by 30% relative to a conventional fossil fuel-powered system with no PVT. Future studies to validate the potential of the proposed system experimentally is a necessity. Furthermore, other designs could include coupling PVT with CHP, since the CHP can be ramped up or down to complement the PVT output. The design has the potential to optimize the size of each component as a function of climate and location. Additional designs could include coupling PVT with combined MSF and RO, the thermal output from PVT entered into the MSF unit, which will increase the production of MSF. Then, the rejected brine of the MSF unit is hot and split into two streams. One stream is fed into the RO unit and the other stream goes out to the sea. The electricity output from PVT will drive the power consumption for MSF and RO.