Techno-economic study for photovoltaic battery-free irrigation systems in an arid area for olive fields in Western West Al Minya, Egypt

Abstract

Due to rain scarcity, artificial irrigation became an environmentally critical application for crop production. Proper irrigation is essential to maximize water use efficiency and plant biomass. Using clean energy sources is currently a trend that is sweeping the globe. To achieve this, we propose a solar-powered irrigation system. This study considers alternative irrigation systems using photovoltaic solar systems to pump water from deep wells for new land reclamation, whereas groundwater is the only source. The main objective is to evaluate various PV-powered pumping systems in Egypt's Western West Al Minya area. Two systems were nominated by considering the annual savings: the conventional irrigation Diesel system and a Photovoltaic (PV) battery-free irrigation system. The second system requires isolated pipes so solar radiation does not affect water temperature and avoids damage to plant roots. The 192 kW PV system was sized to operate a 60 KW water pumping system, with a required area of 1920 m² for implementation. Direct irrigation using PV systems proved the best economical solution since it incurs the fewest costs of $0.015/m³ for 100–120 m well depth, compared with $0.073/m³ from the conventional system. As a result, the proposed PV-pumping system reduced the overall system cost by around 80% concerning the conventional system.

Introduction

Renewable energy, in general, and photovoltaics (PV), in specific, showed excellent promise under a variety of energy consumption loads worldwide [1]. Integrating renewable energy sources as a replacement for Diesel generator systems (DGS) with one of the rising solutions in this field is PV systems, standalone or as part of a hybrid system. Earlier studies [2–4] have investigated the ideal arrangement for various hybrid energy system combinations that would effectively and affordably meet the electrical energy needs of a particular community. Others obtained the ideal configuration of a hybrid renewable energy system using the well-known HOMER program to optimize numerous electric renewables [5]. The system allowed users to input information on loads, component costs, technical specifications, and the availability of solar resources.

Water pumping and irrigation are only two of the many uses for solar energy harvesting that are now emerging. [1]. In such a context, various attempts were demonstrated in the literature toward optimum PV-based irrigation systems [2–10]. Evaluation of the socioeconomic effects of PV-powered irrigation systems from a novel standpoint [2]. Another exciting study in Egypt was reported in [11], searching for an online pre-sizing technique for PV water pump installations. The tool was designed mainly for PV-grid-connected systems as an extension of the work published in [12]. In Egypt, a similar approach was tackled in [9] toward the PV water pumping sizing tool. From a macroscopic perspective, reported attempts in the literature can be classified as complete standalone PV systems as in [4, 6], hybrid systems with the aid of a grid [7], or another renewable energy resource [5]. An interesting study in [3] introduces the PV-driven irrigation system in Egypt. The work presented a helpful model associated with a real case study in Al Minya, Egypt [3]. Moreover, prior attempts in [13] theoretically provided a variety of PV irrigation systems. Nevertheless, another notable gap was revealed by the economic investigations. It is clear from the literature that putting such techno-economic possibilities into practice is a multifaceted process.

The ideal design of a standalone photovoltaic battery-free system is covered in this manuscript. A simple-to-use, environmentally friendly option for irrigation fields is the photovoltaic irrigation system. Compared to the reference running system employing a Diesel generator [15] and other proposed PV battery-based systems in the literature, the proposed PV battery-free option offers significant cost savings.

Methodology

Design requirements

In the current study, the primary constraint considered the rules settled to irrigate the reclaimed land in Western-West Al-Minya summarized by Water pumping is permitted for 12 h per day, and the maximum allowed discharge is 1800 m³ per day. The average irradiance and the temperature across the 12 months in Al-Minya are displayed in Fig. 1; data are captured from [14].

Fig. 1 [Images not available. See PDF.]

The average irradiance and the temperature across the 12 months in Al-Minya

Alternatively, another set of constraints is related to the crop water requirements [15, 16]. Olive (Oleaeuropaea L.) is an evergreen fruit tree owned by the family (Oleaceae). For thousands of years, Throughout the Mediterranean Basin, the olive has long been a significant crop for both table olives and oil. By establishing new orchards in climate-appropriate locations and boosting the productivity of existing plantings, the current rising demand for these goods is offering incentives to expand production. According to FAO statistics 2020 [18], Egypt produced 932,927 tonnes of olives, harvested over 100,826 ha. It is well known that yield and irrigation application intensity are closely connected. On the other hand, the olive tree is the most adapted in semi-arid regions. The tree’s drought tolerance and capacity to grow in shallow, poor soil make it one of the most intriguing plants to grow in dry and semi-arid regions. [17]. Moreover, olive trees are considered moderately tolerant to salinity [18]. Consequently, the olive crop is more suitable for the Western West Al Minya area, whereas the groundwater salinity ranges between 1800–2800 ppm. At a height of 6 to 7 m, transplants of the primary cultivar of olive trees, Aggezi, and the pollinator cultivar, Manzanillo, are being planted (6 m among trees in the same row and 7 m among tree rows—about 100 trees per feddan). The daily needs for water range between 10 to 100 m³ according to the tree's age and the time of year. Depending on the age of the trees, the number of pipes, emitters, and flow rate are chosen. The Western West Al Minya project has divided the entire area into pieces. Each part has roughly 230 feddan, but only 160 are planted and watered. As a result, each portion has a total of 16,000 trees. The water use per day for olive trees using drip irrigation is shown in Table 1 [19].

Table 1. The water requirement (m֚³/day/160 feed)

Month	Qt required (m֚3/day/160 fedd)
Jan	800
Feb	800
Mar	1280
Apr	1600
May	1600
Jun	1600
Jul	1600
Aug	1600
Sep	1600
Oct	1280
Nov	800
Dec	800

Conventional irrigation diesel system

Considering the reference running system, this section demonstrates a diesel generator’s economic analysis. The diesel size load power is 80 hp, with 12 years lifetime. Herein, the annual interest rate is 2%, and the diesel generator’s initial price, including mounting and installation, is $5000. The total cost of the diesel generators, including mounting and installation, overall 24 years, is calculated by [12]:

1

$$P_{\mathit{Diesel}}=5000\ast \left[\frac{1-\left(1+i_{12y}{)}^{-N}\right)}{i_{12y}}\right]=\mathrm{\$}5000\ast \left[\frac{1-\left({1+0.27)}^{-2}\right)}{0.27}\right]=\mathrm{\$}7037$$

The overhaul and maintenance of the diesel generator parts cost 24 years, which is around $2000. The 80-hp diesel generator consumes about 20 L per hour. This amount means that 12 h of operation needs 240 L per day. Based on the Egyptian rate, the cost per liter is about $0.5. Thus, the fuel cost is $120 per day. Since the irrigation is done 270 days per year, the total annual fuel cost is 270 * 120 = $32,400. The cost of fuel consumed in the first year is calculated as [12]:

2

$$P_B\left[\frac{1-\left(1+i_y{)}^{-N}\right)}{i_y}\right]=\mathrm{\$}32,400\left[\frac{1-\left({1+0.02)}^{-24}\right)}{0.02}\right]=\mathrm{\$}612,811$$

Accordingly, the total cost of a diesel generator over 24 years is $\mathrm{\$}7037+\mathrm{\$}2000+\mathrm{\$}612,811=\mathrm{\$}621,848$

On the other hand, the submerged pump power used in this study is 60 KW, 80 hp pump. A submerged pump costs $4000, with a 6-year lifespan. The submerged pump’s cost is reflected in the first year as [14]:

3

$$P_B\ast \left[\frac{1-\left(1+i_{6y}{)}^{-N}\right)}{i_{6y}}\right]=\mathbf{4000}\ast \left[\frac{1-\left({1+0.12)}^{-4}\right)}{0.12}\right]=\mathrm{\$}12,000$$

The specifications of the submersible pump are listed below:

Jacket 120 m × 750 LE/m = 90,000 LE = $\mathrm{\$}$5625.

submersible pump cost 80 hp = $\mathrm{\$}12,000$.

5″ pipe iron 525 LE/m, 120 m = 63,000 LE = $\mathrm{\$}$4000.

Cable 180LE/m * 120 m = 22,000 LE = $\mathrm{\$}$1350.

Electric control = 9000 LE=$\mathrm{\$}$577.

Stabilizer = 30,000 LE=$\mathrm{\$}$1923.

Concrete = 5000 LE=$\mathrm{\$}$321.

The total cost of submerged pump + P_well =$\mathrm{\$}$25,796.

The traditional irrigation diesel system’s economic analysis is as follows:

P_Diesel generator = $\mathrm{\$}621,848$

P_{submerged-pump} + P_well = $\mathrm{\$}$25,796.

The total payment P_t cost of diesel generator overall 24 years + the total cost of submerged pump + P_well = $647,644. The annual average daily pumped water is obtained by summing Q_t in Table 1 and dividing the result by 12. This gives 1280 m³/day. This means that the total amount of pumped water for 1 year is 1280 * 365

4

$$\text{Pt}=\mathrm{\$}647,644=1280\ast 365\ast C_1\ast \left[\frac{1-\left({1.02)}^{-24}\right)}{0.02}\right]$$where ${\mathit{C}}_1=\mathrm{\$}0.073/\mathbf{m}$³, where $C_1$:pumping cost per m³.

PV battery-free irrigation system

Multi-crystalline photovoltaic modules, SES12160, are used; as a commonly used module in the Egyptian market [19], the module characteristics are listed in Table 2. There are 36 series-connected cells per module. Because the usual operating voltage exceeds 12 V and the V_mp of each cell is approximately 0.5 V, most modules are constructed using series cells. According to [4], the PV array factor FA is as follows:

5

$$FA=\frac{P_p}{P_L}$$

Table 2. The PV module and inverter specifications

Parameter	Value
PV module specifications
$P_{\mathit{max}}$	200 W
$V_{\mathit{mp}}$	12.26 V
$I_{\mathit{mp}}$	13.05 A
$V_{\mathit{OC}}$	19.33 V
$I_{\mathit{SC}}$	18.83 A
Dimensions	1482 mm × 675 mm × 30 mm
Inverter specifications
Inverter input voltage	Ns*25 = 12*25 = 300 V
Output voltage	220 V AC
Peak voltage	311 V AC
Rated Power	180 kW
Lifetime	8 years
Phase	Single phase

$P_p$ is the PV array peak power, and $P_L$ is the average load power. $P_L$ is the daily load energy (kWh) divided by 24 h.

For PV sizing, a set of input parameters was defined. The solar declination angle (δ) is the angle between the equatorial plane and the plane; the solar declination angle is calculated by [20]:

6

$$\delta =23.45sin\left(\frac{284+d}{365}\times 360\right)$$

Additionally, the model specifies the sunset hour for an uneven surface (${\omega }_s$) and at an angle of a horizontal surface (${\omega }_{s2}$). Moreover, the hour angle is formed by the arc formed by the meridian planes comprising the first and second points of the earth's location at the same latitude angle along the equator. During dawn, it is set at − 90°, then rises to equal zero at midday, then rises to 90° at sunset.

Both angles are defined as [20]:

7

$${\omega }_s=co{s}^{-1}\left(-tan\delta tan\varphi \right)$$

8

$$\omega _s^{_{}^{″}}=co{s}^{-1}\left(-tan\delta tan(\varphi -\beta \right)$$

The latitude in this indicates the position of a place. The angle of incidence is the angle formed by the incident beam and the surface-perpendicular line. The angle between the plane φ, a surface on which a beam of radiation is falling β, and the horizontal surface is called the inclination. This angle determines the distance of a tilted plane from the south orientation. The surface faces south when the angle is 0°. The angle of incidence h becomes equal to the zenith angle if the plane under examination is horizontal, that is, i.e., β = 0 and also Ɣ = 0, then the angle of incidence = 0, then the angle of incidence θ_h becomes equal to the zenith angle [20].

Therefore, if the angle of incidence is zero, the angle of the amount of sunshine on a particular day of the year and location determines when it is daytime. Daylight fluctuates throughout the year and from place to place. Daytime may be determined using [4]:

9

$$T_d=\frac{24}{\pi }\left({\omega }_s\times \frac{\pi }{180}\right)$$

Consequently, the angle of the global solar radiation on the horizontal surface, which varies annually as well as by position, can be indicated as a part of H_B under zero angle of incident. Alternately, H_T is the surface-tilted global solar radiation. The ratio between H_B and H_T is indicated as [21]:

10

$$R_b=\frac{cos\delta cos\left(\varphi -\beta \right)sin{\omega }_s-{\omega }_{s}sin\delta sin(\varphi -\beta )}{cos\delta cos\left(\varphi -\beta \right)sin{\omega }_s+{\omega }_{s}sin\delta sin(\varphi -\beta )}$$

The monthly average daily extraterrestrial solar insolation on the horizontal surface at the same latitude of the site under consideration, which can be calculated by [4], is what is referred to as extraterrestrial solar radiation on a horizontal surface ($H_{\mathit{EXT}})$ [13]:

11

$$H_{\mathit{ext}}=\frac{24}{\pi }{G}_{\mathit{sc}}\left(cos\delta cos\varphi sin{\omega }_s\right)+{\omega }_s\times \frac{\pi }{180}\left(sin\delta sin\varphi \right)$$

The solar irradiance constant from space G_sc = 1.35 kW/m² regular to sunlight beams on surface. The clearness index ($K_T),$ another factor, measures the ratio of extraterrestrial solar radiation on a horizontal surface at the precise site location to global solar radiation on a horizontal surface. Calculating the clearness index is possible using [4]:

12

$$K_T=\frac{H_B}{H_{\mathit{ext}}}$$

On days with cloud cover, this ratio falls. The angled surface's exposure to the sun’s radiation $H_T$ can be calculated by [20]:

13

$$H_T=H_B\left(1.13K_T{R}_b+0.5\left(1+cos\beta \right)\right)\left(1-1.13K_T\right)+0.5\rho (\left(1-cos\beta \right)$$where the instantaneous global solar irradiance at the tilted surface $G_T$ can be calculated by [13]:

14

$$G_T=\frac{\pi }{24}{H}_T\left[\frac{cos\omega -cos{\omega }_{s2}}{sin{\omega }_{s1}-\frac{\pi {\omega }_{s1}}{180}cos{\omega }_{s2}}\right]$$

The calculated global solar radiation at the tilted surface in Al Minya showed a good agreement with the data published in [22, 23]

Lastly, the cell temperature is regarded as one of the cell properties. T_C is provided as a general guide (with an average wind speed of 3 m/s), which can be calculated by [13, 24, 25]:

15

$$T_C=T_A+7.8^{\prime }10-2^{\prime }I$$where $T_A$ is the ambient temperature, and $I$ is the solar irradiance in Watt/m², as given in Fig. 2b. The thermal voltage (V_T) is calculated by [13]:

16

$$V_T=\frac{\mathit{KT}}{q}$$

Fig. 2 [Images not available. See PDF.]

PV sizing model flow

The open circuit voltage for the PV module (V_OC) is calculated by [13]:

17

$$V_{\mathit{OC}}=V_T^{}ln\left(1+\frac{I_{\mathit{SC}}}{I_o}\right)$$where $I_{\mathit{SC}}$ is the short-circuit current, and $I_o$ is the p–n junction saturation current. The PV Array output current (IA) is calculated by [13]:

18

$$I_A=I_{\mathit{SC}}{G}_T-I_o\left(e^{V\left./\phantom{V{V}_T}\right)V_T}-1\right)$$

The power generated from the PV array (P_A) is calculated by [13]:

19

$$P_A=I_A{V}_B$$

$V_B$ is the battery voltage. The battery current (I_B) is calculated by [13]:

20

$$I_B=I_A-I_L$$

Figure 2 shows the flow chart for the algorithm used in PV sizing, where $I_L$ represents the load current. This procedure considers the model equations. Every minute of the year, the application calculates the sun irradiation. The power of an instantaneous solar PV array is calculated from solar irradiance. This system’s simulation is created using a MATLAB program, considering the effects of the weather, solar radiation, tilt angles, temperature, cloudy days, and the PV array's energy output. The model discussed here was adapted to the hourly tilted surface radiation model, as previously highlighted in [26].

Technical results and discussions

The simulations in this work use silicon material and the comprehensive simulation method outlined in Sect. 4 to refer to Al Minya, Egypt, at a 15-degree angle. The simulation program will power the 60-kW load from the PV array so that watering will last roughly 10 h every day. Our calculations revealed that 192 kW is the minimum array size needed. To determine the area needed to implement such a PV system for water pumping, we considered several factors: Firstly, multiply the power requirement (60 kW) by the operating hours (10 h) to obtain the daily energy output required (600 kWh). Apply the capacity factor to account for system losses and weather conditions; at 70%, the daily energy output required would be 600 kWh/0.7 = 857.14 kWh. Based on the solar irradiance in Al Minya and the efficiency of the PV system, the peak sun hours are around 4.46 h on average. Accordingly, an overall area of around 1920 m² is enquired. It is worth highlighting that the relatively low system efficiency, 70%, is attributed to the relatively high temperature associated with the location, as well as the nature of the system as a battery-free system, which requires a high margin of oversizing. Table 3 and Fig. 3 display the outcomes of the simulation program’s findings.

Table 3. Monthly average energy available in Western West Al Minya fixed system β = 15° North using silicon cell material

Month	Available (kWh/day)	ERequired (kWh/day)
Jan	695.9	405
Feb	907	480
Mar	1070	848
Apr	1114	1081
May	1194	1113
Jun	1155	1098
Jul	1140	1084
Aug	1134	1100
Sep	1051	1064
Oct	916	775
Nov	680	395
Dec	622	371

Fig. 3 [Images not available. See PDF.]

Average energy in Western West Al Minya

Figure 4 displays the required annual amount of water (blue) and the amount of water that must be pumped (orange) over the same period. The amount of pumped water that is available is more significant than what is needed; all information is provided in Table 4. The average monthly pump working time over a year is shown in Fig. 5 using the simulation program. Regarding the PV array arrangement, the number of series modules (Ns) is 300/25 = 12 because the array is 192 kW, and the Inverter needs 300 V at the input. Each module's operating voltage is 12 V. Given that each module has a 0.2 kW peak power, there are 192/0.2 = 960 modules. If there are 12 modules in a series, there are 960/12, or 80 parallel strings, hence Np = 80. All modules are oriented to the south with a tilting angle of 30°, considering standard mounting structures fixed to the ground.

Fig. 4 [Images not available. See PDF.]

The water requirement (m֚/³day/160 feddan) and water available (m֚/³day/160 feddan) for the olive crop 1 year

Table 4. The water Requirement, the water available (m֚/³month/160 feddan) for 1 year, and the pump working period for the Olive crop

Month	Qt(available) (m֚3/day/160 fedd)	Qt(required) (m֚3/day/160 fedd)	Two (working time) Hrs
Jan	1377	800	8.1
Feb	1513	800	8.9
Mar	1615	1280	9.5
Apr	1649	1600	9.7
May	1717	1600	10.1
Jun	1683	1600	9.9
Jul	1683	1600	9.9
Aug	1649	1600	9.7
Sep	1581	1600	9.3
Oct	1513	1280	8.9
Nov	1377	800	8.1
Dec	1343	800	7.9

Fig. 5 [Images not available. See PDF.]

The pump working period for 1 year

In the context of our study, the sensitivity analysis was conducted to account for variations in solar radiation and energy generation, with a specific focus on the performance and economic viability of the proposed PV system. By identifying key variables such as solar radiation levels, panel and Inverter efficiency, and system degradation and defining scenarios for high, medium, and low solar radiation levels based on location-specific data, we were able to quantify the energy generation for each scenario using our developed solar simulation code and PV system modeling tools. This allowed for an estimation of the annual energy output of the PV system under different solar radiation conditions. Subsequently, the financial impact of these variations was assessed by calculating the pumping cost per cubic meter of water for each scenario, considering the energy generation and associated costs, see next section.

The sensitivity analysis then played a crucial role, enabling an examination of how variations in solar radiation levels affect the economic performance of the PV system. By identifying the sensitivity of financial metrics such as payback period, net present value, and levelized cost of energy to changes in solar radiation, we were able to make informed decisions about the system's resilience to fluctuations in solar radiation. Ultimately, this analysis provided valuable insights into the robustness of the proposed PV system and informed the implementation of mitigation strategies, such as energy storage solutions, system design optimization, or operational adjustments, to enhance the system's performance under different environmental conditions.

Economic analysis

Economically, each KWp costs about $200 [1, 3, 13, 27–29], and since each module is 200 Wp, its price is $40. Hence, the entire array costs 80 × 12 × $40, or $38,400. The total cost of preventative maintenance for a PV system throughout its 24-year lifespan, including labor, mounting, cables, and other expenses, is around $38,400. PV modules and their support come to $76,800 in total cost. The secondhand Inverter has 8 years, 300 V, 667 A, and 200 KVA. The Inverter is around $12,500 in price. The cost of an inverter replacement for a project with a 24-year lifespan and a 2% yearly interest rate can be estimated as follows:

21

$$P_{\mathit{inverter}}=\mathrm{\$}12,500\ast \left[\frac{1-\left(1+i_{8y}{)}^{-N}\right)}{i_{8y}}=12,500\ast \left[\frac{1-\left({1+0.08)}^{-3}\right)}{0.08}\right]=\mathrm{\$}32,000\right]$$

The overall system economic analysis can be demonstrated as follows:$${\text{C}}_{\text{PV}}=\mathrm{\$}76,800$$$${\text{C}}_{\text{onverter}}=\mathrm{\$}32,000$$$${\text{C}}_{\text{submerged pump}}+\text{Cwell}=25,796$$$$\text{Total payment Ct}=\mathrm{\$}135,000$$

The pumping cost per m³, $C_1$ can be written as:

22

$$C_t=\mathrm{\$}135,000=1280\ast 365\ast C_1\ast \left[\frac{1-\left({1.02)}^{-24}\right)}{0.02}\right]$$where $C_1=\mathrm{\$}0.015/\text{m}$³.

Based on the provided data in Table 5, the economic analysis of the PV system compared to traditional Diesel systems and PV battery-based models shows promising cost advantages. The table indicates that the PV system, including the inverter and submerged pump, has a pumping cost per cubic meter (m³) of 0.015, significantly lower than the pumping cost of the Diesel system, which is 0.073 per m³. This demonstrates that the running cost of the PV system is substantially lower than that of the Diesel system.

Table 5. Economic considerations for the alternatives under investigation in this paper

Alternative solution	pumping cost per m3	Payback period
1-PV + Inverter + submerged pump (PL = 60 KW) for 120 well depth	C1 = $0.015/m3	6 years
2-Diesel generator + submerged pump (PL = 60 KW) for 120 well depth	C1 = $0.073/m3	NA
3- PV battery-based system as in [3]	C1 = $0.044/m3	9 years

Furthermore, the data suggests that the original cost of the Diesel system is lower than the initial cost of the PV system. However, the running cost of the Diesel system, primarily due to the price of fuel, contributes to higher overall expenses compared to the PV system. Additionally, the analysis indicates that the proposed PV battery-free system offers cost reductions compared to the PV battery-based models, with a pumping cost of $0.044 per m³. This reduction is attributed to the battery-free approach, which eliminates the peak response in initial or replacement costs associated with batteries due to their limited lifetime. In conclusion, the economic considerations presented in Table 5 demonstrate that the PV system, with its lower running cost and competitive initial cost, offers a cost-effective and sustainable alternative compared to traditional Diesel systems and PV battery-based models. This analysis underscores the potential economic advantages of PV systems for water-pumping applications.

Another crucial consideration pertains to the payback period of the PV system. Given that the current PV system is primarily designed to generate savings rather than profits, the payback period is assessed in terms of the amount saved compared to a baseline model utilizing a diesel generator. In this context, the payback period reflects the time required for the cost savings from using the PV system to offset the initial investment, considering the expenses associated with operating a diesel generator. Notably, our analysis revealed that the battery-free PV system exhibited a more favorable payback period than the battery-based system. This outcome can be attributed to the additional costs associated with the latter, including the initial capital outlay for the batteries and potential replacement costs due to the limited lifespan of the battery storage units.

The comparison of payback periods between the battery-free and battery-based PV systems underscores the economic implications of incorporating energy storage in the system design. While the battery-based system offers advantages such as enhanced energy autonomy and load-shifting capabilities, the associated costs impact the overall financial performance and payback period. By highlighting the superior payback period of the battery-free system, our analysis underscores the potential for cost savings and improved financial viability by adopting simpler, battery-free PV configurations. Moreover, the payback period serves as a critical parameter in evaluating the economic feasibility of PV systems, guiding decision-making processes and investment strategies for sustainable and cost-effective energy solutions.

Environmental aspects

The environmental impact of the two irrigation systems, the PV system and the traditional Diesel system can be assessed through their carbon emissions. The Diesel system relies on fossil fuels, which release carbon dioxide (CO₂) and other greenhouse gases into the atmosphere, contributing to climate change. In contrast, the PV system generates electricity from solar energy, which is a renewable and clean source of energy, resulting in minimal carbon emissions. Quantitative analysis shows that the traditional Diesel system emits approximately 0.87 kg of CO₂ per liter of diesel fuel burned. Assuming an average fuel consumption rate of 3 L per hour for a 60-kW pumping system, the annual CO₂ emissions of the Diesel system would be approximately 4566 kg (0.87 kg/L × 3 L/h × 24 h/day × 365 days/year).

In contrast, the PV system does not emit any carbon emissions during its operation. However, the production of PV panels and other components does result in some carbon emissions. The carbon footprint of the PV system can be estimated by calculating the embodied carbon of the system, which includes the carbon emissions associated with the production, transportation, and installation of the components. According to a study by the National Renewable Energy Laboratory, the embodied carbon of a PV system is approximately 50–60 g of CO₂ equivalent per kilowatt-hour (kWh) of electricity generated. Assuming an average annual electricity generation of 200,000 kWh for a 192 KW PV system, the embodied carbon of the PV system would be approximately 11,000–13,200 kg of CO₂ equivalent.

Overall, the PV system offers significant carbon emissions reduction compared to the traditional Diesel system. The annual CO₂ emissions of the Diesel system are approximately 4566 kg, while the embodied carbon of the PV system is approximately 11,000–13,200 kg. This means the PV system can save up to 8634–9634 kg of CO₂ emissions per year. This highlights the eco-friendliness of the PV system and its added value in mitigating climate change.

System scalability

The scalability of the PV-powered irrigation system is a pivotal consideration, particularly when assessing its feasibility for larger agricultural areas. At its core, the system’s scalability refers to its ability to be expanded or replicated to meet the irrigation needs of more extensive farming operations. In the context of our study, the scalability of the PV-powered irrigation system was evaluated to determine its potential applicability for agricultural areas requiring higher water demand and broader coverage.

An essential aspect of assessing the scalability of the PV-powered irrigation system involves an analysis of its capacity to meet the increased water requirements of larger agricultural areas. This encompasses evaluating the system's energy generation, water pumping capacity, and overall efficiency when deployed at a larger scale. Additionally, considerations regarding the spatial requirements for installing additional PV panels and the corresponding irrigation infrastructure are integral to the scalability assessment. By examining these factors, we gained insights into the practicality of implementing the PV-powered irrigation system in more extensive agricultural settings and its potential to address the irrigation needs of expansive farming operations effectively.

The scalability of the PV-powered irrigation system extends beyond its adaptation for larger irrigation areas, encompassing its potential to power small residential units associated with the farming community. A fundamental driving force behind the system's scalability is the surplus energy production it generates, see Table 6. Without a storage system, the excess energy can be directly utilized to power additional loads. These supplementary loads may include expanding the irrigation area to cover larger agricultural expanses, as well as facilitating the energy needs of nearby residential units. The surplus energy produced by the PV-powered irrigation system presents an opportunity for leveraging the system's scalability to address the energy requirements of small houses within the farming community. By harnessing the excess energy, the system can contribute to providing sustainable power sources for lighting, appliances, and other residential needs. This dual-purpose approach not only enhances the economic viability of the system but also fosters an integrated energy ecosystem that benefits both agricultural and residential domains.

Table 6. Generated, consumed, and excess energy along the project lifetime

Year	Generated energy (MWh/year)	Consumed energy (MWh/year)	Excess energy (MWh/year)
0	350.4	219	131.4
1	346.896	219.657	127.239
2	343.42704	220.315971	123.111069
3	339.9927696	220.9769189	119.0158507
4	336.5928419	221.6398497	114.9529922
5	333.2269135	222.3047692	110.9221443
6	329.8946444	222.9716835	106.9229608
7	326.5956979	223.6405986	102.9550993
8	323.3297409	224.3115204	99.01822055
9	320.0964435	224.9844549	95.11198858
10	316.8954791	225.6594083	91.23607078
11	313.7265243	226.3363865	87.39013777
12	310.589259	227.0153957	83.57386337
13	307.4833665	227.6964419	79.78692459
14	304.4085328	228.3795312	76.0290016
15	301.3644475	229.0646698	72.29977768
16	298.350803	229.7518638	68.59893919
17	295.367295	230.4411194	64.92617557
18	292.413622	231.1324427	61.28117926
19	289.4894858	231.8258401	57.66364572
20	286.5945909	232.5213176	54.07327334
21	283.728645	233.2188815	50.50976348
22	280.8913586	233.9185382	46.97282038
23	278.082445	234.6202938	43.46215118
24	275.3016205	235.3241547	39.97746585
25	272.5486043	236.0301272	36.51847718

Furthermore, the system’s adaptability to accommodate additional loads, such as residential energy needs, underscores its versatility and potential for broader community impact. This expanded scope not only enhances the system’s relevance but also contributes to a holistic approach to sustainable energy utilization in rural settings. By recognizing and capitalizing on the surplus energy output, the scalability of the PV-powered irrigation system extends beyond agricultural applications, offering a multifaceted solution that addresses the energy demands of both farming and residential communities.

Finally, the economic feasibility of scaling up the PV-powered irrigation system was a key focus of our analysis. This involved an assessment of the cost implications associated with expanding the system to meet the irrigation demands of larger agricultural areas. Factors such as the upfront investment required for additional PV panels, pumps, and distribution infrastructure, as well as the operational and maintenance costs, were carefully evaluated. By conducting a comprehensive cost–benefit analysis, we determined the economic viability of scaling up the PV-powered irrigation system and its potential to deliver cost-effective and sustainable irrigation solutions for larger agricultural applications.

Challenges and recommendations

Implementing a PV system for irrigation and residential power generation may encounter several challenges and limitations. Weather variability, including cloud cover and seasonal changes in sunlight intensity, can impact energy production and system reliability. Additionally, in the case of a battery-based PV system, challenges related to energy storage, such as battery degradation and replacement costs, can influence the economic feasibility of the system. Water availability for irrigation, technical constraints related to system design and installation, initial capital investment requirements, and ongoing maintenance and operations are also vital considerations. Furthermore, grid interconnection complexities and regulatory requirements for selling excess energy can present additional challenges. Addressing these factors requires a comprehensive approach, including robust system design, effective maintenance strategies, and consideration of local environmental and technical factors.

Another important consideration is related to the risk analysis. Conducting a comprehensive risk analysis for the PV system involves assessing various factors, including equipment failure and long-term durability. Equipment failures, such as malfunctioning solar panels, inverters, or pumps, can disrupt energy production and irrigation processes, leading to potential economic losses. Evaluating the long-term durability of the PV system components is crucial to identify potential degradation, material fatigue, and environmental wear that could affect system performance over time. Additionally, considering external risks such as extreme weather events, vandalism, and theft is essential to develop mitigation strategies and ensure the resilience of the PV system. By addressing these risks, stakeholders can proactively implement measures to enhance system reliability and minimize potential disruptions.

Moreover, the transition from conventional to solar-powered irrigation in the local community carries significant social and economic implications. Solar-powered irrigation systems can enhance water access for agricultural activities, leading to increased crop yields and improved food security. Moreover, this transition can create new job opportunities, such as the installation and maintenance of solar panels and related infrastructure, consequently contributing to skill development and economic empowerment within the community. Additionally, the shift to solar-powered irrigation can reduce the reliance on fossil fuels, leading to environmental benefits and potentially mitigating the impact of climate change, thereby promoting sustainable agricultural practices and community resilience.

The issue of water quality is a crucial consideration when using a PV-powered irrigation system, particularly in areas with variations in groundwater quality. Variations in water quality, such as salinity levels and the presence of contaminants, can significantly impact crop yields and soil health. High salinity levels, for instance, can lead to soil degradation and reduced crop productivity. Therefore, it is essential to implement water quality monitoring and treatment measures to ensure that the irrigation water meets the required quality standards. Incorporating appropriate filtration and treatment technologies as part of the PV-powered irrigation system can help mitigate the potential negative impacts of varying groundwater quality, safeguarding crop yields, and promoting sustainable agricultural practices. We consider such investigation as a part of a future extension to this study.

Based on the research findings, policymakers and farmers in similar regions should consider several steps to promote the adoption of PV-powered irrigation. Firstly, policymakers can incentivize the adoption of solar-powered irrigation through financial support, such as subsidies or tax incentives, to alleviate the initial capital investment burden. Additionally, they can establish supportive regulatory frameworks and standards for grid interconnection and water quality management. Furthermore, capacity-building initiatives, including training programs and knowledge-sharing platforms, can empower farmers with the necessary skills for the installation, operation, and maintenance of PV-powered irrigation systems. Collaborative efforts between policymakers, agricultural extension services, and local communities can raise awareness about the benefits of solar-powered irrigation, ultimately fostering sustainable agricultural practices and enhancing food security in the region.

Conclusion

Solar Photovoltaic (PV) systems have long been regarded as a reliable source of electricity that might lessen a country’s reliance on fossil fuels. Also, the recent decline in PV system pricing has increased the world’s reliance on PV technology. In the Western West Al Minya, the PV system is regarded as the best option for irrigation systems in arid areas for olive fields. The research presented in this study established the techno-economic viability of calculating the array size requirements for a power pumping system for supplying water to irrigate 160 feddan of the olive crop from a deep well (120 m depth). By discussing various approaches for minimal cost, the PV battery-free model has demonstrated a significant cost reduction, reaching 80%, referring to a conventional DGS alternative. Changing the well depth will automatically reflect the pumping power needed and system sizing. However, as the current system is already over-sized to accommodate harsh environmental conditions, a margin of 20% increase in the depth can be accepted. In this regard, a detailed study on the impact of the well depth on the PV sizing can be considered a part of future work.

Author contributions

Conceptualization, Sameh O. Abdellatif; methodology, G. S., W.A. and Sameh O. Abdellatif; software, G. S., W.A. and Sameh O. Abdellatif; validation, G. S., W.A. and Sameh O. Abdellatif;; formal analysis, G. S., W.A. P. R. and Sameh O. Abdellatif;; investigation, G. S., W.A. and Sameh O. Abdellatif;; resources,G. S., W.A. E. S. M. S. and Sameh O. Abdellatif;; data curation, G. S., W.A. and Sameh O. Abdellatif; writing—original draft preparation, G. S., W.A. and Sameh O. Abdellatif; writing—review and editing, G. S., W.A. P. R. M. S. E. S. and Sameh O. Abdellatif; visualization G. S., W.A. and Sameh O. Abdellatif; supervision, G. S., W.A. and Sameh O. Abdellatif; project administration, Sameh O. Abdellatif; funding acquisition: NA. All authors have read and agreed to the published version of the manuscript.

Funding

The authors would like to acknowledge the support and contribution of the Centre for Emerging Learning Technologies CELT.

Data availability

The data supporting this study’s findings are available from the first author upon reasonable request.

Code availability

The code is available from the first author upon reasonable request.

Declarations

Ethics approval and consent to participate

Not applicable for that section. All authors confirm their participation in this paper.

Consent for publication

All authors accept the publication rules applied by the journal.

Competing interests

The authors declare no competing interests.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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