2.1. Irradiance

Solar irradiance is a fundamental factor in energy generation for PV cells. Solar cells absorb incoming sunlight on their surface and convert it into electrical energy. The performance of PV cells is directly dependent on irradiance levels, which are significantly influenced by variables such as geographical location, time of day and seasonal variations [Reference Kalogirou17–Reference Rydh and Sandén19]. Although the Sun generates a constant amount of energy, the rotation of the Earth and its elliptical orbit cause variations in the amount of solar irradiance received at a specific location throughout the day. To determine the amount of energy produced by solar cells, it is essential to calculate the solar irradiance reaching the surface. This calculation is performed using mathematical models and radiation transfer equations that account for the Earth’s position relative to the Sun [Reference Kalogirou17, Reference Aktas, Kirçiçek, Hayton and Reading20–Reference Page22]. To calculate the solar energy received at a specific location, equations that incorporate the angular position of the Earth relative to the Sun are used. Declination ( $\delta $ ) is defined as the angle between the line directed toward the Sun and the equatorial plane [Reference Mateja, Skarka, Peciak, Niestrój and Gude11]

(1) \begin{equation}\delta = 23.45 \times \sin \left( {\frac{{360}}{{365}} \times \left( {284 + n{\rm{\;}}} \right)} \right)\end{equation}

where $n$ represents the day of the year. The declination angle varies between (−23.45°) and (+23.45°), reaching its maximum positive value during the summer solstice and its minimum negative value during the winter solstice. Declination remains the same for all locations on Earth and serves as a fundamental parameter in solar irradiance calculations. The hour angle (ω) is an angular measure that represents the position of the Sun relative to the observer’s local meridian, changing approximately 15° per hour [Reference Mateja, Skarka, Peciak, Niestrój and Gude11]. It takes negative values before solar noon and positive values after solar noon. Solar time, which is used in hour angle calculations, differs from local time as it is based on the moment when the Sun reaches its highest point in the sky at a given location. This time system is determined by the apparent daily motion of the Sun. The hour angle can be calculated using Equation (2).

(2) \begin{equation}\omega = {15^o} \times ( {Solar{\rm{\;}}time - 12})\end{equation}

The hour angle $\left( \omega \right)$ ranges from (−180°) to (+180°), where negative values represent the time before solar noon and positive values correspond to the time after solar noon.

The zenith angle ${\theta _z}$ is the angle between the incoming solar irradiation and a horizontal surface, making it a crucial parameter in determining the angle at which solar irradiance reaches the surface. The representation of the zenith angle is illustrated in Fig. 1. The zenith angle can be expressed using the following equation:

(3) \begin{equation} {\theta _z} = \cos (\varphi ) \times \cos \left( \delta \right) \times \cos \left( {{\rm{\;}}\omega } \right) + {\rm{sin}}\left( {{\rm{\;}}\varphi } \right) \times {\rm{sin}}\left( \delta \right)\end{equation}

$\varphi $ represents the latitude and is converted to radians using the expression $\varphi = latitude{\rm{\;}} \times {\rm{\;}}\pi /180$ . The zenith angle $({\theta _z})$ ranges from 0° to 90°, where ${\theta _z} = {0^o}$ indicates that the Sun is directly overhead, and ${\theta _z} = {90^o}$ corresponds to sunset or sunrise. The day length $({\rm{N}}$ ) can be calculated using the following equation:

(4) \begin{equation}{\rm{N}} = \frac{2}{{15}} \times {\rm{Arccos}}\left( { - {\rm{tan\varphi \;}} \times {\rm{tan\delta }}} \right)\end{equation}

when ${\theta _z} = {0^o}$ means the Sun is directly overhead at the top of the atmosphere, the solar irradiance reaching the surface $\left( {{G_{on}}} \right)$ is determined based on the solar constant $({G_{sc}})$ and the specific day of the year $\left( n \right)$ . It is calculated using the following equation:

(5) \begin{equation}{G_{on}} = {G_{sc}} \times \left[ {1 + 0.033 \times {\rm{cos}}\frac{{360 \times {\rm{n}}}}{{365}}} \right]\end{equation}

Figure 1.

Illustration of the solar zenith angle.

Since the Earth’s orbit is elliptical, the distance between the Sun and the Earth varies by approximately 3.3% throughout the year. This variation affects the amount of solar irradiance reaching the Earth, contributing to seasonal differences. The solar constant ${G_{sc}}$ is considered an average value and is taken as 1367 W/m².

The hourly radiation ${I_o}$ and daily radiation ${H_o}$ can be calculated using the following equations:

(6) \begin{eqnarray} {I_O} &=& \frac{{12 \times 3600}}{\Pi } \times {G_{sc}} \times \left[ {1 + 0.033 \times cos\frac{{360 \times n}}{{365}}} \right]\nonumber\\&& \times [cos\left( \varphi \right) \times {\rm{cos}}\left( {{\rm{\;}}\delta } \right) \times \left( {sin{\omega _2} - sin{\omega _2}} \right) \times \frac{{\pi {\rm{\;}} \times {\rm{\;}}({w_2} - {w_{1)}} }}{{180}} \times sin\left( \varphi \right) \times \sin \left( {{\rm{\;}}\delta } \right)\end{eqnarray}

${\omega _2}$ and ${\omega _1}$ represent the hour angles corresponding to the selected time intervals. ${{\rm{\omega }}_{\rm{s}}}$ denotes the solar hour angle at sunrise and sunset, which defines the maximum hour angle, indicating the times when the Sun rises and sets.

(7) \begin{eqnarray}{{\rm{H}}_{\rm{o}}} &=& \frac{{24 \times 3600}}{{\rm{\pi }}} \times {{\rm{G}}_{{\rm{sc}}}} \times \left[ {1 + 0.033 \times {\rm{cos}}\frac{{360 \times {\rm{n}}}}{{365}}} \right] \nonumber\\&&\times\; {\rm{cos}}\left( {\rm{\varphi }} \right) \times {\rm{cos}}\left( {\rm{\delta }} \right) \times {\rm{sin}}{{\rm{\omega }}_{\rm{s}}} + \frac{{{\rm{\pi }} \times {{\rm{\omega }}_{\rm{s}}}}}{{180}} \times {\rm{sin\;\varphi }} \times {\rm{sin\;\delta }}\end{eqnarray}

The unit of hourly radiation is expressed as $\frac{J}{{{m^2}}}$ , while the unit of daily irradiation is $\frac{J}{{day{\rm{\;}} \times {\rm{\;}}{m^2}}}$ To convert these values into watt-hours (Wh), appropriate unit conversions are applied.

The air mass (AM) represents the path length that solar irradiation travels through the atmosphere before reaching the Earth’s surface and is calculated using the following equation [Reference Lee and Yu13, Reference Zhang, Zhang, Li and Guo15]:

(8) \begin{equation} {\rm{AM}} = \frac{{{\rm{path\;length\;travelled}}}}{{{\rm{vertical\;depth\;of\;the\;atmosphere}}}} = \frac{1}{{{\rm{cos}}{{\rm{\theta }}_{\rm{z}}}}}\end{equation}

Studies in the literature have developed a method for estimating solar irradiation transmitted under clear atmospheric conditions, considering zenith angle and altitude for standard atmospheric conditions and four different climate types [Reference Lee and Yu13, Reference Gao, Qiao, Pei, Wu and Bai16]. In solar energy systems, the two most significant types of radiation are beam radiation and diffuse radiation. Beam radiation refers to solar irradiance that reaches the Earth’s surface without being scattered by the atmosphere, while diffuse radiation is scattered in multiple directions by the atmosphere, with only a portion reaching the surface [Reference Mateja, Skarka, Peciak, Niestrój and Gude11]. The beam radiation (G _cb ) can be calculated using the following equation:

(9) \begin{equation} {{\rm{G}}_{{\rm{cb}}}} = {{\rm{\tau }}_{\rm{b}}} \times {{\rm{G}}_{{\rm{on}}}} \times \left[ {{\rm{cos}}\left( {\rm{\varphi }} \right) \times \cos \left( {\rm{\delta }} \right) \times \cos \left( {\rm{\omega }} \right) + \sin \left( {\rm{\varphi }} \right) \times \sin \left( {\rm{\delta }} \right)} \right]\end{equation}

where $\tau_{b}$ represents the ratio of transmitted beam radiation to the total radiation incident at the top of the atmosphere. This ratio can be calculated using the following equation:

(10) \begin{equation} {{\rm{\tau }}_{\rm{b}}} = \frac{{{{\rm{G}}_{{\rm{cb}}}}}}{{{{\rm{G}}_{\rm{o}}}}} = {{\rm{a}}_0} + {{\rm{a}}_1} \times {{\rm{e}}^{\left( {\frac{{ - {\rm{k}}}}{{{\rm{cos}}{{\rm{\theta }}_{\rm{z}}}}}} \right)}}\end{equation}

The hourly solar irradiance reaching the Earth’s surface is represented by ${G_o}$ , while the total solar irradiance incident on the surface at the top of the atmosphere is denoted as ${G_{on}}$ .

(11) \begin{equation} {G_o} = {G_{on{\rm{\;}}}} \times cos{\rm{\;}}{\theta _z} \end{equation}

The coefficients $\;{{\rm{a}}_0}$ , ${{\rm{a}}_1}$ and $k$ are constants calculated using Equation (12).

(12) \begin{align} {{\rm{a}}_0} &= {{\rm{r}}_0} \times (0.4237 - 0.00821 \times {\left( {6 - {\rm{A}}} \right)^2})\nonumber\\ {{\rm{a}}_1} &= {{\rm{r}}_1} \times \left( {0.5055 - 0.00595 \times {{\left( {6.5 - {\rm{A}}} \right)}^2}} \right)\\ {\rm{k}} &= {{\rm{r}}_{\rm{k}}} \times \left( {0.2711 - 0.01858 \times {{\left( {2.5 - {\rm{A}}} \right)}^2}} \right)\nonumber\end{align}

where ${\rm{\;}}A$ represents the altitude of the region above sea level, expressed in meters (m). These equations are valid only when the condition $A \lt 2.5$ is satisfied. In mid-latitude regions and during summer months, the values of ${{\rm{r}}_0}$ , ${{\rm{r}}_1}$ and ${{\rm{r}}_{\rm{k}}}$ are determined as 0.97, 0.99 and 1.02, respectively [Reference Mateja, Skarka, Peciak, Niestrój and Gude11, Reference Duffie, Beckman and Blair21, Reference Hottel23].

The diffuse solar irradiance (G _cd ) can be calculated using the following equation:

(13) \begin{equation} {{\rm{G}}_{{\rm{cd}}}} = {{\rm{\tau }}_{\rm{d}}} \times {{\rm{G}}_{{\rm{on}}}} \times \left[ {{\rm{cos}}\left( {\rm{\varphi }} \right) \times \cos \left( {\rm{\delta }} \right) \times \cos \left( {\rm{\omega }} \right) + \sin \left( {\rm{\varphi }} \right) \times \sin \left( {\rm{\delta }} \right)} \right]\end{equation}

where $\tau_{b}$ , represents the ratio of transmitted diffuse radiation to the total radiation incident at the top of the atmosphere. This ratio can be determined using Equation (14).

(14) \begin{equation} {{\rm{\tau }}_{\rm{d}}} = \frac{{{{\rm{G}}_{{\rm{cd}}}}}}{{{{\rm{G}}_{\rm{o}}}}} = 0.271 - 0.294 \times {{\rm{\tau }}_{\rm{b}}}\end{equation}

Using the equations above, it is possible to calculate the total irradiance required to determine the energy that can be harvested by solar cells. The total solar irradiance (G _c ) reaching a horizontal surface on Earth can be expressed using the following equation.

(15) \begin{eqnarray} {{\rm{G}}_{\rm{c}}} &=& {{\rm{G}}_{{\rm{cb}}}} + {{\rm{G}}_{{\rm{cd}}}} = \left( {{{\rm{\tau }}_{\rm{b}}} + {{\rm{\tau }}_{\rm{d}}}} \right) \times {{\rm{G}}_{{\rm{sc}}}} \nonumber\\[5pt]&&\times \left[ {1 + 0.033 \times {\rm{cos}}\frac{{360 \times {\rm{n}}}}{{365}}\left] \times \right[{\rm{cos}}\left( {\rm{\varphi }} \right) \times {\rm{cos}}\left( {\rm{\delta }} \right) \times {\rm{cos}}\left( {\rm{\omega }} \right) + {\rm{sin}}\left( {\rm{\varphi }} \right) \times {\rm{sin}}\left( {\rm{\delta }} \right)} \right] \end{eqnarray}

The hourly solar irradiance (I _c ) reaching a horizontal surface can be expressed using the following equation.

(16) \begin{eqnarray} {{\rm{I}}_{\rm{c}}} &=& \frac{{12 \times 3600}}{{\rm{\pi }}} \times \left( {{{\rm{\tau }}_{\rm{b}}} + {{\rm{\tau }}_{\rm{d}}}} \right) \times {{\rm{G}}_{{\rm{sc}}}} \times \left[ {1 + 0.033 \times {\rm{cos}}\frac{{360 \times {\rm{n}}}}{{365}}} \right]\nonumber\\[5pt] && \times \left[ {{\rm{cos}}\left( {\rm{\varphi }} \right) \times \cos \left( {\rm{\delta }} \right) \times \left( {{\rm{sin}}{{\rm{\omega }}_2} - {\rm{sin}}{{\rm{\omega }}_1}} \right) + \frac{{{\rm{\pi }} \times \left( {{{\rm{\omega }}_2} - {{\rm{\omega }}_1}} \right)}}{{180}} \times {\rm{sin\varphi }} \times {\rm{sin\delta }}} \right] \end{eqnarray}

A numerical analysis was conducted using these equations. The results of the sample numerical analysis based on these equations are presented in Fig. 2, illustrating the hourly solar irradiance values obtained for the Kayseri region (38.7°N, 35.5°E; elevation ≍ 1050 m) in July. Kayseri is located in Central Anatolia, Türkiye, and is characterised by a continental climate with high solar irradiance and low humidity, making it a representative location for evaluating the performance of solar-powered UAV systems.

Figure 2.

Hourly variation of Global Horizontal (GHI), Direct Normal (DNI) and Diffuse Horizontal (DHI) solar irradiance throughout a typical July day in the Central Anatolia region, illustrating the diurnal distribution of solar energy components under clear-sky conditions.

Figure 2 Long description

A line graph displays the hourly variation of solar irradiance throughout a typical July day in the Central Anatolia region. The graph features three distinct data series: Global Horizontal Irradiance (GHI) in yellow, Direct Normal Irradiance (DNI) in red, and Diffuse Horizontal Irradiance (DHI) in blue. The x-axis represents the hour of the day, ranging from 0 to 22, while the y-axis indicates irradiance in watts per square meter, scaling from 0 to 1000. The graph illustrates the diurnal distribution of solar energy components under clear-sky conditions, with GHI peaking around midday and DNI following a similar pattern but with slightly lower values. DHI shows a smaller peak and remains relatively low throughout the day. The lines for GHI and DNI rise sharply in the morning, reach their maximum around noon, and then gradually decline in the afternoon, while the DHI line shows a more gradual increase and decrease.

As solar radiation passes through the atmosphere, it is divided into different components, which are fundamental parameters in the performance analysis of solar energy systems. Solar irradiance consists of three main components: Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI) and Diffuse Horizontal Irradiance (DHI). GHI refers to the total solar irradiance received on a horizontal surface and is the sum of DNI and DHI. DNI represents the amount of solar radiation received directly from the Sun without atmospheric scattering. DHI refers to the fraction of solar radiation that is scattered by atmospheric gases, aerosols and clouds, reaching the surface from multiple directions [Reference Eissa, Marpu, Gherboudj, Ghedira, Ouarda and Chiesa24].

2.2 Effect of cloudiness

Clouds have a significant effect on solar irradiation, and this effect depends on the type, density and location of the clouds. Clouds block solar irradiation, reducing the energy reaching the surface. This negatively affects the performance of PV systems. In general, clouds can be classified into three main categories. These are high-level clouds (e.g. cirrus), mid-level clouds (e.g. altostratus) and low-level thick clouds (e.g. cumulonimbus). While high-level clouds do not significantly affect irradiation, low-level clouds significantly block solar irradiation, negatively affecting energy production [Reference Dumka, Kosmopoulos, Ningombam and Masoom25–Reference Mestnikov, Vasilyev, Davydov, Khoyutanov and Alzakkar27].

Cloud cover is evaluated using the okta scale, which quantifies the proportion of the sky covered by clouds. This scale ranges from 0 (completely clear sky) to 8 (completely overcast) [Reference Jebar, Parisi, Downs and Turner28]. The impact of cloud cover on solar irradiance is illustrated in Fig. 3.

Figure 3.

Effect of cloud cover on solar irradiance transmission.

Figure 3 Long description

A line graph titled 'Effect of Cloud Cover on Solar Irradiance' displays the relationship between cloud cover and solar irradiance transmission. The x-axis represents the Okta cloud cover scale ranging from 0 to 8, while the y-axis represents irradiance transmission in percentage, ranging from 0 to 100 percentage. The graph shows a downward trend, indicating that as cloud cover increases, solar irradiance transmission decreases. Key data points include 100 percentage transmission at 0 Okta, 98 percentage at 1 Okta, 94 percentage at 2 Okta, 88 percentage at 3 Okta, 79 percentage at 4 Okta, 70 percentage at 5 Okta, 54 percentage at 6 Okta, 50 percentage at 7 Okta, and 27 percentage at 8 Okta. All values are approximated.

In the cloud cover scale, values above 8 oktas are generally associated with a completely overcast sky, where a significant portion of solar irradiance is lost. Studies in the literature indicate that understanding the impact of cloud cover on solar irradiance is crucial for the efficient design and operation of solar energy systems [Reference Myers29–Reference Wacker, Gröbner, Zysset, Diener, Tzoumanikas, Kazantzidis, Vuilleumier, Stöckli, Nyeki and Kampfer31].

In the simulation model developed for this study, the effect of cloudiness on solar irradiance was explicitly incorporated to ensure realistic environmental modeling. The solar irradiance incident on the PV surface, denoted by I, was adjusted according to the empirical cloud transmittance relationship proposed by Kasten and Czeplak [Reference Kasten and Czeplak32], expressed as:

(17) \begin{equation} I = {I_0}\left( {1 - 0.75\;X\;c{c^{3.4}}} \right)\end{equation}

where ${I_0}$ represents the clear-sky global irradiance (i.e. the irradiance in the absence of clouds) and cc denotes the fractional cloud cover, ranging from 0 (completely clear sky) to 1 (fully overcast conditions). This formulation quantifies the attenuation of solar radiation as a function of cloudiness and has been widely adopted in solar energy performance and atmospheric transmittance modeling.

For the numerical simulations in this study, July was selected as the representative month for the Kayseri region because it exhibits the highest average solar irradiance and the lowest mean cloud cover, providing optimal conditions for evaluating solar-powered UAV performance. According to meteorological data from the Turkish State Meteorological Service (TSMS), the average cloud cover fraction in Kayseri during July ranges between 0.15 and 0.20, corresponding to predominantly clear-sky conditions. Therefore, the inclusion of this cloud attenuation model ensures that the solar energy calculations realistically reflect the influence of atmospheric variability while focusing on the most favourable operational period for solar-powered UAV missions.

2.3 Effect of temperature

Temperature is a critical factor affecting the efficiency of solar cells. As temperature increases, the efficiency of solar cells decreases, negatively impacting the energy conversion process [Reference Wu, Li, Roibás-Millán, Alonso-Moragón and Jiménez-Mateos33]. Each solar cell has a temperature coefficient, which is associated with voltage, current and power parameters, determining the effect of temperature variations on its performance. An increase in temperature degrades the electrical properties of the cells, leading to a reduction in power output and overall efficiency [Reference Duffie and Beckman34, Reference Kazem and Chaichan35].

With every 100-meter increase in altitude, the air temperature decreases by approximately 0,5∼1°C. The distribution of air temperature is largely influenced by latitude, altitude, seasonal variations and topographical features. These temperature drop calculations remain valid up to the tropopause, where the upper atmospheric layer maintains a stable temperature reaching approximately (−51°C). This temperature level is sustained up to an altitude of 20 km [Reference Mateja, Skarka, Peciak, Niestrój and Gude11].

The decline in solar cell efficiency with increasing temperature is primarily related to the heating of the solar cell under solar irradiation and its reduced heat dissipation capacity in high ambient temperatures. Operating PV panels at elevated temperatures not only results in lower electrical power output but also accelerates the degradation process of solar cells, reducing their long-term performance and reliability [Reference Al-Luhaiby36].

The current ambient temperature is correlated with flight altitude and can be calculated using the following equation,

(18) \begin{equation} {T_C} = {T_I} - \left[ {{H_R}{\rm{\;}}x{\rm{\;}}\left( {{T_D}{\rm{\;}}x{\rm{\;}}100} \right)} \right]\end{equation}

where ${T_C}$ represents the temperature at the flight altitude, ${T_I}$ is the temperature at ground level, ${H_R}$ denotes the relative altitude in meters and ${T_D}$ refers to the temperature lapse rate. According to this calculation, when the relative humidity is below 100%, the temperature decreases by approximately 1°C per 100 meters of altitude gain. However, when the relative humidity reaches 100%, the release of latent heat due to condensation slows the temperature decline, resulting in a decrease of approximately 0.6°C per 100 meters [Reference Hemond and Fechner37].

Another critical component affected by temperature is lithium-ion (Li-ion) batteries. The sensitivity of Li-ion batteries to temperature variations is a key factor directly influencing their performance. The optimal operating temperature range for Li-ion batteries is between 25°C and 30°C [Reference Carnovale and Li38]. At low temperatures, the viscosity of the electrolyte increases, leading to a reduction in ionic conductivity and a rise in internal resistance. At (−20°C), in particular, the charge transfer resistance increases significantly, causing a substantial decline in both capacity and power output. Under high temperature conditions, the performance of Li-ion batteries is influenced by more complex mechanisms. Heat generation becomes a significant factor, especially during rapid charging and discharging. Excessive internal temperatures lead to capacity degradation and power loss [Reference Ma, Jiang, Tao, Song, Wu, Wang, Deng and Shang39].

2.4 Pollution of air and solar cells

Air pollution and solar cell contamination are two key environmental factors that significantly reduce the efficiency of PV panels. Air pollution weakens solar irradiation as it enters the atmosphere through reflection, scattering and absorption, thereby reducing the amount of sunlight reaching the panels [Reference Song, Liu and Yang40]. However, it is very difficult to measure these data precisely due to the continuous variability of environmental conditions. Pollutants such as dust layer, smoke and soot particles from industrial emissions, and dew, which accumulate at different levels on the surface of the solar cell, cause negative effects on its performance by reducing the light receiving capacity of the panel [Reference Kazem and Chaichan35].

In order to better understand the effects of pollutants deposited on solar cells and to minimise these effects, the classification of pollutants is of great importance. This classification facilitates the identification of pollution sources and seasonal changes. Pollutants can be generally divided into three main categories. The first category is pollutants of atmospheric origin and includes airborne particulate matter such as dust, smoke and soot. The second category consists of pollutants due to environmental factors. This group includes pollutants of natural origin such as hoarfrost, snow, pollen and organic materials. The third category consists of pollutants of local origin and includes substances such as particles emitted from industrial areas or soil transported from agricultural areas. Such categorisation allows the development of effective cleaning protocols for solar cells in a given geographical area.

The effects of air and surface pollution on the power supply systems of solar-powered UAVs should also be carefully analysed. The intensity and impact of pollutants are directly related to the mission duration of the UAV. While instantaneous pollution is usually negligible during short duration missions, pollutant accumulation becomes a significant problem during long duration missions and necessitates regular cleaning. Therefore, the effects of pollution should be evaluated by considering the time and mission duration parameters.

While some pollutants have instantaneous effects and cause short-term performance losses, others may cause permanent performance decreases in the long term. For example, while the accumulation of hoarfrost and snow in winter months temporarily reduces the radiation absorption capacity of solar cells, dust accumulation in summer months can cause longer and permanent performance losses. These effects are related to both atmospheric pollution and environmental factors and vary depending on seasonal variations [Reference Mateja, Skarka, Peciak, Niestrój and Gude11].

2.5 Flight path and solar irradiation angle

The flight duration of solar-powered UAVs is directly related to solar irradiance angle and flight path optimisation. To achieve maximum energy generation, the irradiance angle must be maintained at an optimal level. The angle of incoming sunlight is determined by the aircraft’s position, tilt angle and orientation. An optimal flight path should be designed considering these factors to ensure maximum solar irradiance exposure throughout the day [Reference Huang, Chen, Wang and Su12].

In this study, gravitational potential energy utilisation is incorporated into flight path optimisation to extend the flight duration of solar-powered UAVs. Particularly during night flights, the excess energy harvested during the daytime allows the UAV to ascend to higher altitudes, accumulating potential energy. This stored energy is then gradually released during the night, enabling the UAV to glide downward efficiently, thereby optimising energy consumption and extending operational endurance [Reference Lee and Yu13].

Additionally, meteorological variables must be considered during flight path planning. For instance, UAVs operating at lower altitudes are more susceptible to atmospheric variations, while determining the optimal flight angle and altitude enhances long-term endurance. Real-time optimisation algorithms can continuously adjust the UAV’s flight path by accounting for variables such as wind conditions, air density and cloud cover. The optimisation of flight trajectory and solar irradiance angle is regarded as a critical parameter for maximising energy harvested from solar cells and extending the UAV’s flight duration [Reference Tkachyck, Kotcemyr, Sokolovskyi and Bilous41].